Table Of Content
Adaptive and Iterative Signal Processing in Communications
Adaptivesignalprocessing(ASP)anditerativesignalprocessing(ISP)areimportanttech-
niquesinimprovingtheperformanceofreceiversincommunicationsystems.Usingexam-
ples from practical transceiver designs, this book describes the fundamental theory and
practical aspects of both methods, providing a link between the two where possible. The
book is divided into three parts: the first two parts deal with ASP and ISP, respectively,
eachinthecontextofreceiverdesignoverintersymbolinterference(ISI)channels.Inthe
thirdpart,theapplicationsofASPandISPtoreceiverdesigninotherinterference-limited
channels, including CDMA and MIMO, are considered; the author attempts to illustrate
in this section how the two techniques can be used to solve problems in channels that
haveinherentuncertainty.Withillustrationsandworkedexamples,thistextwillbesuitable
forgraduatestudentsandresearchersinelectricalengineering,aswellasforpractitioners
inthetelecommunicationsindustry.Furtherresourcesforthistitleareavailableonlineat
www.cambridge.org/9780521864862.
Professor Jinho Choi received his Ph.D. in electrical engineering from the Korea
Advanced Institute of Science and Technology (KAIST) in 1994. He currently holds a
Chair position in the Institute of Advanced Telecommunications (IAT), the University of
WalesSwansea,UK.HeisaseniormemberoftheIEEEandanassociateeditorofIEEE
Transactions on Vehicular Technology and an editor of the Journal of Communications
andNetworks.In1999,hewasawardedtheBestPaperAwardforSignalProcessingfrom
EURASIP.
Adaptive and Iterative Signal
Processing in Communications
JINHO CHOI
cambridge university press
Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo
Cambridge University Press
The Edinburgh Building, Cambridge cb2 2ru, UK
Published in the United States of America by Cambridge University Press, New York
www.cambridge.org
Information on this title: www.cambridge.org/9780521864862
© Cambridge University Press 2006
This publication is in copyright. Subject to statutory exception and to the provision of
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without the written permission of Cambridge University Press.
First published in print format 2006
isbn-13 978-0-511-60746-2 OCeISBN
isbn-13 978-0-521-86486-2hardback
isbn-10 0-521-86486-0 hardback
Cambridge University Press has no responsibility for the persistence or accuracy of urls
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Contents
Listoffigures pageviii
Listoftables xii
Preface xiii
Listofsymbols xv
Listofabbreviations xvi
1 Introduction 1
1.1 Communicationsininterference-limitedenvironments 1
1.2 Issuesinreceiverdesign 5
1.3 Adaptivesignalprocessing 7
1.4 Iterativesignalprocessing 7
1.5 Outlineofthebook 10
1.6 Limitationsofthebook 10
I ISIchannelsandadaptivesignalprocessing 13
2 Channelequalizationfordispersivechannels 15
2.1 ISIchannelsandtheequalizationproblem 15
2.2 Linearequalizers 19
2.3 Decisionfeedbackequalizers 26
2.4 Adaptivelinearequalizers 33
2.5 Adaptivedecisionfeedbackequalizers 43
2.6 Summaryandnotes 44
2.7 AppendixtoChapter2:ConvergenceoftheLMSalgorithm 44
3 Sequencedetectionwithadaptivechannelestimation 48
3.1 MLSDandtheViterbialgorithm 48
3.2 Channelestimation 61
3.3 MLSDwithestimatedchannel 65
3.4 Per-survivorprocessingwithadaptivechannelestimation 68
3.5 Summaryandnotes 74
v
vi Contents
4 Estimationanddetectionforfadingmultipathchannels 75
4.1 Introductiontofadingchannelmodeling 75
4.2 MMSEapproachtoestimatetime-varyingchannels 85
4.3 Adaptivealgorithmstotracktime-varyingchannels 89
4.4 Kalmanfilterforchanneltracking 93
4.5 MLSDandPSPwithchanneltrackingforfadingchannels 100
4.6 Summaryandnotes 104
II IterativesignalprocessingforISIchannels 105
5 MAPdetectionanditerativechannelestimation 107
5.1 MAPsymboldetectionoverISIchannels 107
5.2 MLchannelestimationandtheEMalgorithm 118
5.3 IterativechannelestimationwithMAPdetection 127
5.4 MLdatadetectionviatheEMalgorithm 131
5.5 Summaryandnotes 133
6 IterativereceiversoverstaticISIchannels 134
6.1 Abriefoverviewofinformationtheory 134
6.2 Convolutionalcodes 143
6.3 Iterativereceivers 152
6.4 EXITchartanalysis 160
6.5 Summaryandnotes 169
7 Iterativereceiversundertime-varyingchannelconditions 171
7.1 Detection/decodingforunknowntime-varyingchannels 171
7.2 IterativereceiverbasedonExDD–ImCapproach 172
7.3 IterativereceiverbasedonExC–ImDDapproach 179
7.4 Summaryandnotes 188
7.5 AppendixtoChapter7:Gauss–Seideliteration 190
III Otherinterference-limitedsystems 193
8 CDMAsystemsandmultiuserdetection 195
8.1 Overviewofcellularsystems 195
8.2 IntroductiontoCDMAsystems 197
8.3 Multiuserdetection 203
8.4 Adaptivedetectors 210
8.5 Summaryandnotes 218
9 IterativeCDMAreceivers 219
9.1 Structureofiterativereceivers 219
9.2 MAPdetectioniniterativereceivers 220
Contents vii
9.3 ApproximateMAPdetectionwithiniterativereceivers 223
9.4 MMSE-SCdetectionwithiniterativereceivers 227
9.5 Iterativereceiverwithunknowninterferers 232
9.6 Summaryandnotes 238
10 Iterativereceiversformultipleantennasystems 239
10.1 Spacediversity 239
10.2 MIMOdetection 245
10.3 Iterativereceiverswithknownchannels 253
10.4 Doublyiterativereceiversunderuncertainconditions 261
10.5 Summaryandnotes 268
10.6 AppendixtoChapter10:ProofofEq.(10.71) 269
11 CodedOFDMandtheiterativereceiver 271
11.1 IntroductiontoOFDMsystems 271
11.2 CodedOFDM 279
11.3 EM-basediterativechannelestimation 284
11.4 Summaryandnotes 288
11.5 AppendixtoChapter11:DerivationofEq.(11.6) 289
Appendix1 ReviewofsignalprocessingandtheZ-transform 290
Appendix2 Importantpropertiesofmatricesandvectors 293
Appendix3 Backgroundforprobabilityandstatistics 299
References 308
Index 316
Figures
1.1 Radiochannelwithmultipaths. page2
1.2 Multiusersystem. 2
1.3 Dispersivechannelandlinearequalizer. 2
1.4 Uplinkchannelswithspreadsignals. 4
1.5 BlockdiagramforMIMOsystems. 5
1.6 Adaptiveequalization. 7
1.7 Iterativechannelestimationapproach. 8
1.8 Turboequalizerwithintheiterativereceiver. 9
2.1 Communicationsthroughabandlimitedchannel. 16
2.2 Examplesofwaveformsof p(t)andz(t). 16
2.3 Discrete-timedomainISIchannel. 19
2.4 Linearequalizer. 20
2.5 Frequencyresponsesoftwochannels. 25
2.6 BiterrorrateperformanceoftheMMSELEforChannelAandChannelB. 25
2.7 StructureoftheDFE. 26
2.8 BiterrorrateperformanceoftheMMSEDFEwithandwithoutdecisionerrors. 31
2.9 MSEfunctionanditsderivativewhen M =1. 35
2.10 Acaseofdivergencewhenμistoolarge. 35
3.1 FIRchannelwithadditivewhiteGaussiannoise. 49
3.2 BiterrorrateversusSNRfortheAWGNchannelwithoutISI. 52
3.3 TrellisdiagramforanISIchannelwhen P =3. 54
3.4 Twopathsenterstates .Path1isthesurvivalpathandPath2willbe
k
discarded. 56
3.5 ExampleoftheViterbialgorithmonatrellis. 57
3.6 Trellisdiagramwith P =2. 57
3.7 MLsequenceonthetrellisdiagram. 58
3.8 BiterrorrateresultsoftheMLSDandDFEwiththeidealBERthatcanbe
obtainedwithoutISI. 59
3.9 SumsquarederrorcurvesoftheLMSalgorithmwithdifferentvaluesofμ. 63
3.10 BiterrorrateperformanceoftheMLSDwiththechannelestimationusing
theLMSalgorithm. 66
3.11 Errorfloorswhenh =1. 68
0
3.12 Twopathsenterstatek attimel.InthePSP,eachstateateachtimehasan
associatedestimatedCIR. 69
viii
Listoffigures ix
3.13 BiterrorrateperformanceoftheMLSDwithestimatedCIRandPSPin
termsoftheSNR. 70
3.14 BiterrorrateperformanceoftheMLSDwithestimatedCIRandPSPin
termsofthelengthofthepilotsymbolsequence. 71
4.1 Receiverinmotionwiththereceivedsignalthroughasinglepath. 76
4.2 Amplitudeofh(t),|h(t)|,when A1 = A2 =1and fsh,2 =200Hz. 78
4.3 Clarke’spowerspectrumofh(t)withmaximumDopplerfrequency f . 79
d
4.4 Fadingprocesswith f =100Hz. 80
d
4.5 Classificationoffadingchannels. 84
4.6 Pilot-symbol-aided(PSA)modulation. 86
4.7 OptimalvaluesofμdependingonfadingrateandSNR=σ2/σ2with P =4. 92
h n
4.8 BiterrorrateperformanceofthePSPwithKalmanfilterorNLMSfilter
(withμ=0.5)totracktime-varyingchannels. 102
4.9 BiterrorrateperformanceofthePSPwithLMSalgorithm. 103
5.1 Setsofstatetransitionsonthetrellisdiagram. 110
5.2 BiterrorrateresultsoftheMAPsymboldetectionandMLSDwiththe
idealBERwhichcanbeobtainedwithoutISI. 116
5.3 Biterrorrateversus Rσ. 117
5.4 BiterrorrateversusErr . 118
cir
5.5 IterativechannelestimationwiththeMAPsymboldetector. 128
5.6 (Empirical)MSEversusSNR. 129
5.7 EstimatednoisevarianceversusSNR. 129
5.8 BiterrorrateversusSNR. 130
6.1 Theentropyofabinaryrandomvariable. 135
6.2 Binarysymmetricchannel(BSC). 136
6.3 ChannelcapacityandmutualinformationintermsoftheSNR=μ2/σ2. 143
n
6.4 A(2,1,3)convolutionalencoder. 144
6.5 Thestatediagramofa(2,1,3)convolutionalencoder. 144
6.6 Thetrellisdiagramofa(2,1,3)convolutionalencoder. 145
6.7 GeneratingacodedsequenceusingthetrellisdiagraminExample6.2.1. 146
6.8 BiterrorrateperformanceoftheMLandMAPdecodingforarate-half
convolutionalcodewithgeneratorpolynomial(7,5)inoctal. 149
6.9 Thestatediagramrequiredtofindthetransferfunctionforthefundamental
pathsoftheconvolutionalencoderinFig.6.4. 150
6.10 Blockdiagramofthetransmitterforcodedsignaltransmission. 152
6.11 Blockdiagramfortheiterativereceiver. 153
6.12 BiterrorrateperformanceoftheiterativereceiverwiththeMAPand
MMSE-SCequalizerswhen L =212. 160
6.13 EXITchartsoftheiterativereceiverwithanMAPequalizerandanMAP
decoder. 162
6.14 EXITchartsoftheMAPdecoderforarate-halfconvolutionalcodewith
generatorpolynomial(7,5)inoctal. 164
6.15 HistogramoftheLLRsfromtheMAPequalizerwhenSNR=4dBand
thereisnopriorinformation. 165
