Cw Test Final

11

IntroductionIntroduction

• Operationalized in September 2007, with its Head Office in Mumbai.

• Comprises of a resource pool of 350+ Engineers who have worked with all Tier 1 OEMs across India. They bring rich experience by working in companies such as WIPRO, Reliance Communications, Tata Tele Services, Micro Technologies.

• Management comprises of members having over 10 years of experience in providing solutions over the wireless network.

• Dedicated to achieve best in Software Development and getting you

the most of innovative developed software’s.

Netwing Technologies Private Ltd.Netwing Technologies Private Ltd.

NETWING TECHNOLOGIES Pvt. Ltd.NETWING TECHNOLOGIES Pvt. Ltd.W W W . W A T S O N W Y A T T . C O M

A Telecom & IT Companywww.netwing.in

Equipment DetailsEquipment Details

Frequency used 

2300 - 2400 MHz NETWING Tool Discription  

Activity type   reference

Transmission

RF SynthesizerTortoise Multi-Band Transmitter (CW)

2.3 GHz, 2.5/25/50/200 kHz step 20 watt

Power Amplifier Tortoise 20 watt

RF Cables set 1/2" 5-10 mtr

Power meter Yellow Frog Coyat 150 Mhz -2.7 ghz for rms & CW both

Omni antenna Jaybeam Wireless 7640240

Telescopic mast Various 5 to 7meters with safety guides

Reception

Analog Receiver Coyote modular receiver w/GPSRx1: 2.3-2.4 GHz receiver module (25 kHz

steps/25 kHz IF BW)

Magnetic antenna Mount Antenna UMB

Set of accessories Coyote  

GPS    

Wheel trigger Rotary (Same Work) Coyat

PC laptop various  

Netwing Technologies Private Ltd.Netwing Technologies Private Ltd. 22

Equipment DetailsEquipment Details

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Activity type   reference

Survey

Digital camera Canon / Sony with Zoom equiv 35mm above 105

Professional Compass Topochaix Universal

GPS handset Trimble / Garmin… various references

Decameter various

Binocular Olympus

Complements

Antenna line tester Anritsu site master

Spectrum analyzer Anritsu MS2721 or equiv.

digital multimeter Flex to test Volt, Amp, ohm

Tool box with divers wrench

Site SelectionSite Selection

The major criteria with which sites were selected for CW testing is:

•The representation of clutters in the sites surroundings meeting the pretext of model for which it is being driven.•Any major obstacles which can badly affect the collection of data.•For the feasibility of installing antenna and safe upkeep of the CW equipments near to the antenna.•Adequacy of driving in the surroundings of the selected sites.•Ability to find cleaner frequency channel for data collection.•Existence of regular power supply for avoiding battery to discharge in case where the drive tests may prolong more than 3 hours.

Site SelectionSite Selection

•The planning area should be categorized into dense urban, mean urban, suburb and rural.•The testing site shall be free of visible obstructions around. the building where the testing site is located on shall be higher• than the average height of surrounding buildings.• In dense urban, the valid antenna height should be about 10m higher than the average height of surrounding buildings; In mean urban, it’s about 15m; in suburban or rural, it’s about 15 to 25m.•There should be enough clutters (from the digital map) around the site, and enough roads to be able to cover those clutters.•The building’s rooftop should not be too large. The antenna must be raised when the building’s rooftop is too large to affect the radio propagation, especially when there is a parapet on rooftop.•The omni antenna is set on top of the building or tower, and the valid antenna height, above ground level (from the ground to the middle of antenna), is 4 to 30m.

CW MethodologyCW Methodology

Measurements Procedures For CW Survey• CW test routes were planned carefully to avoid re running

on the routes where ever it was possible and also following sections were not included in the data collection by using the pause facility of the equipment.

1) Elevated sections of roads. 2) Tunnels.

3) Bridges.• Sufficient measurements were made in each clutter type

for the model to be reasonably accurate and thus valid.

CW MethodologyCW Methodology

Precautions Taken :• Measurement tape was used to verify the accurate

height.• Position of the site was recorded carefully with the

help of GPS.• Mostly antenna heights were selected considering

the average height of the clutter.• The power meter is used for checking the output

power after the feeder. It is important to check the forward power as well as the reflected in the antenna connection to be able to calculate the EiRP.

CW Drive Route DefinitionCW Drive Route Definition

• Distance : Must account for expected coverage propagation. Must account for expected interference propagation

• Clutter : Sufficient measurement in all local clutter types ( >1000 )

• Roads : Avoid street canyons, tunnels, elevated roads, cuttings etc..Mix of radial and tangential road roads with ground height above the transmitter antenna.

CW Drive Route DefinitionCW Drive Route Definition

•All directions from the testing site should be included.• Different distances should be reached;• All the clutters in coverage area must be tested.• Roads should be reached as much as possible.• Common and narrow roads are the main targets to be chosen. •Avoid of Drive test in the same route. • Don’t record the data when the car stops.•The testing radius should be large enough so that the received signal’s strength could be weaker than -110dBm;adjust the testing route according to the received signal in the practical drive test.

CW Equipment Set upCW Equipment Set up

Transmitter setupTransmitter setup

Tortoise Transmitter

To PowerSupply12V DC@5A

Power Meter

Antenna

CW Equipment Set upCW Equipment Set up

Receiver setupReceiver setup

Antenna

Coyote :The signal received from the Omni-directional antenna (no gain) is fed to the receiver and is again fed to the laptop PC through the parallel port extender. Output of the GPS is also fed to the laptop with the same cable. The transmitted test frequency is monitored using a laptop connected to the receiver. The data is processed using the Forecaster software

Data Post processingData Post processing

Depends on customer requirements:

• Averaged Measurements – post processing involves simple conversion into Signia format supported by Enterprise

• Signia data file ( .dat ) contains longitude, latitude (decimal degrees) and received level (dBm)

• Every data file must have header file with identical name but with extension .hd.

• Header file must have antenna type (identical name to one in Asset3g), Tx power, Tx antenna height, coordinates.

• It is common practice to include all gains and losses under Tx power value and leave other fields relevant to gain/losses in the header blank. Therefore in a Tx field usually is put:

• Tx – Ct +Atg –Arg+Crl where

• Tx-Tx power(dBm),

• Ct-cable loss between transmitter and antenna (dB),

• Atg-transmitting antenna gain (dBi)

• Arg-receiving antenna gain (dBi)

• Crl-cable loss between receiver and receiving antenna (dB)

CW Data ValidationCW Data Validation

• Compare the site data (photographs, surrounding clutter and terrain profile) to the Clutter and DTM layer of the map data provided.

• Check the driven routes against vectors within the map data.

• Filter out any invalid data that may cause anomalies in the calibration process

• Make sure that details relating to a site (EIRP, Location, Height, Antenna file) correspond to reports from CW Survey.

• Use Asset utilities to get visual representation of the received signal vs distance.

Data filteringData filtering

• Filter clutter types that have less than 500 bins. Clutter offsets or them will be estimated Filter clutter types that have less than 500 bins. Clutter offsets or them will be estimated later in the model tuning process.later in the model tuning process.

• Filter out any file which shows extreme in signal level.Filter out any file which shows extreme in signal level.

• Unusually high signal level at far distance can be caused by reflection over big water Unusually high signal level at far distance can be caused by reflection over big water surface, or driving along route which is higher than antenna.surface, or driving along route which is higher than antenna.

• Unusually weak signal level can be caused by driving behind blocking object.Unusually weak signal level can be caused by driving behind blocking object.

• Okumura –Hata can’t model above situations, therefore these data must be filtered out.Okumura –Hata can’t model above situations, therefore these data must be filtered out.

• With careful route planning filtering can be avoided.With careful route planning filtering can be avoided.

• Having more than one file per site makes filtering during post processing much easierHaving more than one file per site makes filtering during post processing much easier

Filtering example-Driving above Tx antennaFiltering example-Driving above Tx antenna

Filtering example-Blocking objectFiltering example-Blocking object

Displaying CW measurements in AssetDisplaying CW measurements in Asset

– Data Types-CW Measurements-CW Data Types-CW Measurements-CW SignalSignal

– To set up thresholds double click on CW To set up thresholds double click on CW Signal and specify thresholds under Signal and specify thresholds under Categories tabCategories tab

– The same goes for other options inside The same goes for other options inside CW MeasurementsCW Measurements

Okumura-Hata in AssetOkumura-Hata in Asset

• Asset uses slightly modified Okumura-Hata:

Ploss =K1 + K2*log(d) + K3*Hms + K4*log(Hms) + K5*log(Heff) + K6*log(Heff)*log(d) + K7*Ldiff + Lclutter

d is distance in km between Tx antenna and mobile station

Hms is mobile station height

Heff is effective antenna height in metres

Ldiff is a loss due to diffraction

Lclutter is a clutter loss

• Asset has 4 algorithms for calculating effective antenna height

• Asset has 4 algorithms for calculating diffraction

Asset improvementsAsset improvements

K1 near and k2 near are designed to overcome Okumura-Hata limitation for close K1 near and k2 near are designed to overcome Okumura-Hata limitation for close distances. distances.

Through Clutter Loss – takes into the account clutter profile along distance d from mobile Through Clutter Loss – takes into the account clutter profile along distance d from mobile station to base station.station to base station.

Advantages in improved accuracy/reduced standard deviation error and more realistic Advantages in improved accuracy/reduced standard deviation error and more realistic calculated predictions.calculated predictions.

Through Clutter Model DefinitionThrough Clutter Model Definition

Each clutter category is given Through Clutter Loss (dB/km) on the path between Each clutter category is given Through Clutter Loss (dB/km) on the path between transmitter and receiver.transmitter and receiver.

Through clutter losses are linearly weighted. The clutter nearest the mobile station has Through clutter losses are linearly weighted. The clutter nearest the mobile station has highest effecthighest effect

Overview of Model CalibrationOverview of Model Calibration

• There must be project set up (map data, antennas, sites, propagation model) in order to There must be project set up (map data, antennas, sites, propagation model) in order to start tuningstart tuning

• Load CW dataLoad CW data

• Make appropriate filtering, usually:Make appropriate filtering, usually:• -110dBm to -40dBm-110dBm to -40dBm• 125m to 10000125m to 10000

• Start with the default values for k parametersStart with the default values for k parameters• Do Auto TuneDo Auto Tune• Try all combination of effective antenna height and diffraction algorithms and determine Try all combination of effective antenna height and diffraction algorithms and determine

which one gives the lowest standard deviationwhich one gives the lowest standard deviation

• Take note of second and third bestTake note of second and third best

Model settingModel setting

• Tools-Model Tuning-OptionsTools-Model Tuning-Options

• Select the resolution of mapping Select the resolution of mapping datadata

• Select the model as a start tuning Select the model as a start tuning model. It is recommended to use model. It is recommended to use default modeldefault model

Filter SettingFilter Setting

• Tools-Model Tuning-Options-FilterTools-Model Tuning-Options-Filter

• Set up distance filteringSet up distance filtering

• Set up signal level filteringSet up signal level filtering

• Filter out clutter types with insufficient data Filter out clutter types with insufficient data by highlighting themby highlighting them

• If you tune k7 click just NLOSIf you tune k7 click just NLOS

• Click antenna button if directional antennas Click antenna button if directional antennas were usedwere used

Auto TuneAuto Tune

• Tools-Model Tuning-Auto TuneTools-Model Tuning-Auto Tune

• Set up deltasSet up deltas

•

• Click fix box next to the k factor you don’t want to Click fix box next to the k factor you don’t want to tunetune

• Click Auto Tune under Tools tabClick Auto Tune under Tools tab

• Wait for resultsWait for results

• You can apply new parameters by clicking apply You can apply new parameters by clicking apply new parametersnew parameters

• Through clutter offsets and clutter offsets are Through clutter offsets and clutter offsets are under Clutter tabunder Clutter tab

K parametersK parameters

• K3 and K4 are not altered. This is because they relate to mobile height which in a typical K3 and K4 are not altered. This is because they relate to mobile height which in a typical cellular system is constant making these coefficients redundant.cellular system is constant making these coefficients redundant.

• K7 is the diffraction parameter. It can be determined by tuning just NLOS data.K7 is the diffraction parameter. It can be determined by tuning just NLOS data.

• All K parameters must keep the same polarity as in the original Okumura Hata modelAll K parameters must keep the same polarity as in the original Okumura Hata model

• K1, K2, K7 >0K1, K2, K7 >0

• K3, K5, K6 <0K3, K5, K6 <0

• Above step can be easily fulfil by determining the delta range under Auto tune windowAbove step can be easily fulfil by determining the delta range under Auto tune window

Default K parametersDefault K parameters

k1, k2 near calibrationk1, k2 near calibration

• If model is not good close to the site, for example up to 700m, auto tune the If model is not good close to the site, for example up to 700m, auto tune the model from 700m to 10k. Apply found k parameters.model from 700m to 10k. Apply found k parameters.

• Tune model again with k5,k6 and k7 locked and filter out distances above 700m.Tune model again with k5,k6 and k7 locked and filter out distances above 700m.

• Result will be k1 near and k2 near.Result will be k1 near and k2 near.

• If standard deviation is still bad try with other distances until you find the best fit.If standard deviation is still bad try with other distances until you find the best fit.

Clutter offsetClutter offset

• Some through clutter offsets and clutter offsets need to be estimated due to Some through clutter offsets and clutter offsets need to be estimated due to insufficient data.insufficient data.

• Estimation is done relative to the clutter offsets with sufficient data.Estimation is done relative to the clutter offsets with sufficient data.

• Clutter offsets must be realistic relative to each other.Clutter offsets must be realistic relative to each other.

• Water will have the smallest offset while building and forest the highest.Water will have the smallest offset while building and forest the highest.

Adjusting MEAdjusting ME

• Mean error is usually altered after estimation of clutter offsets.Mean error is usually altered after estimation of clutter offsets.

• ME can be easily bring back to 0 by changing k1ME can be easily bring back to 0 by changing k1

• If mean error is If mean error is ΔΔ change k1 to k1+ change k1 to k1+ ΔΔ

Model analysesModel analyses

• Make statistical analyses for ME and SD for different distance ranges.Make statistical analyses for ME and SD for different distance ranges.

• In the range of interest, typically 1km to 4km, following requirements should In the range of interest, typically 1km to 4km, following requirements should be fulfilled be fulfilled

• -1 < -1 < ME ME < 1< 1

• SD < 8SD < 8

• If ME or SD is outside the above specified values, try with changing the dual If ME or SD is outside the above specified values, try with changing the dual slope distance or take the second best model from the initial tuning.slope distance or take the second best model from the initial tuning.

Statistical Breakdown for Coastal Urban 15mStatistical Breakdown for Coastal Urban 15m

No. of Bins Mean Error Standard Deviation Actual

Calibration whole range 80260 0 6.8

125~250 1030 -0.5 8.1

250~500 2899 -1.1 8

500~1km 8700 -1.4 7.7

1km~2km 19351 -0.1 7.4

2km~4km 29598 0.9 6.6

4km~8km 17791 -0.4 5.4

8km~16km 891 -1.6 5.2

Statistical Breakdown for ME and SDStatistical Breakdown for ME and SD

Standard deviation distribution

0

1

2

3

4

5

6

7

8

9

Distance (km)

Sta

nd

ard

dev

iati

on

Mean error vs distance

-2

-1.5

-1

-0.5

0

0.5

1

1.5

Distance (km)

Mea

n er

ror

Validation of Tuned Model-Site 1Validation of Tuned Model-Site 1

Apoview site

No. of Bins

Mean Error

Standard Deviation Actual

Calibration whole range

10668 -1 6.1

125~250 53 4.3 5.6

250~500 368 0.4 7.5

500~1km 1153 -2.7 7.3

1km~2km 2324 -1.5 6.3

2km~4km 4383 0.4 5.9

4km~8km 2343 -2.4 5.1

8km~16km 44 -2.4 4.1

Coverage plot – Site 1Coverage plot – Site 1

Validation of Tuned Model-Site 2Validation of Tuned Model-Site 2

Banawa site

No. of Bins Mean Error Standard Deviation Actual

Calibration whole range

6354 0.1 6.4

125~250 95 11.6 5.2

250~500 42 2.7 5.7

500~1km 252 -1.8 7.7

1km~2km 1620 -0.9 6.3

2km~4km 3228 1 6.4

4km~8km 1041 -1.6 4.8

8km~16km 76 -2.9 3.8

Coverage plot – Site 2Coverage plot – Site 2

3737

Thank YouThank You

Netwing Technologies Private Ltd.Netwing Technologies Private Ltd.