Research Article Simple Simulated Propagation Modeling and Experimentation within and around Buildings at 2700 MHz Tanay Bhatt 1 and Jonathan Bredow 2 1 Department of Electrical Engineering, Arkansas State University, P.O. Box 1740, State University, AR 72467, USA 2 Department of Electrical Engineering, University of Texas at Arlington, P.O. Box 19016, Arlington, TX 76019, USA Correspondence should be addressed to Tanay Bhatt; [email protected] Received 16 September 2015; Revised 23 December 2015; Accepted 10 January 2016 Academic Editor: Sanghyun Ahn Copyright © 2016 T. Bhatt and J. Bredow. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ere is a growing interest in understanding wave behavior in urban and suburban environment for 5th generation broadband applications. With the advent of using broadband technologies in buildings, office space and vehicle have become a necessity on a large scale. Models, predictions, and calculations for in-building, within a vehicle or near a reflective object with microscale details, are becoming highly classified in a competitive telecom environment. is paper provides an improved understanding of signal strength behavior within suburban residences with predictions prequalified using a vehicular scanner. Supporting predictions are provided by a ray tracing algorithm developed for dissertation. Results indicate signal strength variation of more than 50 dB from “strong signal” locations such as room centers and far corners to “weak signal” locations where shadowing and tunneling effects are evident. Based on this unique classification a scheme is proposed which indicates that specular scattering provides the major signal energy at more than 70% of the locations within the residences. Finally, an observed rake stabilizing effect is attributed to the proximity of strong scatterers. 1. Introduction With the coming of new wireless technologies, ird-Gener- ation Partnership Project (3GPP), wideband-CDMA (WCDMA), 802.11, Bluetooth, and Ultra-wide Band (UWB) systems are rapidly gaining interest and market penetration. Analysts in the USA are predicting more than 20 million broadband portable systems by the end of this decade. An increased percentage of these broadband technologies are being deployed for in-building coverage and capacity. Indoor coverage available using radio frequencies (1 GHz−3 GHz) in the licensed UHF bands for broadband wireless systems depends on the multipath and attenuation as these electromagnetic waves pass through the structure. A formula-based approach to predicting the signal strength at any given position in the structure is desired. With the base station transmitter at an external location, this formula attempts to predict coverage or signal strength within a given structure. Initial work was presented by Walker 1983 [1] and subsequently by others [2–5]. An empirical model with transmitter located at only high altitude to study angular reflection and diffraction was presented for a rectangular building by Axiotis and eologou [6]. An urban low ele- vation, lamp post levels transmitter installation study was presented with interference analysis supporting urban envi- ronment structures in 1700 MHz [7], producing a simple path loss model with high -factors at 2.5 GHz and different building constructions [8] and using “best fit” analysis at 900 MHz [9]. A similar study in urban microcell settings was experimented with time delayed arrivals causing higher interference through buildings [10] and a 2D model for ray tracing within buildings inclusive of building penetration loss [11] with some shadowing and subsequently experimental results with foliage shadowing at 5.85 GHz [12]. An experiment in a suburban environment using time delay spread with root mean square (RMS) that doubled at every 19 dB of path loss was observed by Devasirvatham et al. [13]. Previous works were proposed to evaluate mobile antennas performance compared to a reference antenna with a mean effective gain in an urban/suburban environment [14] Hindawi Publishing Corporation International Journal of Vehicular Technology Volume 2016, Article ID 9846374, 10 pages http://dx.doi.org/10.1155/2016/9846374
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Research ArticleSimple Simulated Propagation Modeling and Experimentationwithin and around Buildings at 2700 MHz
Tanay Bhatt1 and Jonathan Bredow2
1Department of Electrical Engineering Arkansas State University PO Box 1740 State University AR 72467 USA2Department of Electrical Engineering University of Texas at Arlington PO Box 19016 Arlington TX 76019 USA
Correspondence should be addressed to Tanay Bhatt tbhattastateedu
Received 16 September 2015 Revised 23 December 2015 Accepted 10 January 2016
Academic Editor Sanghyun Ahn
Copyright copy 2016 T Bhatt and J Bredow This is an open access article distributed under the Creative Commons AttributionLicense which permits unrestricted use distribution and reproduction in any medium provided the original work is properlycited
There is a growing interest in understanding wave behavior in urban and suburban environment for 5th generation broadbandapplications With the advent of using broadband technologies in buildings office space and vehicle have become a necessity on alarge scale Models predictions and calculations for in-building within a vehicle or near a reflective object with microscale detailsare becoming highly classified in a competitive telecom environment This paper provides an improved understanding of signalstrength behavior within suburban residences with predictions prequalified using a vehicular scanner Supporting predictions areprovided by a ray tracing algorithm developed for dissertation Results indicate signal strength variation of more than 50 dB fromldquostrong signalrdquo locations such as room centers and far corners to ldquoweak signalrdquo locations where shadowing and tunneling effectsare evident Based on this unique classification a scheme is proposed which indicates that specular scattering provides the majorsignal energy at more than 70 of the locations within the residences Finally an observed rake stabilizing effect is attributed to theproximity of strong scatterers
1 Introduction
With the coming of new wireless technologies Third-Gener-ation Partnership Project (3GPP) wideband-CDMA(WCDMA) 80211 Bluetooth and Ultra-wide Band (UWB)systems are rapidly gaining interest and market penetrationAnalysts in the USA are predicting more than 20 millionbroadband portable systems by the end of this decade Anincreased percentage of these broadband technologies arebeing deployed for in-building coverage and capacity
Indoor coverage available using radio frequencies(1 GHzminus3GHz) in the licensed UHF bands for broadbandwireless systems depends on the multipath and attenuationas these electromagnetic waves pass through the structureA formula-based approach to predicting the signal strengthat any given position in the structure is desired With thebase station transmitter at an external location this formulaattempts to predict coverage or signal strength within a givenstructure Initial work was presented by Walker 1983 [1]and subsequently by others [2ndash5] An empirical model with
transmitter located at only high altitude to study angularreflection and diffraction was presented for a rectangularbuilding by Axiotis and Theologou [6] An urban low ele-vation lamp post levels transmitter installation study waspresented with interference analysis supporting urban envi-ronment structures in 1700MHz [7] producing a simplepath loss model with high 119896-factors at 25 GHz and differentbuilding constructions [8] and using ldquobest fitrdquo analysis at900MHz [9] A similar study in urban microcell settingswas experimented with time delayed arrivals causing higherinterference through buildings [10] and a 2D model for raytracingwithin buildings inclusive of building penetration loss[11] with some shadowing and subsequently experimentalresults with foliage shadowing at 585GHz [12]
An experiment in a suburban environment using timedelay spread with root mean square (RMS) that doubled atevery 19 dB of path loss was observed by Devasirvatham etal [13] Previous works were proposed to evaluate mobileantennas performance compared to a reference antenna withamean effective gain in an urbansuburban environment [14]
Hindawi Publishing CorporationInternational Journal of Vehicular TechnologyVolume 2016 Article ID 9846374 10 pageshttpdxdoiorg10115520169846374
2 International Journal of Vehicular Technology
with multiple efficiency characterized over different polar-izations however results were outlined without a directionalhorn antenna to specifically quantify the angular scattering
Specific attenuation measurements with lower sample ofresults through cinder block building was presented withlinear polarization for 200MHz to 3GHz [15]
Via analysis of measurements and with simulation sup-port this paper focuses on the topics of improved under-standing of signal strength behavior within residences in asuburban environment in terms of features of the indoorenvironment use of rake activity as an indicator of qualityof the local radio environment and impact of terrain foliageand nearby buildings on the indoor signal strength A classi-fication scheme based on rake finger activity is proposed thatquantifies the impact on electromagnetic wave propagationmechanisms at various locations within a residence that is interms of specular scattering tunneling and edge diffraction
Once further testing is concluded this could lead tomicroscale models within residential buildings for generat-ing a tailored indoor or on amicroscale dense urban vehicularcoverage prediction maps In the second area of focus ithas been found that variability over time in the number ofrake fingers used in this classification scheme based on theenvironment that is rake activity relates to the presenceof large scatterers within a few tens of wavelengths of thereceiver As long as the large scatterers do not shadow thereceiver the tendency is for these large scatterers to stabilizethe number of rake fingers used compared to greater or erraticrake finger activity In the final focus area the degree of devia-tion between predictions based on commercially available RFplanning tools and measured signal strengths is examined toassess effects of objects and terrain outside of the residenceIn this work it is noticed that ray tracing predictions whichaccount only for effects of the building studied much moreclosely follow measurement values for the 2nd floor than forthe 1st floor presumably because the terrain and surroundingfoliage and buildings have less impact on propagation withinthe 2nd floor for a typical suburban area
2 Experimental Setup and DataCollectionProcessing
To enable testing in theMultichannelMultipointDistributionService (MMDS) frequency band of 25ndash27GHz using a PCSW-CDMA scanner a down-converter was developed Thisdrive test system enables the measurement of the strong-est N signals found in each time slot of 2560 chips The blockdiagram for the test setup and configuration of all equipmentis shown in Figure 1 As in other CDMA systems in W-CDMA each transmitter output signal is scrambled by multi-plying all of its data channels by a unique pseudonoise (PN)code referred to in the W-CDMA specification as a scram-bling code Amobile receiver can distinguish one transmitterfrom another by correlating the received signal spectrumwith a scrambling code that is identical to that used in thedesired transmitter Similarly each mobile receiver outputsignal is scrambled with a unique scrambling code that allowsthe transmitter receiver to discern one mobile receiver from
Down-converter
Duplexer
LNA
To +12 VDCTx
RxRx inRx out
RF
RF input
RF out
CommonMag-mountantenna
LO IF
Mixer
Signal generator
Lap top
ScannerSerial port
GPS antenna
GPs antenna
Figure 1 Block diagram of the portable vehicle mounted receivingsystem
Figure 2 Test site locations relative to transmitter showing 65-degree coverage area
another The scrambling codes are applied at a fixed rate of3840Mcps The purpose of the rake receiver is to performmaximal ratio combining of received multipaths in order tomaximize SNR as well as despread the received chips intosymbols The 8 rake-fingers share the same time slot withinthe hardware prior to being processed by the combining stage
The2600MHz systemswere located inAustin TX Trans-mitter antennas for the 2 sectors were located on top of a9-story building 396 meter Above Ground Level (AGL)Figure 2 shows the transmitter as well as the two residentialtest site locations Power levels are estimated using the IEEE80216 suburban model [16]
After a thorough drive test using the portable vehiclemounted test system shown in Figure 1 the data was cor-related and tuned to the predicted coverage plots for asuburban environmentThe buildings were selected as muchas possible to represent a range of natural architectural andlocal environmental characteristics with wood framework
International Journal of Vehicular Technology 3
Table 1 Building information
Building ID DescriptionB2A Building 2A two-floor house stonevinyl construction composite roof and 2-car garageB3A Building 3A single floor house brick construction composite sloped roof and 2-car garage
sheet rock and composite sloped roofs Table 1 summarizeseach building construction
To form a file of fast-fading components each sample ofdata collected in a given environment was normalized by theaverage signal strength within that environment To controlthe pedestrian effects only a single person was in the vicinityof the test gear Collection of statistics was commenced afterone minute to compensate for electromagnetic effects causedby human presence These statistics could be correlated backto a dense urban mobile environment The local mean wasestimated by averaging the signal strength over 1000 samplesthat is the system is to collect 1 measurement at 100msintervals for 10000ms Figures 3 and 4 indicate normalizedreceive power levels measured for various locations insideand outside of the two residential test sites Although thesetests could have directly been conducted in a dense urbanvehicular settings the decision to show comparable results ina pedestrian suburban model was taken into considerationdue to logistics and personnel at hand
Parameters considered for evaluation are mean andstandard deviation of measured power mean and standarddeviation of 119864
119888119873
0 RMS delay spread and variability in
rake finger activity The primary RF design parameter forCDMA systems is the SNR or chip energy (119864
119888) of a specific
CDMA channel in relation to the noise (1198730) energy known
as the 119864
119888119873
0ratio The transmitter and receiver use an
119864
119904119873
0estimator to measure the ratio of symbol (119864
119904) to noise
(1198730) energy for a particular channel (eg BDCH) Spread
Factor (SF) is dynamically controlled within the receiverTherelationship between 119864
119888119873
0and 119864
119904119873
0is as follows
119864
119888
119873
0
(dB) = minus10 lowast log10(SF) +
119864
119904
119873
0
(1)
Codespace can be viewed as consisting of 512 units of band-width A SF = 512 channel uses 1 unit a SF = 256 channel uses2 units a SF = 128 channel uses 4 units and a SF = 4 channeluses 128 units More units effectively correspond to a higherbandwidth channel
The relation between bit energy119864119887119873
0and symbol energy
119864
119904119873
0is reasonably straightforward For 119872-PSK119872-QAM
modulation the number of bits in each constellation symbolis
119896 = log2119872 (2)
Since each symbol carries 119896 bits the symbol to noise ration119864
119904119873
0is 119896 times the bit to noise ratio 119864
119887119873
0 or
119864
119904
119873
0
=
119896119864
119887
119873
0
(3)
Using the above formula the symbol error rate versus bitenergy (SNR per bit 119864
119887119873
0) for the system under test can
thus give as
119875
1199044QAM = erfc (radic119864
119887
119873
0
) (4)
Mean and standard deviation of measured power and119864
119888119873
0are obtained by considering measurements within a
local cluster For example the means and standard deviationsof power and119864
119888119873
0at location 31 in Figure 4 are formed from
the time average measurements at locations 27 through 31RMS delay spread is found according to
RMS delay spread = 119878 = [sum
119873
119896=1(119905
119896minus 119889)
2
119875 (119905
119896)
sum
119873
119896=1119875 (119905
119896)
]
12
(5)
where 119889 is the mean time delay 119905119896is the time delay (in
seconds) relative to the start of the power delay profile (PDP)119875 is the signal power (W) and 119873 is the index of the finalPDP signal point consideredVariability in rake finger activitysimply relates to how much the number of active fingerschanges over the measurement interval
3 The Simulator
The simulator based on the zero-wavelength approximationtreating waves as rays has been found to give reasonablepredictions of path loss and RMS delay spread for the indoorenvironments studied here General ray tracing in an indoorenvironment assumes that direct reflected refracted anddiffracted rays all carry some energy to the receiver althoughone or more of these may be negligible Note that each ray isconsidered to be a tube that opens up as the wave propagatesthis opening up represents energy spreading (the energy inthe tube is considered to be constant) Although after locat-ing a scattering point the reception test is performed basedon reception sphere concept this method is successfullyapplicable to complex environmentwhich requires enormouscomputing time and memoryThe reflected rays are assumedto emanate from the mirror image of the source onto the flatsection of wall ceiling or floor and the refracted ray is nearlyparallel to the incident ray with a slight path length deviationof Δ119889 where
Δ119889 =
119889 sin (120579119894minus 120579
119905)
cos 120579119905
(6)
119889 is the thickness of the wall ceiling or floor and 120579
119894 120579119905
are the angles of incidence and refraction respectively Thediffracted field that is due to illumination of outside cornersis calculated using the UniformTheory of Diffraction (UTD)
4 International Journal of Vehicular Technology
B2A first floor2-story stone construction composite roof and all measurements in feet2 times 55 5 times 55
2 times 51 5 times 51
8 times 12
0 times 19
0 times 38
0 times 16
0 times 0
2 times 0
1 2 3 4
567
8
9
1011
12
13
14
15
16
17
18 19
2021
Kitchen wisland
Entrance
Power (dB)
Living
Closet
Deck
Shed
Garage 2-car
Play room wpool table
N
BS
15998400
10998400
lt25lt35
lt45lt55
16 times 50
48 times 38
48 times 22
35 times 38
35 times 2230 times 22
30 times 21 35 times 21
26 times 1814 times 19
16 times 38
14 times 16
10 times 20
19 times 18
26 times 21
19 times 22
48 times 21
20 times 1228 times 13
48 times 046 times 038 times 025 times 0
23 times 013 times 012 times 0
28 times 822 times 8
22 times 13
25 times 16
35 times 50
(a)
9 times 380 times 38
8 times 10
8 times 12
9 times 28
9 times 20
0 times 0
33 times 4819 times 48
17 times 38 19 times 38 33 times 38 38 times 38 48 times 38
17 times 2015 times 20
11 times 20
11 times 2815 times 28 17 times 28
22 times 20
38 times 15
35 times 1328 times 13
22 times 13
35 times 15
38 times 27 48 times 27
48 times 15
28 times 8
35 times 0 48 times 0
22 times 8
17 times 0
15 times 10
B2A second floor2-story stone construction composite roof and all measurements in feetCPE at 3-feet above ground
2223
2425
26
27
28
29
30
31
lt35lt45lt55
Balcony
Masterbath
StudyMedia room Closed
Closed
ClosedMaster bedroom
Power (dB)
(b)
Figure 3 B2A Blue Print Model showing test positions and measured power for (a) first floor and (b) second floor
International Journal of Vehicular Technology 5
Single story brick construction composite roof and all measurements in feet
Bedroom
Master bedroom
Living
Garage 2 car
N
BS
123
Entrance
4 5 6
Playroom
Dining
Bedroomclosed
Breakfast
Kitchen
Bath
Patio
Den
Bedroom
Bath
OfficeStorage
Closet
Bath
Exercise room
78
9 10
11
1516
19
17 18
20 26
25
22 23
2421
43
4244
40
3938
37
413433
32 3536
29 30
2728
31
12
1314
0
0
Power (dB)lt15lt25
lt35lt45
10998400
15998400
43 times 26
43 times 31
35 times 26
35 times 31
39 times 3933 times 39
24 times 2928 times 29
28 times 3124 times 31
18 times 29
18 times 31
14 times 29
14 times 31
29 times 39 43 times 39
39 times 5
35 times 17
35 times 2139 times 21
39 times 1743 times 17
57 times 039 times 0
57 times 2143 times 21
43 times 34
43 times 43
57 times 3452 times 34
52 times 4349 times 43
49 times 47
57 times 51
57 times 4743 times 47
43 times 5129 times 51
29 times 41
29 times 28
29 times 19
29 times 522 times 511 times 5
11 times 14
22 times 1911 times 19
11 times 31
11 times 41
11 times 510 times 51
0 times 41
0 times 31
0 times 14
14 times 13 6 times 6
13 times 14
19 times 12
9 times 11
8 times 11
11 times 1411 times 14
19 times 14
13 times 15
14 times 11
B3A CPE at 1m height at all locations
Figure 4 Blue Print Model of residence B3A as tested (numbers indicate test positions and measured power)
The ray tracing-based simulator developed for this workis composed of two main parts The first part referred to asthe ray tracer defines the geometrical paths taken by the radiowave to reach the receiver The second part referred to as theelectromagnetic tracer ormodeler determines themagnitudeand phase of the signal along each path upon arrival at thereceiver That is it produces a file containing informationabout the complex impulse response of the radio channel thatis of the form [17]
ℎ (119905) =
119873
sum
119899=1
119860
119899120575 (119905 minus 120591
119899) exp (minus119895120599
119899) (7)
where there are 119873 time-delayed impulses (rays) each rep-resented by an attenuated and phase-shifted version of theoriginal transmitted impulse for which the amplitude is 119860
119899
the arrival time is 120591119899 and the phase is 120599
119899 Reflected and trans-
mitted rays are evaluated through use of geometrical opticswhile diffracted rays are calculated using geometrical theory
of diffraction [17] Accordingly the complex amplitude alongeach path is obtained as
119864
119894= 119864
119900119865
119905119894119865
119903119894Π
119895119877
119895Π
119896119879
119896Π
119905119860
119905(119904
1015840
119904)119863
119905
119890
minus119895119896119889
119889
(8)
where 119864119900represents the reference field 119865
119905119894and 119865
119903119894represent
the transmitting and receiving antenna field radiation pat-terns in the direction of the ray 119877
119895represents the reflection
coefficient for the 119895th reflection 119879119896represents the wall trans-
mission coefficient for the 119896th transmission 119863119905represents
the diffraction coefficient for the 119894th diffracting wedge andexp(minus119895119896119889) represents the propagation phase factor due tothe path length 119889
119905(119896 = 2120587120582) 119860
119905(119904
1015840
119904) provides the correctspatial attenuation for the diffracted rays
Both the simulator and the floor plan module used bythe simulator (the latter developed by [18]) are MATLABregbased The source file for the floor plan module includesthematerial characteristics (conductivity and permittivity) ofeach wall floor and ceiling section as well as the 119909 119910 119911 pointsof each corner for the configuration Material parameters
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
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RotatingMachinery
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Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
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Shock and Vibration
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Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
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Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
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Chemical EngineeringInternational Journal of Antennas and
Propagation
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DistributedSensor Networks
International Journal of
2 International Journal of Vehicular Technology
with multiple efficiency characterized over different polar-izations however results were outlined without a directionalhorn antenna to specifically quantify the angular scattering
Specific attenuation measurements with lower sample ofresults through cinder block building was presented withlinear polarization for 200MHz to 3GHz [15]
Via analysis of measurements and with simulation sup-port this paper focuses on the topics of improved under-standing of signal strength behavior within residences in asuburban environment in terms of features of the indoorenvironment use of rake activity as an indicator of qualityof the local radio environment and impact of terrain foliageand nearby buildings on the indoor signal strength A classi-fication scheme based on rake finger activity is proposed thatquantifies the impact on electromagnetic wave propagationmechanisms at various locations within a residence that is interms of specular scattering tunneling and edge diffraction
Once further testing is concluded this could lead tomicroscale models within residential buildings for generat-ing a tailored indoor or on amicroscale dense urban vehicularcoverage prediction maps In the second area of focus ithas been found that variability over time in the number ofrake fingers used in this classification scheme based on theenvironment that is rake activity relates to the presenceof large scatterers within a few tens of wavelengths of thereceiver As long as the large scatterers do not shadow thereceiver the tendency is for these large scatterers to stabilizethe number of rake fingers used compared to greater or erraticrake finger activity In the final focus area the degree of devia-tion between predictions based on commercially available RFplanning tools and measured signal strengths is examined toassess effects of objects and terrain outside of the residenceIn this work it is noticed that ray tracing predictions whichaccount only for effects of the building studied much moreclosely follow measurement values for the 2nd floor than forthe 1st floor presumably because the terrain and surroundingfoliage and buildings have less impact on propagation withinthe 2nd floor for a typical suburban area
2 Experimental Setup and DataCollectionProcessing
To enable testing in theMultichannelMultipointDistributionService (MMDS) frequency band of 25ndash27GHz using a PCSW-CDMA scanner a down-converter was developed Thisdrive test system enables the measurement of the strong-est N signals found in each time slot of 2560 chips The blockdiagram for the test setup and configuration of all equipmentis shown in Figure 1 As in other CDMA systems in W-CDMA each transmitter output signal is scrambled by multi-plying all of its data channels by a unique pseudonoise (PN)code referred to in the W-CDMA specification as a scram-bling code Amobile receiver can distinguish one transmitterfrom another by correlating the received signal spectrumwith a scrambling code that is identical to that used in thedesired transmitter Similarly each mobile receiver outputsignal is scrambled with a unique scrambling code that allowsthe transmitter receiver to discern one mobile receiver from
Down-converter
Duplexer
LNA
To +12 VDCTx
RxRx inRx out
RF
RF input
RF out
CommonMag-mountantenna
LO IF
Mixer
Signal generator
Lap top
ScannerSerial port
GPS antenna
GPs antenna
Figure 1 Block diagram of the portable vehicle mounted receivingsystem
Figure 2 Test site locations relative to transmitter showing 65-degree coverage area
another The scrambling codes are applied at a fixed rate of3840Mcps The purpose of the rake receiver is to performmaximal ratio combining of received multipaths in order tomaximize SNR as well as despread the received chips intosymbols The 8 rake-fingers share the same time slot withinthe hardware prior to being processed by the combining stage
The2600MHz systemswere located inAustin TX Trans-mitter antennas for the 2 sectors were located on top of a9-story building 396 meter Above Ground Level (AGL)Figure 2 shows the transmitter as well as the two residentialtest site locations Power levels are estimated using the IEEE80216 suburban model [16]
After a thorough drive test using the portable vehiclemounted test system shown in Figure 1 the data was cor-related and tuned to the predicted coverage plots for asuburban environmentThe buildings were selected as muchas possible to represent a range of natural architectural andlocal environmental characteristics with wood framework
International Journal of Vehicular Technology 3
Table 1 Building information
Building ID DescriptionB2A Building 2A two-floor house stonevinyl construction composite roof and 2-car garageB3A Building 3A single floor house brick construction composite sloped roof and 2-car garage
sheet rock and composite sloped roofs Table 1 summarizeseach building construction
To form a file of fast-fading components each sample ofdata collected in a given environment was normalized by theaverage signal strength within that environment To controlthe pedestrian effects only a single person was in the vicinityof the test gear Collection of statistics was commenced afterone minute to compensate for electromagnetic effects causedby human presence These statistics could be correlated backto a dense urban mobile environment The local mean wasestimated by averaging the signal strength over 1000 samplesthat is the system is to collect 1 measurement at 100msintervals for 10000ms Figures 3 and 4 indicate normalizedreceive power levels measured for various locations insideand outside of the two residential test sites Although thesetests could have directly been conducted in a dense urbanvehicular settings the decision to show comparable results ina pedestrian suburban model was taken into considerationdue to logistics and personnel at hand
Parameters considered for evaluation are mean andstandard deviation of measured power mean and standarddeviation of 119864
119888119873
0 RMS delay spread and variability in
rake finger activity The primary RF design parameter forCDMA systems is the SNR or chip energy (119864
119888) of a specific
CDMA channel in relation to the noise (1198730) energy known
as the 119864
119888119873
0ratio The transmitter and receiver use an
119864
119904119873
0estimator to measure the ratio of symbol (119864
119904) to noise
(1198730) energy for a particular channel (eg BDCH) Spread
Factor (SF) is dynamically controlled within the receiverTherelationship between 119864
119888119873
0and 119864
119904119873
0is as follows
119864
119888
119873
0
(dB) = minus10 lowast log10(SF) +
119864
119904
119873
0
(1)
Codespace can be viewed as consisting of 512 units of band-width A SF = 512 channel uses 1 unit a SF = 256 channel uses2 units a SF = 128 channel uses 4 units and a SF = 4 channeluses 128 units More units effectively correspond to a higherbandwidth channel
The relation between bit energy119864119887119873
0and symbol energy
119864
119904119873
0is reasonably straightforward For 119872-PSK119872-QAM
modulation the number of bits in each constellation symbolis
119896 = log2119872 (2)
Since each symbol carries 119896 bits the symbol to noise ration119864
119904119873
0is 119896 times the bit to noise ratio 119864
119887119873
0 or
119864
119904
119873
0
=
119896119864
119887
119873
0
(3)
Using the above formula the symbol error rate versus bitenergy (SNR per bit 119864
119887119873
0) for the system under test can
thus give as
119875
1199044QAM = erfc (radic119864
119887
119873
0
) (4)
Mean and standard deviation of measured power and119864
119888119873
0are obtained by considering measurements within a
local cluster For example the means and standard deviationsof power and119864
119888119873
0at location 31 in Figure 4 are formed from
the time average measurements at locations 27 through 31RMS delay spread is found according to
RMS delay spread = 119878 = [sum
119873
119896=1(119905
119896minus 119889)
2
119875 (119905
119896)
sum
119873
119896=1119875 (119905
119896)
]
12
(5)
where 119889 is the mean time delay 119905119896is the time delay (in
seconds) relative to the start of the power delay profile (PDP)119875 is the signal power (W) and 119873 is the index of the finalPDP signal point consideredVariability in rake finger activitysimply relates to how much the number of active fingerschanges over the measurement interval
3 The Simulator
The simulator based on the zero-wavelength approximationtreating waves as rays has been found to give reasonablepredictions of path loss and RMS delay spread for the indoorenvironments studied here General ray tracing in an indoorenvironment assumes that direct reflected refracted anddiffracted rays all carry some energy to the receiver althoughone or more of these may be negligible Note that each ray isconsidered to be a tube that opens up as the wave propagatesthis opening up represents energy spreading (the energy inthe tube is considered to be constant) Although after locat-ing a scattering point the reception test is performed basedon reception sphere concept this method is successfullyapplicable to complex environmentwhich requires enormouscomputing time and memoryThe reflected rays are assumedto emanate from the mirror image of the source onto the flatsection of wall ceiling or floor and the refracted ray is nearlyparallel to the incident ray with a slight path length deviationof Δ119889 where
Δ119889 =
119889 sin (120579119894minus 120579
119905)
cos 120579119905
(6)
119889 is the thickness of the wall ceiling or floor and 120579
119894 120579119905
are the angles of incidence and refraction respectively Thediffracted field that is due to illumination of outside cornersis calculated using the UniformTheory of Diffraction (UTD)
4 International Journal of Vehicular Technology
B2A first floor2-story stone construction composite roof and all measurements in feet2 times 55 5 times 55
2 times 51 5 times 51
8 times 12
0 times 19
0 times 38
0 times 16
0 times 0
2 times 0
1 2 3 4
567
8
9
1011
12
13
14
15
16
17
18 19
2021
Kitchen wisland
Entrance
Power (dB)
Living
Closet
Deck
Shed
Garage 2-car
Play room wpool table
N
BS
15998400
10998400
lt25lt35
lt45lt55
16 times 50
48 times 38
48 times 22
35 times 38
35 times 2230 times 22
30 times 21 35 times 21
26 times 1814 times 19
16 times 38
14 times 16
10 times 20
19 times 18
26 times 21
19 times 22
48 times 21
20 times 1228 times 13
48 times 046 times 038 times 025 times 0
23 times 013 times 012 times 0
28 times 822 times 8
22 times 13
25 times 16
35 times 50
(a)
9 times 380 times 38
8 times 10
8 times 12
9 times 28
9 times 20
0 times 0
33 times 4819 times 48
17 times 38 19 times 38 33 times 38 38 times 38 48 times 38
17 times 2015 times 20
11 times 20
11 times 2815 times 28 17 times 28
22 times 20
38 times 15
35 times 1328 times 13
22 times 13
35 times 15
38 times 27 48 times 27
48 times 15
28 times 8
35 times 0 48 times 0
22 times 8
17 times 0
15 times 10
B2A second floor2-story stone construction composite roof and all measurements in feetCPE at 3-feet above ground
2223
2425
26
27
28
29
30
31
lt35lt45lt55
Balcony
Masterbath
StudyMedia room Closed
Closed
ClosedMaster bedroom
Power (dB)
(b)
Figure 3 B2A Blue Print Model showing test positions and measured power for (a) first floor and (b) second floor
International Journal of Vehicular Technology 5
Single story brick construction composite roof and all measurements in feet
Bedroom
Master bedroom
Living
Garage 2 car
N
BS
123
Entrance
4 5 6
Playroom
Dining
Bedroomclosed
Breakfast
Kitchen
Bath
Patio
Den
Bedroom
Bath
OfficeStorage
Closet
Bath
Exercise room
78
9 10
11
1516
19
17 18
20 26
25
22 23
2421
43
4244
40
3938
37
413433
32 3536
29 30
2728
31
12
1314
0
0
Power (dB)lt15lt25
lt35lt45
10998400
15998400
43 times 26
43 times 31
35 times 26
35 times 31
39 times 3933 times 39
24 times 2928 times 29
28 times 3124 times 31
18 times 29
18 times 31
14 times 29
14 times 31
29 times 39 43 times 39
39 times 5
35 times 17
35 times 2139 times 21
39 times 1743 times 17
57 times 039 times 0
57 times 2143 times 21
43 times 34
43 times 43
57 times 3452 times 34
52 times 4349 times 43
49 times 47
57 times 51
57 times 4743 times 47
43 times 5129 times 51
29 times 41
29 times 28
29 times 19
29 times 522 times 511 times 5
11 times 14
22 times 1911 times 19
11 times 31
11 times 41
11 times 510 times 51
0 times 41
0 times 31
0 times 14
14 times 13 6 times 6
13 times 14
19 times 12
9 times 11
8 times 11
11 times 1411 times 14
19 times 14
13 times 15
14 times 11
B3A CPE at 1m height at all locations
Figure 4 Blue Print Model of residence B3A as tested (numbers indicate test positions and measured power)
The ray tracing-based simulator developed for this workis composed of two main parts The first part referred to asthe ray tracer defines the geometrical paths taken by the radiowave to reach the receiver The second part referred to as theelectromagnetic tracer ormodeler determines themagnitudeand phase of the signal along each path upon arrival at thereceiver That is it produces a file containing informationabout the complex impulse response of the radio channel thatis of the form [17]
ℎ (119905) =
119873
sum
119899=1
119860
119899120575 (119905 minus 120591
119899) exp (minus119895120599
119899) (7)
where there are 119873 time-delayed impulses (rays) each rep-resented by an attenuated and phase-shifted version of theoriginal transmitted impulse for which the amplitude is 119860
119899
the arrival time is 120591119899 and the phase is 120599
119899 Reflected and trans-
mitted rays are evaluated through use of geometrical opticswhile diffracted rays are calculated using geometrical theory
of diffraction [17] Accordingly the complex amplitude alongeach path is obtained as
119864
119894= 119864
119900119865
119905119894119865
119903119894Π
119895119877
119895Π
119896119879
119896Π
119905119860
119905(119904
1015840
119904)119863
119905
119890
minus119895119896119889
119889
(8)
where 119864119900represents the reference field 119865
119905119894and 119865
119903119894represent
the transmitting and receiving antenna field radiation pat-terns in the direction of the ray 119877
119895represents the reflection
coefficient for the 119895th reflection 119879119896represents the wall trans-
mission coefficient for the 119896th transmission 119863119905represents
the diffraction coefficient for the 119894th diffracting wedge andexp(minus119895119896119889) represents the propagation phase factor due tothe path length 119889
119905(119896 = 2120587120582) 119860
119905(119904
1015840
119904) provides the correctspatial attenuation for the diffracted rays
Both the simulator and the floor plan module used bythe simulator (the latter developed by [18]) are MATLABregbased The source file for the floor plan module includesthematerial characteristics (conductivity and permittivity) ofeach wall floor and ceiling section as well as the 119909 119910 119911 pointsof each corner for the configuration Material parameters
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
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Active and Passive Electronic Components
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RotatingMachinery
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Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
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Shock and Vibration
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Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
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Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
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Chemical EngineeringInternational Journal of Antennas and
Propagation
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Navigation and Observation
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DistributedSensor Networks
International Journal of
International Journal of Vehicular Technology 3
Table 1 Building information
Building ID DescriptionB2A Building 2A two-floor house stonevinyl construction composite roof and 2-car garageB3A Building 3A single floor house brick construction composite sloped roof and 2-car garage
sheet rock and composite sloped roofs Table 1 summarizeseach building construction
To form a file of fast-fading components each sample ofdata collected in a given environment was normalized by theaverage signal strength within that environment To controlthe pedestrian effects only a single person was in the vicinityof the test gear Collection of statistics was commenced afterone minute to compensate for electromagnetic effects causedby human presence These statistics could be correlated backto a dense urban mobile environment The local mean wasestimated by averaging the signal strength over 1000 samplesthat is the system is to collect 1 measurement at 100msintervals for 10000ms Figures 3 and 4 indicate normalizedreceive power levels measured for various locations insideand outside of the two residential test sites Although thesetests could have directly been conducted in a dense urbanvehicular settings the decision to show comparable results ina pedestrian suburban model was taken into considerationdue to logistics and personnel at hand
Parameters considered for evaluation are mean andstandard deviation of measured power mean and standarddeviation of 119864
119888119873
0 RMS delay spread and variability in
rake finger activity The primary RF design parameter forCDMA systems is the SNR or chip energy (119864
119888) of a specific
CDMA channel in relation to the noise (1198730) energy known
as the 119864
119888119873
0ratio The transmitter and receiver use an
119864
119904119873
0estimator to measure the ratio of symbol (119864
119904) to noise
(1198730) energy for a particular channel (eg BDCH) Spread
Factor (SF) is dynamically controlled within the receiverTherelationship between 119864
119888119873
0and 119864
119904119873
0is as follows
119864
119888
119873
0
(dB) = minus10 lowast log10(SF) +
119864
119904
119873
0
(1)
Codespace can be viewed as consisting of 512 units of band-width A SF = 512 channel uses 1 unit a SF = 256 channel uses2 units a SF = 128 channel uses 4 units and a SF = 4 channeluses 128 units More units effectively correspond to a higherbandwidth channel
The relation between bit energy119864119887119873
0and symbol energy
119864
119904119873
0is reasonably straightforward For 119872-PSK119872-QAM
modulation the number of bits in each constellation symbolis
119896 = log2119872 (2)
Since each symbol carries 119896 bits the symbol to noise ration119864
119904119873
0is 119896 times the bit to noise ratio 119864
119887119873
0 or
119864
119904
119873
0
=
119896119864
119887
119873
0
(3)
Using the above formula the symbol error rate versus bitenergy (SNR per bit 119864
119887119873
0) for the system under test can
thus give as
119875
1199044QAM = erfc (radic119864
119887
119873
0
) (4)
Mean and standard deviation of measured power and119864
119888119873
0are obtained by considering measurements within a
local cluster For example the means and standard deviationsof power and119864
119888119873
0at location 31 in Figure 4 are formed from
the time average measurements at locations 27 through 31RMS delay spread is found according to
RMS delay spread = 119878 = [sum
119873
119896=1(119905
119896minus 119889)
2
119875 (119905
119896)
sum
119873
119896=1119875 (119905
119896)
]
12
(5)
where 119889 is the mean time delay 119905119896is the time delay (in
seconds) relative to the start of the power delay profile (PDP)119875 is the signal power (W) and 119873 is the index of the finalPDP signal point consideredVariability in rake finger activitysimply relates to how much the number of active fingerschanges over the measurement interval
3 The Simulator
The simulator based on the zero-wavelength approximationtreating waves as rays has been found to give reasonablepredictions of path loss and RMS delay spread for the indoorenvironments studied here General ray tracing in an indoorenvironment assumes that direct reflected refracted anddiffracted rays all carry some energy to the receiver althoughone or more of these may be negligible Note that each ray isconsidered to be a tube that opens up as the wave propagatesthis opening up represents energy spreading (the energy inthe tube is considered to be constant) Although after locat-ing a scattering point the reception test is performed basedon reception sphere concept this method is successfullyapplicable to complex environmentwhich requires enormouscomputing time and memoryThe reflected rays are assumedto emanate from the mirror image of the source onto the flatsection of wall ceiling or floor and the refracted ray is nearlyparallel to the incident ray with a slight path length deviationof Δ119889 where
Δ119889 =
119889 sin (120579119894minus 120579
119905)
cos 120579119905
(6)
119889 is the thickness of the wall ceiling or floor and 120579
119894 120579119905
are the angles of incidence and refraction respectively Thediffracted field that is due to illumination of outside cornersis calculated using the UniformTheory of Diffraction (UTD)
4 International Journal of Vehicular Technology
B2A first floor2-story stone construction composite roof and all measurements in feet2 times 55 5 times 55
2 times 51 5 times 51
8 times 12
0 times 19
0 times 38
0 times 16
0 times 0
2 times 0
1 2 3 4
567
8
9
1011
12
13
14
15
16
17
18 19
2021
Kitchen wisland
Entrance
Power (dB)
Living
Closet
Deck
Shed
Garage 2-car
Play room wpool table
N
BS
15998400
10998400
lt25lt35
lt45lt55
16 times 50
48 times 38
48 times 22
35 times 38
35 times 2230 times 22
30 times 21 35 times 21
26 times 1814 times 19
16 times 38
14 times 16
10 times 20
19 times 18
26 times 21
19 times 22
48 times 21
20 times 1228 times 13
48 times 046 times 038 times 025 times 0
23 times 013 times 012 times 0
28 times 822 times 8
22 times 13
25 times 16
35 times 50
(a)
9 times 380 times 38
8 times 10
8 times 12
9 times 28
9 times 20
0 times 0
33 times 4819 times 48
17 times 38 19 times 38 33 times 38 38 times 38 48 times 38
17 times 2015 times 20
11 times 20
11 times 2815 times 28 17 times 28
22 times 20
38 times 15
35 times 1328 times 13
22 times 13
35 times 15
38 times 27 48 times 27
48 times 15
28 times 8
35 times 0 48 times 0
22 times 8
17 times 0
15 times 10
B2A second floor2-story stone construction composite roof and all measurements in feetCPE at 3-feet above ground
2223
2425
26
27
28
29
30
31
lt35lt45lt55
Balcony
Masterbath
StudyMedia room Closed
Closed
ClosedMaster bedroom
Power (dB)
(b)
Figure 3 B2A Blue Print Model showing test positions and measured power for (a) first floor and (b) second floor
International Journal of Vehicular Technology 5
Single story brick construction composite roof and all measurements in feet
Bedroom
Master bedroom
Living
Garage 2 car
N
BS
123
Entrance
4 5 6
Playroom
Dining
Bedroomclosed
Breakfast
Kitchen
Bath
Patio
Den
Bedroom
Bath
OfficeStorage
Closet
Bath
Exercise room
78
9 10
11
1516
19
17 18
20 26
25
22 23
2421
43
4244
40
3938
37
413433
32 3536
29 30
2728
31
12
1314
0
0
Power (dB)lt15lt25
lt35lt45
10998400
15998400
43 times 26
43 times 31
35 times 26
35 times 31
39 times 3933 times 39
24 times 2928 times 29
28 times 3124 times 31
18 times 29
18 times 31
14 times 29
14 times 31
29 times 39 43 times 39
39 times 5
35 times 17
35 times 2139 times 21
39 times 1743 times 17
57 times 039 times 0
57 times 2143 times 21
43 times 34
43 times 43
57 times 3452 times 34
52 times 4349 times 43
49 times 47
57 times 51
57 times 4743 times 47
43 times 5129 times 51
29 times 41
29 times 28
29 times 19
29 times 522 times 511 times 5
11 times 14
22 times 1911 times 19
11 times 31
11 times 41
11 times 510 times 51
0 times 41
0 times 31
0 times 14
14 times 13 6 times 6
13 times 14
19 times 12
9 times 11
8 times 11
11 times 1411 times 14
19 times 14
13 times 15
14 times 11
B3A CPE at 1m height at all locations
Figure 4 Blue Print Model of residence B3A as tested (numbers indicate test positions and measured power)
The ray tracing-based simulator developed for this workis composed of two main parts The first part referred to asthe ray tracer defines the geometrical paths taken by the radiowave to reach the receiver The second part referred to as theelectromagnetic tracer ormodeler determines themagnitudeand phase of the signal along each path upon arrival at thereceiver That is it produces a file containing informationabout the complex impulse response of the radio channel thatis of the form [17]
ℎ (119905) =
119873
sum
119899=1
119860
119899120575 (119905 minus 120591
119899) exp (minus119895120599
119899) (7)
where there are 119873 time-delayed impulses (rays) each rep-resented by an attenuated and phase-shifted version of theoriginal transmitted impulse for which the amplitude is 119860
119899
the arrival time is 120591119899 and the phase is 120599
119899 Reflected and trans-
mitted rays are evaluated through use of geometrical opticswhile diffracted rays are calculated using geometrical theory
of diffraction [17] Accordingly the complex amplitude alongeach path is obtained as
119864
119894= 119864
119900119865
119905119894119865
119903119894Π
119895119877
119895Π
119896119879
119896Π
119905119860
119905(119904
1015840
119904)119863
119905
119890
minus119895119896119889
119889
(8)
where 119864119900represents the reference field 119865
119905119894and 119865
119903119894represent
the transmitting and receiving antenna field radiation pat-terns in the direction of the ray 119877
119895represents the reflection
coefficient for the 119895th reflection 119879119896represents the wall trans-
mission coefficient for the 119896th transmission 119863119905represents
the diffraction coefficient for the 119894th diffracting wedge andexp(minus119895119896119889) represents the propagation phase factor due tothe path length 119889
119905(119896 = 2120587120582) 119860
119905(119904
1015840
119904) provides the correctspatial attenuation for the diffracted rays
Both the simulator and the floor plan module used bythe simulator (the latter developed by [18]) are MATLABregbased The source file for the floor plan module includesthematerial characteristics (conductivity and permittivity) ofeach wall floor and ceiling section as well as the 119909 119910 119911 pointsof each corner for the configuration Material parameters
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
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Active and Passive Electronic Components
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RotatingMachinery
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Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
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Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
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Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
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Chemical EngineeringInternational Journal of Antennas and
Propagation
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Navigation and Observation
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DistributedSensor Networks
International Journal of
4 International Journal of Vehicular Technology
B2A first floor2-story stone construction composite roof and all measurements in feet2 times 55 5 times 55
2 times 51 5 times 51
8 times 12
0 times 19
0 times 38
0 times 16
0 times 0
2 times 0
1 2 3 4
567
8
9
1011
12
13
14
15
16
17
18 19
2021
Kitchen wisland
Entrance
Power (dB)
Living
Closet
Deck
Shed
Garage 2-car
Play room wpool table
N
BS
15998400
10998400
lt25lt35
lt45lt55
16 times 50
48 times 38
48 times 22
35 times 38
35 times 2230 times 22
30 times 21 35 times 21
26 times 1814 times 19
16 times 38
14 times 16
10 times 20
19 times 18
26 times 21
19 times 22
48 times 21
20 times 1228 times 13
48 times 046 times 038 times 025 times 0
23 times 013 times 012 times 0
28 times 822 times 8
22 times 13
25 times 16
35 times 50
(a)
9 times 380 times 38
8 times 10
8 times 12
9 times 28
9 times 20
0 times 0
33 times 4819 times 48
17 times 38 19 times 38 33 times 38 38 times 38 48 times 38
17 times 2015 times 20
11 times 20
11 times 2815 times 28 17 times 28
22 times 20
38 times 15
35 times 1328 times 13
22 times 13
35 times 15
38 times 27 48 times 27
48 times 15
28 times 8
35 times 0 48 times 0
22 times 8
17 times 0
15 times 10
B2A second floor2-story stone construction composite roof and all measurements in feetCPE at 3-feet above ground
2223
2425
26
27
28
29
30
31
lt35lt45lt55
Balcony
Masterbath
StudyMedia room Closed
Closed
ClosedMaster bedroom
Power (dB)
(b)
Figure 3 B2A Blue Print Model showing test positions and measured power for (a) first floor and (b) second floor
International Journal of Vehicular Technology 5
Single story brick construction composite roof and all measurements in feet
Bedroom
Master bedroom
Living
Garage 2 car
N
BS
123
Entrance
4 5 6
Playroom
Dining
Bedroomclosed
Breakfast
Kitchen
Bath
Patio
Den
Bedroom
Bath
OfficeStorage
Closet
Bath
Exercise room
78
9 10
11
1516
19
17 18
20 26
25
22 23
2421
43
4244
40
3938
37
413433
32 3536
29 30
2728
31
12
1314
0
0
Power (dB)lt15lt25
lt35lt45
10998400
15998400
43 times 26
43 times 31
35 times 26
35 times 31
39 times 3933 times 39
24 times 2928 times 29
28 times 3124 times 31
18 times 29
18 times 31
14 times 29
14 times 31
29 times 39 43 times 39
39 times 5
35 times 17
35 times 2139 times 21
39 times 1743 times 17
57 times 039 times 0
57 times 2143 times 21
43 times 34
43 times 43
57 times 3452 times 34
52 times 4349 times 43
49 times 47
57 times 51
57 times 4743 times 47
43 times 5129 times 51
29 times 41
29 times 28
29 times 19
29 times 522 times 511 times 5
11 times 14
22 times 1911 times 19
11 times 31
11 times 41
11 times 510 times 51
0 times 41
0 times 31
0 times 14
14 times 13 6 times 6
13 times 14
19 times 12
9 times 11
8 times 11
11 times 1411 times 14
19 times 14
13 times 15
14 times 11
B3A CPE at 1m height at all locations
Figure 4 Blue Print Model of residence B3A as tested (numbers indicate test positions and measured power)
The ray tracing-based simulator developed for this workis composed of two main parts The first part referred to asthe ray tracer defines the geometrical paths taken by the radiowave to reach the receiver The second part referred to as theelectromagnetic tracer ormodeler determines themagnitudeand phase of the signal along each path upon arrival at thereceiver That is it produces a file containing informationabout the complex impulse response of the radio channel thatis of the form [17]
ℎ (119905) =
119873
sum
119899=1
119860
119899120575 (119905 minus 120591
119899) exp (minus119895120599
119899) (7)
where there are 119873 time-delayed impulses (rays) each rep-resented by an attenuated and phase-shifted version of theoriginal transmitted impulse for which the amplitude is 119860
119899
the arrival time is 120591119899 and the phase is 120599
119899 Reflected and trans-
mitted rays are evaluated through use of geometrical opticswhile diffracted rays are calculated using geometrical theory
of diffraction [17] Accordingly the complex amplitude alongeach path is obtained as
119864
119894= 119864
119900119865
119905119894119865
119903119894Π
119895119877
119895Π
119896119879
119896Π
119905119860
119905(119904
1015840
119904)119863
119905
119890
minus119895119896119889
119889
(8)
where 119864119900represents the reference field 119865
119905119894and 119865
119903119894represent
the transmitting and receiving antenna field radiation pat-terns in the direction of the ray 119877
119895represents the reflection
coefficient for the 119895th reflection 119879119896represents the wall trans-
mission coefficient for the 119896th transmission 119863119905represents
the diffraction coefficient for the 119894th diffracting wedge andexp(minus119895119896119889) represents the propagation phase factor due tothe path length 119889
119905(119896 = 2120587120582) 119860
119905(119904
1015840
119904) provides the correctspatial attenuation for the diffracted rays
Both the simulator and the floor plan module used bythe simulator (the latter developed by [18]) are MATLABregbased The source file for the floor plan module includesthematerial characteristics (conductivity and permittivity) ofeach wall floor and ceiling section as well as the 119909 119910 119911 pointsof each corner for the configuration Material parameters
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
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Active and Passive Electronic Components
Control Scienceand Engineering
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RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
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Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Vehicular Technology 5
Single story brick construction composite roof and all measurements in feet
Bedroom
Master bedroom
Living
Garage 2 car
N
BS
123
Entrance
4 5 6
Playroom
Dining
Bedroomclosed
Breakfast
Kitchen
Bath
Patio
Den
Bedroom
Bath
OfficeStorage
Closet
Bath
Exercise room
78
9 10
11
1516
19
17 18
20 26
25
22 23
2421
43
4244
40
3938
37
413433
32 3536
29 30
2728
31
12
1314
0
0
Power (dB)lt15lt25
lt35lt45
10998400
15998400
43 times 26
43 times 31
35 times 26
35 times 31
39 times 3933 times 39
24 times 2928 times 29
28 times 3124 times 31
18 times 29
18 times 31
14 times 29
14 times 31
29 times 39 43 times 39
39 times 5
35 times 17
35 times 2139 times 21
39 times 1743 times 17
57 times 039 times 0
57 times 2143 times 21
43 times 34
43 times 43
57 times 3452 times 34
52 times 4349 times 43
49 times 47
57 times 51
57 times 4743 times 47
43 times 5129 times 51
29 times 41
29 times 28
29 times 19
29 times 522 times 511 times 5
11 times 14
22 times 1911 times 19
11 times 31
11 times 41
11 times 510 times 51
0 times 41
0 times 31
0 times 14
14 times 13 6 times 6
13 times 14
19 times 12
9 times 11
8 times 11
11 times 1411 times 14
19 times 14
13 times 15
14 times 11
B3A CPE at 1m height at all locations
Figure 4 Blue Print Model of residence B3A as tested (numbers indicate test positions and measured power)
The ray tracing-based simulator developed for this workis composed of two main parts The first part referred to asthe ray tracer defines the geometrical paths taken by the radiowave to reach the receiver The second part referred to as theelectromagnetic tracer ormodeler determines themagnitudeand phase of the signal along each path upon arrival at thereceiver That is it produces a file containing informationabout the complex impulse response of the radio channel thatis of the form [17]
ℎ (119905) =
119873
sum
119899=1
119860
119899120575 (119905 minus 120591
119899) exp (minus119895120599
119899) (7)
where there are 119873 time-delayed impulses (rays) each rep-resented by an attenuated and phase-shifted version of theoriginal transmitted impulse for which the amplitude is 119860
119899
the arrival time is 120591119899 and the phase is 120599
119899 Reflected and trans-
mitted rays are evaluated through use of geometrical opticswhile diffracted rays are calculated using geometrical theory
of diffraction [17] Accordingly the complex amplitude alongeach path is obtained as
119864
119894= 119864
119900119865
119905119894119865
119903119894Π
119895119877
119895Π
119896119879
119896Π
119905119860
119905(119904
1015840
119904)119863
119905
119890
minus119895119896119889
119889
(8)
where 119864119900represents the reference field 119865
119905119894and 119865
119903119894represent
the transmitting and receiving antenna field radiation pat-terns in the direction of the ray 119877
119895represents the reflection
coefficient for the 119895th reflection 119879119896represents the wall trans-
mission coefficient for the 119896th transmission 119863119905represents
the diffraction coefficient for the 119894th diffracting wedge andexp(minus119895119896119889) represents the propagation phase factor due tothe path length 119889
119905(119896 = 2120587120582) 119860
119905(119904
1015840
119904) provides the correctspatial attenuation for the diffracted rays
Both the simulator and the floor plan module used bythe simulator (the latter developed by [18]) are MATLABregbased The source file for the floor plan module includesthematerial characteristics (conductivity and permittivity) ofeach wall floor and ceiling section as well as the 119909 119910 119911 pointsof each corner for the configuration Material parameters
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
6 International Journal of Vehicular Technology
Top view (x-y)
14
12
10
8
6
4
2
0
minus4 minus2 0 2 4 6 8 10 12 14 16x (m)
y (m
)
(a)Po
wer
(dB)
Time delay (ns)
Ray tracing power delay profile
MeasuredPredicted
0 10 5020 30 40 60 70
35
30
25
20
15
10
5
0
(b)
Figure 5 (a) Two-dimensional top view of location 8 of building B2A showing all contributing rays (b) Power delay profile for location 8building B2A
Table 2 Permittivity and conductivity at 2600MHz [22 23]
Location Conductivity(Sm)
Permittivityrelative
Ceiling (composite pluswood and plaster) 0005 3
Floor (concrete) 000022 7Internal walls (plaster typeof concrete) 0005 3
External walls (brick) 0005 3Windows 100E minus 05 6Metallic object 100 3
used for simulations are shown in Table 2 Figure 5(a) showsa sample location and contributing rays as determined by thesimulator and Figure 5(b) indicates the resulting power delayprofile for that sample location
4 Results
Most of the discussion concerns measured and predictedpower levels and rake finger activity as these can be readilyexplained in terms of features of the indoor environment Itis noticed though that predicted and measured RMS delayspread values matched to within 10 ns for the majority oflocations serving as a validation for the simulator
From Figures 3 and 4 a consistent finding is that signalstrengths at room centers are at least 10ndash12 dB higher thanfor the corresponding corner locations This of course isonly for cases where scattering diffraction and shadowingfrom objects such as cabinets and appliances do not stronglyinfluence the signal strength This result is expected and
largely due to the narrow angular range of rays that contributeto the signal in the corner locations (as opposed to thecenter location) The results are similar to those realized by[5 19] where 15ndash20 dB variations between corner and centerlocations were observed
Figures 3 and 4 also show substantial variation of signalstrength among the corners of a room For the sites tested inthis work thewave direction (from the base station) is directlyonto one corner of each of the buildings As a result a majorcomponent of energy travel is defined by a ray from corner tocorner within each room A general finding here is that themeasured power is most often higher (by several dB) at thefar corner of the room that is farthest from the base stationprovided that the rooms are interior rooms that there are noexterior walls of the room that are illuminated by the basestation and that there are no strong scattering diffractionand shadowing effects from objects such as cabinets andappliances that may modify the pattern This apparently isdue to a strong corner reflector effect involving rays withlower number of reflections
Evidence of tunneling (waveguiding) similar to Seideland Rappaport [20] shadowing and diffraction are clearin both of Figures 3 and 4 For example in Figure 3 themeasured signal strength at location 13 is several dB lowerthan expected due to shadowing and tunneling effects (in theshort hallway-like area) and the measured signal strengths atlocations 15 and 16 appear to be due to shadowing from thedeck Similarly in Figure 4 the measured signal strengths atlocations 21 and 24 are several dB higher than expected dueto diffraction and tunneling effects involving the two pillarswhereas the signal strength at location 25 is several dB lowerthan expected due to tunneling and shadowing effects in-between the two pillars
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Vehicular Technology 7
Table 3 Summary of effects on signal strength (notice that the cor-responding maxima and minima are identified with labeled arrowson the measurement curves in Figures 6 and 7)
Location (arrow on measurementcurve)noted feature(s) Mechanism(s)
B2A 26(G)B3A 11(B) 19(D) and 36(J) Room center
B2A 8(A) 24(F)B3A 8(A) 12(B) 16(C) 28(G) and 32(I) Room (far) corner
B3A 21(E)pillars 24(F)pillars TunnelingB2A 11(B)kitchen TunnelingscatteringB3A 25(P)pillars TunnelingshadowingB2A 14(C)deckshed 15(J)deckkitchenand 29(K)balcony Scattering
B3A 30(H)bathroom 39(K)bathroom ScatteringdiffractionB2A 17(D) 22(E)B3A 43(L)
Exterior wall exposedto base station
B3A 20(O)pillars ShadowingB3A 14(N)pillars ShadowingtunnelingB2A 9(H)kitchen 12(I)deck and13(I)hallway-like areaB3A 9(M)kitchen
Shadowingscattering
Effects of scattering and shadowing due to items in thekitchen (cabinets and large appliances) and bathroom (cab-inets and bathroom fixtures) are noticeable in the measure-ments For example in Figure 3 measurements at locations9 and 11 are several dB lower than expected apparently as aresult of scattering and shadowing due to the kitchen itemsIn Figure 4 signal strength at location 9 seems to be sub-stantially influenced (lowered) by shadowing and scatteringeffects from kitchen items whereas signal strength at loca-tions 14 and 22 are substantially lower than expected appar-ently due to scattering and shadowing of bathroom items
A summary of the mechanisms thought to be responsiblefor maximum and minimum signal strengths in the mea-surements is provided in Table 3 Notice that the table refersto Figures 3 and 4 which show measurement locations andFigures 6 and 7 which showmeasured power versus locationAlso shown in Figures 6 and 7 are predictions provided by theray tracing simulator Also note that the predicted trends aresimilar to those measured however the measurements showconsiderably wider variations This appears to be a result ofscattering from neighboring residences as well as scatteringfrom terrain and foliage all of which are not considered by thesimulator Also no knowledge about the wall composition ofneighboring buildings is available These factors can explainthe disagreement between measured and simulated PDPsfor large delays Nevertheless the delay spread and averagedelay showgood agreement betweenmeasured and simulatedpower delays One reason is due to the similarities at shortdelays in both plots which are of utmost importance Forthe longer delays define longer delay parameters which arenot in good agreement with simulated versus measured Alllocation results are shown in order to compare adequately themodel versus measured power delay profiles Of particular
00
100
200
300
400
500
600
700
0 10 20 30 40
Pow
er (d
B)
Location
Power building B2A
MeasuredPredicted
GFEDCBA
KJIH
Figure 6 Power profile for building B2A
Power building B3A
MeasuredPredicted
F G IHJ
K LA B C D E
MN O P
05
101520253035404550
Pow
er (d
B)
10 20 30 40 500Location
Figure 7 Power profile for building B3A
note are the higher measured values on the second floor ofB2A compared to those on the first floor (as expected) andthe closer agreement of the simulator predictions to meas-urements for the second floor of B2A
A simple classification scheme was developed to deter-mine the predominant mechanism for signal strength aspredicted by the simulator at each of the locations inbuildings B2A and B3A Classifications are specular surfacescattering including corner reflector effects edge diffrac-tion and tunneling The corner reflector effect is when asignal pulse bounces twice Once it bounces on a verticalsurface facing the receiver and then rebounces a second timefrom a horizontal surface towards the targeted receiver Thepredominant mechanism is designated as tunneling if the
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
8 International Journal of Vehicular Technology
Table 4 Measured rake activity according to building and location
Buildinglocation Approximate number of times active rakefingers changedsecond
B3A41 5B3A10 10B3A17 2B3A24 1B2A18 3B2A10 7B2A13 25B2A29 4
majority of signal strength can be accounted for by reflectedrays forming an interference pattern similar to that observedin a waveguide over at least a few wavelengths includingthe location of interest [20] The mechanism is designatedas edge diffraction if the majority of signal strength at aparticular location can be accounted for by rays emanating atangles within Kellerrsquos cone from diffracting edges The thirdcategory that is specular surface scattering is assumed to bethe predominant mechanism for other locations Accordingto this classification scheme for building B3A signal strengthat 71 of the locations was found to be primarily a result ofspecular scattering edge diffraction at 14 of the locationsand tunneling at 14 of the locations Similarly for buildingB2A signal strength at 75 of the locations was found to beprimarily a result of specular scattering edge diffraction at13 of the locations and tunneling at 125 of the locations
41 Rake Fingers Activity as a Multipath Source IndicatorHaving many rake fingers active implies that many propaga-tion paths are present However given the system chip ratethe paths are not resolvable unless they differ by at least about80m in length Although spatial resolution is within 1ndash3mcomparative analysis when compared to ray tracing resultsindoor arewithin 8 dBwith rake finger activity ranging from 1to 10 see Table 4This implies that the resolvable propagationpaths are normally a result of multipath propagation outsideof a typical residence that is due to the limited buildingdimensions Nonetheless the rake finger activity or variationappears to be impacted by characteristics of the indoorchannel A study was done of the channel behavior usingmeasurements at locations described in Figures 3 and 4 andseveral of these results are shown in Table 4 The resultsalthough with a small sample size indicate that rake activityis lower the closer the location is to an exterior wall that facesthe transmitter and lower when the location is close to butnot in the shadow of strong scatterers such as pillars cabinetscounters and large appliances On the other hand the level ofrake activity tends to increase substantially when the locationis in the shadowof large objects In general it is assumed that ifthe number of rake fingers varies by more than a single fingermore than 3 or 4 times over the measurement time of 10 sthen it is considered to represent fades due to remote scatter-ers and not a ldquorake stabilizingrdquo effect of direct paths or nearbyobjects such as wall corner reflections and edge diffractions
strong scattering and diffraction from cabinets countersand appliances This technique is purely based on a stand-alone receiver compared to channel sounding which takesinto account feedback information from the transmitter witha defined channel sounding spread with a weighted wave-form to the subscriber station or receiver
5 Conclusions
Given knowledge of the base station location relative to aparticular residence in a typical suburban area the ldquostrongestsignalrdquo and ldquoweakest or most variable signalrdquo locations canbe predicted based on knowledge of the residence floor planand locations of major scatterers such as large appliances andcabinetry For example room center and far corner locationswere found to have the highest signal strengths howeverhallway-like areas and locations near strongly diffractingobjects were also found to often have higher than expectedsignal strengths Although the simulator does not considerfoliage and colocated building the power delay results showedcomparable location specific variations when compared tothe measured Relative differences between strongest andweakest signal levels can also be estimated for the tworesidences considered in this work this difference was foundto be as high as 50 dB Typical building characteristics canbe drawn and concluded dependent on area morphologywith a relatively higher sample of similar buildings and fur-niture adaptations within a microscale environment Witha straightforward extension of the proposed propagationmechanism classification scheme a microscale propagationmodel can be developed for predicting coverage within anindoor environment This prediction tool can also be usedin a small cell dense urban environment for amobile environ-ment given the predefinedmorphological conditions Similarhybrid environment considerations were given in previousresearch see Chia [7] and Wertz et al [21] The correlationbetween in-building and mobile environment is predictedusing ray tracing and measured in a similar environmentwith identical results [21] As shown the indoor propagationmodel allows the vector-oriented definition of an arbitrarynumber of objects with different materials a vehicle or build-ing can be modeled accurately Furthermore for the indooror vehicle objects a smaller discretization model is used foran urban scenario This same discretization was consideredin this paper With a provision of slight transition require-ment between suburban indoor versus dense mobile urbanconditions
Rake finger activity can be used to verify or provideadditional information about important indoor propagationeffects For example at locations exposed to exterior wallsoriented toward the base station and for locations near butnot in the shadow of large scatterers rake finger activity tendsto be minimum whereas rake activity tends to increase atlocations well inside and away from large scatterers and is thehighest where the location is in the shadow of large scatterers
In our study for the first floor of both residences themeasured signal strengths showed much higher variabilitythan the predicted signal strengths that is 50 dB versus20 dB On the other hand for the 2nd floor of the 2-floor
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of Vehicular Technology 9
20 40 60 80 100 120 140 160 180 200 220
x (m)
3-dimensional view
01020304050607080
z (m
)
250
y (m)
200150
10050
Figure 8 Vehicle configured in a dense urban clutter with raytracing and power delay profile
residence the prediction trend much more closely followedthe measurement trend although still with somewhat lowervariability apparently due to indoor furnishings The inac-curacy of the building database and the lack of informationabout the material characteristics may cause the discrepan-cies founded between simulations and measured results
Future studies to be released after receiving authorizationfrom all parties will show similar test and measurements fora dense urban environment Using the same ray tracing tooland subsequent measurements with a vehicle driven througha congested dense building clutter will be presented as shownin Figure 8
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgment
The authors would like to thank Dr Jacques Beneat NorwichUniversity for the MATLAB subroutine to generate 3Dbuildings with unique material characteristics
References
[1] E H Walker ldquoPenetration of radio signals into buildings in thecellular radio environmentrdquo The Bell System Technical Journalvol 62 no 9 pp 2719ndash2734 1983
[2] A J Motley and J M P Keenan ldquoPersonal communicationradio coverage in buildings at 900MHz and 1700MHzrdquo Elec-tronics Letters vol 24 no 12 pp 763ndash764 1988
[3] F Lotse J E Berg and R Bownds ldquoIndoor propagation meas-urements at 900MHzrdquo in Proceedings of the 42nd IEEE Vehic-ular Technology Conference pp 629ndash632 Denver Colo USAMay 1992
[4] A F De Toledo A M D Turkmani and J Parsons ldquoEstimatingcoverage of radio transmission into andwithin buildings at 9001800 and 2300MHzrdquo IEEE Personal Communications vol 5no 2 pp 40ndash47 1998
[5] A F de Toledo Narrowband Characterization of radio trans-missions into and within buildings at 900 1800 and 2300MHz [PhD thesis] Department of Electrical Engineering andElectronics University of Liverpool Liverpool UK 1992
[6] D I Axiotis andM ETheologou ldquoAn empirical model for pre-dicting building penetration loss at 2GHz for high elevationanglesrdquo IEEE Antennas and Wireless Propagation Letters vol 2pp 234ndash237 2003
[7] S T S Chia ldquo1700MHz urban microcells and their coverageinto buildingsrdquo in Proceedings of the 7th International Confer-ence on Antennas and Propagation (ICAP rsquo91) pp 504ndash507York USA April 1991
[8] C Oestges and A J Paulraj ldquoPropagation into buildings forbroad-band wireless accessrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 521ndash526 2004
[9] D Pena R Feick H D Hristov and W Grote ldquoMeasurementand modeling of propagation losses in brick and concrete wallsfor the 900-MHz bandrdquo IEEE Transactions on Antennas andPropagation vol 51 no 1 pp 31ndash39 2003
[10] Y L C de JongM H A J Herben J-FWagen and AMawiraldquoTransmission of UHF radiowaves through buildings in urbanmicrocell environmentsrdquo Electronics Letters vol 35 no 9 pp743ndash745 1999
[11] Y L C de Jong M H J L Koelen and M H A J HerbenldquoA building-transmissionmodel for improved propagation pre-diction in urban microcellsrdquo IEEE Transactions on VehicularTechnology vol 53 no 2 pp 490ndash502 2004
[12] G Durgin T S Rappaport and H Xu ldquo585-GHz radio pathloss and penetration loss measurements in and around homesand treesrdquo IEEECommunications Letters vol 2 no 3 pp 70ndash721998
[13] D M J Devasirvatham R R Murray and D R Wolter ldquoTimedelay spread measurements in a wireless local loop test bedrdquo inProceedings of the IEEE 45th Vehicular Technology Conferencepp 241ndash245 July 1995
[14] I Z Kovacs P C F Eggers and K Olesen ldquoComparison ofmean effective gains of different DCS 1800 handset antennasin urban and suburban environmentsrdquo in Proceedings of the48th IEEE Vehicular Technology Conference (VTC rsquo98) vol 3pp 1974ndash1978 IEEE Ottawa Canada May 1998
[15] C D Taylor S J Gutierrez S L Langdon and K L MurphyldquoOn the propagation of RF into a building constructed of cinderblock over the frequency range 200MHz to 3GHzrdquo IEEETrans-actions on Electromagnetic Compatibility vol 41 no 1 pp 46ndash49 1999
[16] V Erceg K V S Hari M S Smith et al ldquoChannel modelsfor fixed wireless applicationsrdquo Contribution IEEE 802163c-0129r1 2001
[17] J B Keller ldquoGeometrical theory of diffractionrdquo Journal of theOptical Society of America vol 52 pp 116ndash130 1962
[18] N Bailey andNDeslandes Senior Project ReportmdashSecureWire-less Communication Deployment Tool Norwich University2003 Director J Beneat
[19] G E Athanasiadou and A R Nix ldquoA novel 3-d indoor ray-tracing propagation model the path generator and evaluationof narrow-band and wide-band predictionsrdquo IEEE Transactionson Vehicular Technology vol 49 no 4 pp 1152ndash1168 2000
[20] S Y Seidel and T S Rappaport ldquoSite-specific propagationprediction for wireless in-building personal communicationsystem designrdquo IEEE Transactions on Vehicular Technology vol43 no 4 pp 879ndash891 1994
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
10 International Journal of Vehicular Technology
[21] P Wertz D Zimmermann F M Landstorfer G Wolfle andR Hoppe ldquoHybrid ray optical models for the penetration ofradio waves into enclosed spacesrdquo in Proceedings of the IEEE58th Vehicular Technology Conference (VTC rsquo03) vol 1 pp 109ndash113 IEEE October 2003
[22] A R Von Hippel Dielectric Materials and Applications JohnWiley amp Sons New York NY USA 1954
[23] American Institute of Physics Handbook McGraw-Hill NewYork NY USA 3rd edition 1972
International Journal of
AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
RoboticsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Active and Passive Electronic Components
Control Scienceand Engineering
Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
International Journal of
RotatingMachinery
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporation httpwwwhindawicom
Journal ofEngineeringVolume 2014
Submit your manuscripts athttpwwwhindawicom
VLSI Design
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Shock and Vibration
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Civil EngineeringAdvances in
Acoustics and VibrationAdvances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Electrical and Computer Engineering
Journal of
Advances inOptoElectronics
Hindawi Publishing Corporation httpwwwhindawicom
Volume 2014
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
SensorsJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Chemical EngineeringInternational Journal of Antennas and
Propagation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Navigation and Observation
International Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
DistributedSensor Networks
International Journal of
International Journal of
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