Fundamentals COPYRIGHTED MATERIALadaptive and reconﬁgurable coding and modulation including distributed source coding which is ... from mobile communication systems such as GSM and

...

chap01 JWBK007-Glisic April 23, 2007 22:7 Char Count= 0

1Fundamentals

1.1 4G AND THE BOOK LAYOUT

Currently the research community and industry in the field of telecommunications are consideringpossible choices for solutions in the fourth generation (4G) of wireless communications. This chapterwill start with a generic 4G system concept that integrates available advanced technologies and thenfocuses on system adaptability and reconfigurability as possible options for meeting a variety ofservice requirements, available resources and channel conditions. The elements of such a concept canbe found in Refs [1–51]. The chapter will also try to offer a vision beyond the state of the art, withthe emphasis on how advanced technologies can be used for efficient 4G multiple access. Among therelevant issues the focus will be on:

� adaptive and reconfigurable coding and modulation including distributed source coding which isof interest in data aggregation in wireless sensor networks;

� adaptive and reconfigurable space–time coding including a variety of turbo receivers;

� channel estimation and equalization and multiuser detection;

� Orthogonal Frequency Division Multiple Access (OFDMA), Multi Carrier CDMA (MC CDMA)and Ultra Wide Band (UWB) radio;

� linear precoding in MIMO systems;

� cognitive radio including discussion on strategic difference between macro and micro reconfigura-bility;

� cooperative transmit diversity;

� user location in 4G;

� channel modeling;

� cross-layer optimization including adaptive and power efficient MAC layer design, adaptive andpower efficient routing on IP and TCP layer and concept of green wireless network;

� cognitive networks modeling based on game theory.

Advanced Wireless Communications Second Edition Savo G. GlisicC© 2007 John Wiley & Sons, Ltd. ISBN: 978-0-470-05977-7

1

COPYRIG

HTED M

ATERIAL

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2 FUNDAMENTALS

PSTN PLMN

IP Network PrivateNetwork

MobileCellularnetworks

MobileCellular

NetworksAccess

BRANAccess

CognitiveMobile

Terminals

TDMA IS 136EDGEUMTS WCDMAup to 2 MBit/scdma20004GMC CDMAOFDMASpace−Timediversityexpected 100 Mbit/s

IEEE 802.112.4GHz (ISM)FHSS & DSSS5GHz

WLAN, WPAM, WATMIEEE 802.xx, WiMAX,WiBROOFDMSpace−time-frequencycoding, UWB/impulse radioIEEE 802.154G expected data rate 1Gbit/s

Figure 1.1 IMT2000 and WLAN convergence.

Receiver

Pull ofalgorithms

Reconfigurationdecision

Networkparameters andperformancemonitoring

QoSrequirements

Figure 1.2 Reconfigurable cognitive radio concept intersystem roaming and QoS provi-sioning.

An important aspect of wireless system design is power consumption. This will be also incorporatedin the chapter including several layers in the network.

At this stage of the evolution of wireless communications there is a tendency to agree that 4Gwill integrate mobile communications as specified by International Mobile Telecommunications(IMT) standards and Wireless Local Area Networks (WLAN) or in general Broadband Radio AccessNetworks (BRAN). The core network will be based on Public Switched Telecommunications Network(PSTN) and Public Land Mobile Networks (PLMN) based on Internet Protocol (IP) [13, 16, 19, 24,32, 41, 51]. This concept is summarized in Figure 1.1. Each of the segments of the system will befurther enhanced in the future. The inter-technology roaming of the mobile terminal will be based ona reconfigurable cognitive radio concept presented in its generic form in Figure 1.2.

...


4G AND THE BOOK LAYOUT 3

The material in this book is organized as follows:Chapter 1 we start with a general structure of 4G signals, mainly advanced time division multiple

access (ATDMA), code division multiple access (CDMA), orthogonal frequency division multiplex-ing (OFDM), multicarrier CDMA (MC CDMA) and ultra wide band (UWB) signal. These signalswill be elaborated on later in the book.

Chapter 2 this chapter introduces Adaptive coding. The book has no intention of covering all detailsof coding but rather of focusing on those components that enable code adaptability and reconfigura-bility. Within this concept the chapter covers adaptive and reconfigurable block and convolutionalcodes, punctured convolutional codes/code reconfigurability, maximum likelihood decoding/Viterbialgorithm, systematic recursive convolutional code, concatenated codes with interleaver, the iterative(turbo) decoding algorithm and a discussion on adaptive coding practice and prospective. The chapteralso includes presentation of distributed source coding, which is of interest in data aggregation inwireless sensor networks.

Chapter 3 covers adaptive and reconfigurable modulation. This includes coded modulation, trelliscoded modulation (TCM) with examples of TCM schemes such as two-, four- and eight-state trellisesand QAM with 3 bits per symbol transmission. The chapter further discusses signal-set partition-ing, equivalent representation of TCM, TCM with multidimensional constellations, adaptive codedmodulation for fading channels and adaptation to maintain fixed distance in the constellation.

Chapter 4 introduces space–time coding. It starts with a discussion on diversity gain, the encodingand transmission sequence, the combining scheme and ML decision rule for two-branch transmitdiversity scheme with one and M receivers. In the next step it introduces a general discussion onspace–time coding within a concept of space–time trellis modulation. The discussion is then extendedto introduce space–time block codes from orthogonal design, mainly linear processing orthogonaldesigns and generalized real orthogonal designs. The chapter also covers channel estimation im-perfections. It continuous with quasi-orthogonal space–time block codes, space–time convolutionalcodes and algebraic space–time codes. It also includes differential space–time modulation with anumber of examples.

Layered space–time coding and concatenated space–time block coding are also discussed. Es-timation of MIMO channel and space–time codes for frequency selective channels are discussedin detail. MIMO system optimization, including gain optimization by singular value decomposition(svd) are also discussed. This chapter is extended to include a variety of turbo receivers.

Chapter 5 introduces multiuser detection starting with CDMA receivers and signal subspace-basedchannel estimation. Then it extends this approach to iterative space time receivers. In Chapter 7 thisapproach is extended to OFDM receivers.

Chapter 6 deals with equalization, detection in a statistically known time-varying channel, adaptiveMLSE equalization, adaptive joint channel identification and data demodulation, turbo-equalizationKalman filter based joint channel estimation and equalization using higher order signal statistics

Chapter 7 covers orthogonal frequency division multiplexing (OFDM) and MC CDMA. Thefollowing topics are discussed: timing and frequency offset in OFDM, fading channel estimationfor OFDM systems, 64-DAPSK and 64-QAM modulated OFDM signals, space–time coding withOFDM signals, layered space–time coding for MIMO- OFDM, space–time coded TDMA/OFDMreconfiguration efficiency, multicarrier CDMA system, multicarrier DS-CDMA broadcast systems,frame-by-frame adaptive rate coded multicarrier DS-CDMA systems, intermodulation interfer-ence suppression in multicarrier DS-CDMA systems, successive interference cancellation inmulticarrier DS-CDMA systems, MMSE detection of multicarrier CDMA, multiuser receiver forspace–time coded multicarrier CDMA systems, and peak-to-average power ratio (PAPR) problemmitigation.

Chapter 8 introduces Ultra Wide Band Radio. It covers topics like UWB multiple access inGaussian channels, the UWB channel, UWB systems with M-ary modulation, M-ary PPM UWBmultiple access, coded UWB schemes, multiuser detection in UWB radio, UWB with space–timeprocessing and beamforming for UWB radio.

Chapter 9 covers antenna array signal processing with focus on space–time receivers forCDMA communications, MUSIC and ESPRIT DOA estimation, joint array combining and MLSEreceivers, joint combiner and channel response estimation, and complexity reduction in wide-bandbeamforming.

...


4 FUNDAMENTALS

Chapter 10 discusses adaptive/reconfigurable cognitive radio. The focus is on energy efficientadaptive radio, frame length adaptation, energy-efficient adaptive error control, processing-gain adap-tation, trellis based processing/adaptive maximum likelihood sequence equalizer, a software radioarchitecture for linear multiuser detection, and reconfigurable ASIC architecture.

Chapter 11 introduces cooperative transmit diversity as a power efficient technology to increasethe coverage in multihop wireless networks. It is expected that elements of this approach will be usedin 4G cellular systems too, especially with relaying as a simple case of this approach.

Chapter 12 covers the problem of the coexistence of different wireless networks as it becomes moreand more important, and solutions other than frequency planning and standardization are needed.For this reason Chapter 12 has been completely replaced and now presents an example of the latestschemes for interference suppression in ultra wide band (UWB) cognitive systems, like advancedpersonal area networks (PAN), and discusses its performance. The schemes can be used significantlyto improve performance of UWB systems, e.g. high speed Bluetooth, in the presence of interferencefrom mobile communication systems such as GSM and WCDMA. It is also effective in the presenceof WLAN systems, which are nowadays based on OFDMA technology (e.g. IEEE802.11, 16e, 20).The chapter also discusses the effectiveness of the scheme in suppressing MC CDMA, which is acandidate technology for 4G mobile communications. The effectiveness decreases if the number ofsubcarriers is increased.

Chapter 13 is significantly modified to include more details on positioning. This is the resultof the anticipation that this technique will be gaining more and more space in advanced wirelesscommunications. This is also supported by activities within the Galileo program in Europe.

Chapter 14 discusses channel modeling and measurements for 4G. It includes macrocellularenvironments (1.8 GHz), urban spatial radio channels in macro/micro cell (2.154 GHz), MIMOchannels in micro and pico cell environments (1.71/2.05 GHz), outdoor mobile channels (5.3 GHz),microcell channels (8.45 GHz), wireless MIMO LAN environments (5.2 GHz), indoor WLANchannels (17 GHz), indoor WLAN channel (60 GHz) and UWB channel models.

Chapter 15 includes discussion on adaptive 4G networks. It covers adaptive MAC layer, minimumenergy routing in pear-to-pear mobile wireless networks, least-resistance routing in wireless networksand power optimal routing in wireless networks for guaranteed TCP layer QoS.

Chapter 16 represents a significant extension of the book to include cognitive networks and modelsbased on game theory. The following topics are covered:� cognitive power control as a noncooperative game, including power control games with QoS

guarantee, multiuser detection and MIMO systems;

� game-theory-based MAC for ad hoc networks;

� tit-for-tat (TFT) game-theory-based packet forwarding strategies in ad hoc networks;

� TFT game-theory-based modelling of node cooperation with energy constraints;

� packet forwarding models based on dynamic Bayesian games;

� game theoretic models for routing in wireless sensor networks;

� profit driven routing in cognitive networks;

� game theoretical model of flexible spectra sharing in cognitive networks with social awareness;

� a game theoretical modelling of slotted ALOHA protocol;

� game-theory-based modeling of admission in competitive wireless networks;

� modelling access point pricing as a dynamic game.

1.2 GENERAL STRUCTURE OF 4G SIGNALS

The evolution of the common air interface in wireless communications can be presented as in Table1.1 The coding and modulation for the 4G air interface are more or less defined but work on a

...


GENERAL STRUCTURE OF 4G SIGNALS 5

Table 1.1 Evolution of the common air interface in mobile communications

Generation 2G 3G 4G

Coding Convolutional coding Turbo coding Turbo coding andspace–time coding

Modulation GMSK, BPSK, QPSK BPSK, QPSK,mQAM

NmQAM (OFDM)

Multiple access TDMA CDMA IIC MAC

new multiple access scheme still remains to be elaborated. In this section we refer to this solutionas intercell interference coordination (IIC) in the MAC layer (IIC MAC) as a new multiple accessscheme for 4G systems.

In this section we will summarize the signal formats used in existing wireless systems and pointout possible ways of evolution towards the 4G system. The focus will be on OFDMA, MC CDMAand UWB signals.

1.2.1 Advanced time division multiple access (ATDMA)

In a TDMA system, each user is using a dedicated time slot within a TDMA frame as in GSM (GlobalSystem of Mobile Communications) or in ADC (American Digital Cellular System). Additional dataabout the signal format and system capacity are given in [54]. The evolution of the ADC systemresulted in TIA (Telecommunications Industry Association) Universal Wireless Communications(UWC) Standard 136 [54]. The evolution of GSM resulted in a system known as Enhanced Data ratesfor GSM Evolution (EDGE) with parameters summarized also in [54].

1.2.2 Code division multiple access (CDMA)

The CDMA technique is based on spreading the spectra of the relatively narrow information signalSn by a code c, generated by much higher clock (chip) rate. Different users are separated by usingdifferent uncorrelated codes. As an example, the narrowband signal in this case can be a PSK signalof the form

Sn = b(t, Tm) cos ωt (1.1)

where 1/Tm is the bit rate and b = ±1 is the information. The baseband equivalent of (1.1.) is

Sbn = b(t, Tm) (1.1a)

A spreading operation, presented symbolically by operator ε( ), is obtained if we multiply anarrowband signal by a pseudo noise (PN) sequence (code) c(t, Tc) = ±1. The bits of the sequenceare called chips and the chip rate is 1/Tc � 1/Tm. The wideband signal can be represented as:

Sw = ε(Sn) = cSn = c(t, Tc)b(t, Tm) cos ωt (1.2)

The baseband equivalent of (1.2) is

Sbw = c(t, Tc)b(t, Tm) (1.2a)

Despreading, represented by operator D(), is performed if we use ε() once again and bandpassfiltering, with the bandwidth proportional to 2/Tm , represented by operator BPF() resulting in

D(Sw) = BPF(ε(Sw)) = BPF(cc b cos ωt) = BPF(c2 b cos ωt) = b cos ωt (1.3)

The baseband equivalent of (1.3) is

D(Sb

w

) = LPF(ε(Sb

w)) = LPF(c(t, Tc)c(t, Tc)b(t, Tm)) = LPF(b(t, Tm) = b(t, Tm) (1.3a)

...


6 FUNDAMENTALS

where LPF() stands for low pass filtering. This approximates the operation of correlating the inputsignal with the locally generated replica of the code Cor(c, Sw). Nonsynchronized despreading wouldresult in

Dτ (); Cor(cτ , Sw) = BPF(ετ (Sw)) = BPF(cτ c b cos ωt) = ρ(τ )b cos ωt (1.4)

In Equation (1.4) BPF would average out the signal envelope cτ c resulting in E(cτ c) = ρ(τ ). Thebaseband equivalent of Equation (1.4) is

Dτ ( ); Cor(cτ , Sb

w

) =Tm∫

0

cτ Sbw dt = b(t, Tm)

Tm∫0

cτ c dt = bρ(τ ) (1.4a)

This operation would extract the useful signal b as long as τ ∼= 0, otherwise the signal will besuppressed because, ρ(τ ) ∼= 0 for τ ≥ Tc. Separation of multipath components in a RAKE receiver isbased on this effect. In other words if the received signal consists of two delayed replicas of the form

r = Sbw(t) + Sb

w(t − τ )

the despreading process defined by Equation (1.4a) would result in

Dτ ( ); Cor(c, r ) =Tm∫

0

cr dt = b(t, Tm)

Tm∫0

c(c + cτ ) dt = bρ(0) + bρ(τ )

Now, if ρ(τ ) ∼= 0 for τ ≥ Tc, all multipath components reaching the receiver with a delay largerthan the chip interval will be suppressed.

If the signal transmitted by user y is despread in receiver x, the result is

Dxy(); BPF(εxy(Sw)) = BPF(cx cy by cos ωt) = ρxy(t)by cos ωt (1.5)

So in order to suppress the signals belonging to other users (multiple access interference, MAI), thecrosscorrelation functions should be low. In other words, if the received signal consists of the usefulsignal plus the interfering signal from the other user:

r = Sbwx (t) + Sb

wy(t) = bx cx + bycy (1.6)

the despreading process at receiver of user x would produce

Dxy(); Cor(cx , r ) =Tm∫

0

cxr dt = bx

Tm∫0

cx cx dt + by

Tm∫0

cx cy dt = bxρx (0) + byρxy(0) (1.7)

When the system is properly synchronized ρx (0) ∼= 1, and if ρxy(0) ∼= 0 the second componentrepresenting MAI will be suppressed. This simple principle is elaborated in the WCDMA standardresulting in a collection of transport and control channels. The system is based on 3.84 Mcips rateand up to 2 M bits/s data rate. In a special downlink, high data rate, shared channel, the data rate andsignal format are adaptive. There shall be mandatory support for QPSK and 16QAM and optionalsupport for 64 QAM based on UE capability which will proportionally increase the data rate. Fordetails see www.3gpp.com.

1.2.3 Orthogonal frequency division multiplexing (OFDM)

In wireless communications, the channel imposes a limit on data rates in the system. One way toincrease the overall data rate is to split the data stream into a number of parallel channels and usedifferent subcarriers for each channel. The concept is presented in Figures 1.3 and 1.4 and representsthe basic idea of OFDM system. The overall signal can be represented as

x(t) =N−1∑n=0

{Dne j2π n

N fS t}

; − k1

fs< t <

N + k2

fs(1.8)

...



Gate

Gate

Filter Mod AddGate

Gate

Filter

Filter

Filter

Mod

Mod

Mod

tw1cos

tw1sin

tw2cos

tw2sinClockClock

Figure 1.3 An early version of OFDM.

f

Figure 1.4 Spectrum overlap in OFDM.

In other words complex data symbols [D0, D1, . . . , DN−1] are mapped in OFDM symbols[d0, d1, . . . , dN−1] such that

dk =N−1∑n=0

Dne j2π knN . (1.9)

The output of the FFT block at the receiver produces data per channel. This can be represented as

D̃m = 1

N

N−1∑k=0

rke− j2πm k2N

rk =N−1∑n=0

Hn Dne j2π n2N k + n (k) (1.10)

D̃m ={

Hn Dn + N (n) , n = mN (n) , n �= m

The system block diagram is given in Figure 1.5.In order to eliminate residual intersymbol interference, a guard interval after each symbol is used

as shown in Figure 1.6.

...


8 FUNDAMENTALS

Block into N complex numbers

IFFT Filter

Filter Sample Block

Synch FFT UnblockEqualize

Data In

Rate I/T

Rate N/T

Channel

Channel

Data Out

Figure 1.5 Basic OFDM system.

f

1/T

Guard Interval

Figure 1.6 OFDM time and frequency span.

An example of an OFDM signal specified by IEEE 802.11a standard is shown in Figure 1.7.The signal parameters are: 64 points FFT, 48 data subcarriers, 4 pilots, 12 virtual subcarriers, DCcomponent 0, guard interval 800 ns. Discussion on OFDM and an extensive list of references on thetopic are included in Chapter 7.

1.2.4 Multicarrier CDMA (MC CDMA)

Good performance and flexibility to accommodate multimedia traffic are incorporated in MC CDMAwhich is obtained by combining CDMA and OFDM signal formats.

Figure 1.8 shows the DS-CDMA transmitter of the j-th user for binary phase shift keying/coherentdetection (CBPSK) scheme and the power spectrum of the transmitted signal, respectively, whereG DS = Tm/Tc denotes the processing gain and C j (t) = [C j

1 C j2 · · · C j

G DS] the spreading code of the

jth user.Figure 1.9 shows the MC-CDMA transmitter of the jth user for the CBPSK scheme and the

power spectrum of the transmitted signal, respectively, where GMC, denotes the processing gain, NC

the number of subcarriers, and C j (t) = [C j1 C j

2 · · · C jG MC

] the spreading code of the jth user. The

...



Figure 1.7 802.11a/HIPERLAN OFDM.

Datastream

Scanningcorrelator

Tc

2Tc

Path selector

Rake receiver

Path gain 2

Path gain GDS

Path gain 1

j C (t)

Combiner

j C (t)

j C (t)

j C (t) COS(2πfot)

j C2

j CGDS

j C1

j C3

Time

Power spectrum of transmitted signalf0 Frequency

Time

GDST

LPF

LPF

LPF

Figure 1.8 DS-CDMA scheme.

j CG

j C2

j C1

j C3

MC

j

C1

j q

1

j q

2 j

C2

j D

Data stream

ja

Time

Copie

cos(2πf1t

Nc=GM

cos(2πfGMCt)

ja

Time

j

CGMC

j

qGMC

Σ

LP

LP

LP

cos(2πf1t

cos(2πf2t

Σ

cos(2πfGMC t)

cos(2πf1t

frequenc

freq

uenc

y

f1 f2 f3

Figure 1.9 MC-CDMA scheme.

...


10 FUNDAMENTALS

cos(2πf1t)j

C1

j a1

j a1

Serial/parallel converter Σ

jCGMC

cos(2πf1+(GMC-1)/TS)) 1:P

Data stream

Frequency Nc = P×GMC

1 2

Figure 1.10 Modification of MC-CDMA scheme: spectrum of its transmitted signals.

MC-CDMA scheme is discussed assuming that the number of subcarriers and the processing gainare all the same.

However, we do not have to choose NC = GMC, and actually, if the original symbol rate is highenough to become subject to frequency selective fading, the signal needs to be first S/P-convertedbefore spreading over the frequency domain. This is because it is crucial for multicarrier transmissionto have frequency nonselective lading over each subcarrier.

Figure 1.10 shows the modification to ensure frequency nonselective fading, where TS denotesthe original symbol duration, and the original data sequence is first converted into P parallel seque-nces, and then each sequence is mapped onto GMC subcarriers (NC = P × GMC).

The multicarrier DS-CDMA transmitter spreads the S/P-converted data streams using a givenspreading code in the time domain so that the resulting spectrum of each subcarrier can satisfythe orthogonality condition with the minimum frequency separation. This scheme was originallyproposed for an uplink communications channel, because the introduction of OFDM signaling into aDS-CDMA scheme is effective for the establishment of a quasi-synchronous channel.

Figure 1.11 shows the multicarrier DS-CDMA transmitter of the jth user and the power spectrumof the transmitted signal, respectively, where GMD denotes the processing gain, NC the number ofsubcarriers, and C j (t) = [C j

1 C j2 · · · C j

GMD] the spreading code of the jth user.

The multitone MT-CDMA transmitter spreads the S/P-converted data streams using a givenspreading code in the time domain, so that the spectrum of each subcarrier prior to the spreadingoperation can satisfy the orthogonality condition with the minimum frequency separation. Therefore,the resulting spectrum of each subcarrier no longer satisfies the orthogonality condition. The MT-CDMA scheme uses longer spreading codes in proportion to the number of subcarriers, as comparedwith a normal (single carrier) DS-CDMA scheme, therefore, the system can accommodate more usersthan can the DS-CDMA scheme.

Figure 1.12 shows the MT-CDMA transmitter of the jth user for CBPSK scheme and the powerspectrum of the transmitted signal, respectively, where GMT denotes the processing gain, NC thenumber of subcarriers, and C j (t) = [C j

1 C j2 · · · C j

GMT] the spreading code of the jth user.

...



Datastream

Time

Serial- to-

parallel

j C (t)

j C (t)

j C (t) j

C (t)

j C (t)

j C (t)

cos(2πf1t)

cos(2πfNct)

Time

Σ

LP

LP

LP

cos(2πf1t)

cos(2πf2t)cos(2πf2t)

cos(2πfNct)

Parallel-to-serial

converter

j C1

j C3

j C2

Timej

CGMD

Power spectrum of trasmitted signal

Figure 1.11 Multicarrier DS-CDMA scheme.

GMT

Data stream

Time

Serial-to-parallelconverter

j C (t)

j C (t)

j C (t)

cos(2πf1t)

cos(2πfNct)

Time

Σ

cos(2πf1t)

cos(2πf2t)cos(2πf2t)

cos(2πfNct)

Parallel -to-serial converter

Time

Rakecombiner 1

Rake combiner 2

Rake combiner Nc

j C4

j C6

j C2

j C1

j C3

j C5

jC7

j CGMT

j = CGDS

× Nc

f1 f2 f3 f4...fNc Frequency

Figure 1.12 MT-CDMA scheme.

All these schemes will be discussed in detail in Chapter 7.

1.2.5 Ultra wide band (UWB) signals

For the multipath resolution in indoor environments a chip interval of the order of few nanosecondsis needed. This results in a spread spectrum signal with the bandwidth of the order of few GHz. Sucha signal can also be used with no carrier resulting in what is called impulse radio (IR) or ultra wideband (UWB) radio. A typical form of the signal used in this case is shown in Figure 1.13. A collectionof pulses received on different locations within the indoor environment is shown in Figure 1.14, and

...


12 FUNDAMENTALS

t (nanoseconds)

0.1

1

0.8

0.6

0.4

0.2R

ecei

ved

mon

ocyc

le ω

rec

(t)

−0.2

−0.4

0.2 0.3 0.4 0.5 0.6

Figure 1.13 A typical ideal received monocycle ωrec (t) at the output of the antenna sub-system as a function of time in nanoseconds.

−10 −6−8 −4 −2 0Time (nanoseconds)

AP17F31

0.8

0.6

0.4

0.2

−0.8

−0.6

−0.4

−0.2

2 4 6 8 10

Figure 1.14 A collection of received pulses in different locations [53] c© IEEE 2007.

a collection of channel inpulse responses in Figure 1.15. Ultra wide band radio will be discussed indetail in Chapter 8. In this section we will initially define only a possible signal format.

A typical time-hopping format used in this case can be represented as

s(k)tr

(t (k)

) =∞∑

j=−∞ωtr

(t (k) − jT f − c(k)

j Tc − δd (k)[ j/Ns ]

)(1.11)

where t (k) is the kth transmitter’s clock time and T f is the pulse repetition time. The transmitted pulsewaveform ωtr is referred to as a monocycle. To eliminate collisions due to multiple access, each user(indexed by k) is assigned a distinctive time shift pattern {c(k)

j } called a time-hopping sequence. Thisprovides an additional time shift of c(k)

j Tc seconds to the jth monocycle in the pulse train, whereTc is the duration of addressable time delay bins. For a fixed T f the symbol rate, Rs, determinesthe number Ns of monocycles that are modulated by a given binary symbol as Rs = (

1/Ns T f

)s−1.

The modulation index δ is chosen to optimize performance. For performance prediction purposes,most of the time the data sequence {d (k)

j }∞j=−∞ is modeled as a wide-sense stationary random process

composed of equally likely symbols. For data, a pulse position data modulation is used.

...



Figure 1.15 A collection of channel delay profiles [52] c© IEEE 2002.

When K users are active in the multiple-access system, the composite received signal at the outputof the receiver’s antenna is modeled as:

r (t) =K∑

k=1

Aks(k)rec (t − τk) + n (t) (1.12)

The antenna/propagation system modifies the shape of the transmitted monocycle ωtr (t) to ωrec (t)on its output. An idealized received monocycle shape ωrec(t) for a free-space channel model with nofading is shown in Figure 1.13.

The optimum receiver for a single bit of a binary modulated impulse radio signal in additive whiteGaussian noise (AWGN) is a correlation receiver

‘decide d (1)0 = 0’ if

Ns−1∑j=0

pulsecorrelatoroutput�= α j (u)︷︸︸︷∫ τ1+( j+1)T f

τ1+ jT f

r (u, t) υ(

t − τ1 − jT f − c(1)j Tc

)dt

︸︷︷︸teststatistic

�= α(u)

> 0

(1.13)

where υ (t)�=ωrec (t) − ωrec (t − δ).

The spectra of a signal using TH is shown in Figure 1.16. If instead of TH a DS signal isused the signal spectra is shown in Figure 1.17(a) for pseudorandom code and Figure 1.17(b) for arandom code. The FCC (Frequency Control Committee) mask for indoor communications is shownin Figure 1.18. Possible options for UWB signal spectra are given in Figures 1.19 and 1.20 for singleband and Figure 1.21 for multiband signal format. For more details see http://www.uwb.org andhttp://www.uwbmultiband.org.

The optimal detection in a multiuser environment, with knowledge of all time-hopping sequences,leads to complex parallel receiver designs [2]. However, if the number of users is large and no suchmultiuser detector is feasible, then it is reasonable to approximate the combined effect of the otherusers’ dehopped interfering signals as a Gaussian random process. All details regarding the systemperformance will be discussed in Chapter 8.

...


14 FUNDAMENTALS

0 2 4 6 8 10 12−70

−60

−50

−40

−30

−20

−10

0

10

Power(dB)

random TH

Figure 1.16 Spectra of a TH signal.

0 2 4 6 8 10 12−70

−60

−50

−40

−30

−20

−10

0

10

Frequency (GHz)

pseudo

random DS

Power(dB)

0 2 4 6 8−70

−60

−50

−40

−30

−20

−10

0

10

Frequency (GHz)

Power(dB)

random

DS

(a)

(b)

10 12

Figure 1.17 Spectra of pseudorandom DS and random DS signal.

...


0 2 4 6 8 10 12-

-

-

-

-

-

-

-

-

Frequency (GHz)

Power(dBm)

GPS band

802.11a

802.11b

Figure 1.18 FCC frequency mask.

FCC mask for indoor

Gaussian pulse: 0.36 ns

Gaussian pulse: 0.72 ns

0 2 4 6 8 10 12 −95

−90

−85

−80

−75

−70

−65

−60

−55

−50

−45

−40

Frequency (GHz)

Power(dBm)

Figure 1.19 FCC mask and possible UWB signal spectra.

0 2 4 6 8 10 12

FCCmask possible spectra

−80

−75

−70

−65

−60

−55

−50

−45

−40

Frequency (GHz)

Power(dBm)

Figure 1.20 Single band UWB signal.

15

...


16 FUNDAMENTALS

1 2 3 4 5 6 7 8 9 10 11 12−55

−50

−45

−40

Frequency (GHz)

Power(dBm)

Figure 1.21 Multi band UWB signal.

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Fundamentals COPYRIGHTED MATERIALadaptive and reconﬁgurable coding and modulation including distributed source coding which is ... from mobile communication systems such as GSM and

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