Digitally Enhanced Mixed Signal Systems

380 Pages·2019·16.336 MB·English

by  Chadi Jabbour, Patricia Desgreys, Dominique Dallet

IETMATERIALS,CIRCUITSANDDEVICESSERIES40
Digitally Enhanced Mixed
Signal Systems
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Digitally Enhanced Mixed
Signal Systems
Edited by
Chadi Jabbour, Patricia Desgreys
and Dominique Dallet
TheInstitutionofEngineeringandTechnology
PublishedbyTheInstitutionofEngineeringandTechnology,London,UnitedKingdom
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Contents
Preface xi
1 Digitallyenhancedmixedsignalsystems—thebigpicture 1
ChristianVogel,HaraldEnzinger,andKarlFreiberger
1.1 Motivation 1
1.2 Methodology 2
1.2.1 Asystem-orientedperspective 2
1.2.2 Anextendedviewondataconverters 3
1.2.3 Thedesignprocess 6
1.3 Examples 9
1.3.1 Enhancingpoweramplifiers 9
1.3.2 Enhancingdataconverters 11
1.3.3 Enhancingclockgeneration 13
1.4 Conclusion 14
References 15
2 Nonlinearmodeling 27
RaphaelVansebrouck,Dang-KiènGermainPham,ChadiJabbour,
andPatriciaDesgreys
2.1 Introduction 27
2.2 Nonlinearmodels 27
2.2.1 Parametricmodels 28
2.2.2 Nonparametricmodels 35
2.3 SuitedmodelsforeachRFbloc 38
2.3.1 Extensiontocomplexmodels 38
2.3.2 Modelsforpoweramplifiers 41
2.3.3 Modelsforlow-noiseamplifiers 44
2.3.4 Modelsforbasebandblocks 46
2.4 Digitalcompensationofnonlineardistortions 46
2.4.1 Directlearningarchitecture 47
2.4.2 Indirectlearningarchitecture 57
2.5 Summary 59
References 60
vi Digitallyenhancedmixedsignalsystems
3 Digitalpredistortion 65
GenevièveBaudoin,OlivierVenard,andDang-KiènGermainPham
3.1 Whydoweneedpredistortion? 65
3.1.1 Waveformfeatures 66
3.1.2 Systemlevelconsiderations 67
3.2 Principlesofpredistortion 70
3.3 Analogvsdigitalpredistortion 73
3.4 Mathematicalaspects 74
3.4.1 Basebandformulation 74
3.4.2 pth-Orderinverseoflinearsystem 75
3.5 ModelsforDPDstructures 76
3.5.1 Parametricmodels 77
3.5.2 Nonparametricmodels 83
3.6 Identification 84
3.6.1 Indirectlearningarchitecture 85
3.6.2 Directlearningarchitecture 87
3.6.3 DPDwithiterativelearningcontrol(ILC) 89
3.7 Widebandandsubbandprocessing 92
3.8 Multidimensionalpredistortion 96
3.8.1 Linearizationofnoncontiguouscarrieraggregation 97
3.8.2 Multipleinputmultipleoutput 98
3.9 Modelsizing 99
3.9.1 Modelsizingbyhillclimbingheuristic 100
3.9.2 Modelsizingbyintegergeneticalgorithm 102
3.9.3 Model sizing using orthogonal matching pursuit (OMP)
algorithm 104
3.10 Jointmitigationofvariousimpairments 105
3.10.1 Cooperationwithcrestfactorreduction(CFR) 105
3.10.2 Processingofimperfections 106
3.11 Overviewofcompanionsignalprocessing 109
3.11.1 Synchronization 109
3.11.2 Samplingfrequency 110
3.11.3 Monitoring 110
3.12 Implementation 111
3.13 Conclusion 113
References 113
4 Digitalpost-distortionofradioreceiversandanalog-to-digital
converters 125
BryceMinger,RaphaëlVansebrouck,ChadiJabbour,LoïcFuché,
GuillaumeFerré,DominiqueDallet,PatriciaDesgreys,
andOlivierJamin
4.1 Motivationsforpost-distortionofradioreceiversandADCs 126
4.1.1 Idealvs.practicalradioreceiver 126
4.1.2 Dynamicrangeissuesofmodernradioreceivers 126
Contents vii
4.1.3 Principleofpost-distortion 127
4.1.4 Figuresofmerit 127
4.2 Reviewofdistortionsissuesmetinradioreceivers 128
4.2.1 DistortionissueofIF-digitisingsuperheterodynereceivers 128
4.2.2 Distortionissueoflow-IFreceivers 130
4.2.3 Distortionissueoffull-digitalreceivers 132
4.3 Model-basedpost-distortion:modelling 133
4.3.1 ThepassbandVolterramodel 133
4.3.2 ThebasebandVolterramodel 135
4.3.3 Physical interpretation and dimensioning of Volterra
modelnon-linearityorderandmemorydepth 136
4.3.4 DerivativesofVolterramodel 137
4.3.5 ModellingADCs 137
4.3.6 Modelling IF-digitising superheterodyne and full-digital
receivers 138
4.3.7 Modellinglow-IFreceivers 139
4.3.8 On the usage of baseband Volterra model for reducing
computationalburdenofpassbandVolterramodel 141
4.3.9 Onsamplingfrequencyrequiredfornon-linear
systemmodelling 143
4.4 Model-basedpost-distortion:identificationandinversion 144
4.4.1 Statementsofthemodelidentificationproblem 145
4.4.2 Dealing with the need of both distorted and undistorted
signalsamples 146
4.4.3 SolutionofdirectWienerfilterproblem 147
4.4.4 Inversionofamodeldeterminedbyadirect
identificationscheme 148
4.4.5 Onthenumericalinstabilityissue 149
4.4.6 Effectsofnumericalinstabilityontheleastsquaresolution 150
4.4.7 Effects of numerical instability on stochastic least mean
squareandrecursiveleastsquaresolutions 151
4.5 StudyofanexampleofADCandreceivermodel-based
post-distortionsolution 152
4.5.1 Targetedsystemfeatures 152
4.5.2 Blockdiagramofthepost-distortionsolution 154
4.5.3 Modellingfeatures 154
4.5.4 Identificationfeatures 156
4.5.5 Inversionfeatures 157
4.5.6 Resultsofpost-distortionoperatedonasimulated
full-digitalreceiver 157
4.5.7 Resultsofpost-distortionoperatedonthetargetedsystem 158
4.6 Look-up-table-basedpost-distortionofADCs 160
4.6.1 LUT-basedpost-distortionstrategies 160
4.6.2 DeterminationofLUTvalues 161
4.6.3 INLsequencemodelling 162
4.7 Conclusion 162
References 163
viii Digitallyenhancedmixedsignalsystems
5 Timeorfrequencyinterleavedanalog-to-digitalconverters 171
AntoineBonnetat,HanLeDuc,AliBeydoun,DominiqueDallet,
GuillaumeFerré,Jean-MichelHodé,PatriciaDesgreys,
andChadiJabbour
5.1 Introduction 171
5.2 Principleoftime-interleavedADCsandimpactsofmismatches 172
5.2.1 TIADCprinciple 172
5.2.2 Theimpactofchannelmismatches 173
5.3 Stateoftheartofinterleavedchannelmismatchescompensation 180
5.3.1 Analogcompensationtechniques 181
5.3.2 Mixedsignalcompensationtechniques 181
5.3.3 Digitalcompensation 182
5.4 Feedforwardbackgroundcalibrationtechniqueofclockskews 184
5.4.1 Digitalestimation 184
5.4.2 Digitalcorrection 187
5.4.3 CalibrationforinputatanyNyquistband 191
5.5 Feedbackcalibrationtechniqueofbandwidthmismatches 193
5.5.1 Frequency–responsemismatchmodel 193
5.5.2 Theoreticalchannelmismatchesestimation 199
5.5.3 Channelmismatchescompensation 202
5.5.4 Simulationresults 205
5.6 Extendedfrequencybanddecomposition(cid:2)(cid:3)A/Dconverter 209
5.6.1 EFBDarchitecture 209
5.6.2 Digitalreconstructionsystem(DS) 211
5.6.3 Adaptationalgorithms 215
5.7 Conclusion 218
References 218
6 Digitallyenhanceddigital-to-analogueconverters 227
TorstenLehmann,PasinduAluthwala,andSridevanParameswaran
6.1 Overview 227
6.2 Digital-to-analogueconverters 228
6.2.1 Converterimplementation 228
6.2.2 Convertererrors 230
6.3 DAClinearisation 234
6.3.1 Calibration 234
6.3.2 Dynamicelementmatching 235
6.4 Harmonic-cancellingDACwithpartialDEM 241
6.4.1 Harmonic-cancellingsinewavegeneration 241
6.4.2 DynamicelementmatchinginHC-DACs 244
6.4.3 Experimentalresults 248
6.5 Summary 251
References 252
Contents ix
7 Clockgeneration 255
NaserPourmousavian,TeerachotSiriburanon,Feng-WeiKuo,
MasoudBabaie,andRobertBogdanStaszewski
7.1 DevelopmentofadvancedPLLs 255
7.2 ADPLL-basedtransmitter 260
7.3 Ultra-low-voltage,ultra-low-powerADPLLforIoTapplications 261
7.4 Switched-capacitorDC–DCconverter 263
7.5 Low-voltageADPLLarchitecturewithPVT-tolerantTDC 267
7.6 Switchingcurrent-sourceoscillator 268
7.7 CalibrationforPVT-insensitivetime-to-digitalconverter(TDC) 270
7.8 Design of high-efficiency switched-capacitor doubler/regulator
forevent-basedload 275
7.9 Implementationandexperimentalresults 280
7.10 Conclusion 284
References 286
8 Fixed-pointrefinementofdigitalsignalprocessingsystems 289
DanielMénard,GabrielCaffarena,JuanAntonioLopez,DavidNovo,
andOlivierSentieys
8.1 Introduction 289
8.2 Fixed-pointarithmetic 291
8.2.1 Fixed-pointrepresentation 291
8.2.2 Formatpropagation 292
8.2.3 Quantisationprocessandroundingmodes 293
8.2.4 Overflowmodes 294
8.3 Architecturesupportforfixedpoint 295
8.3.1 Fine-grainedword-lengthoperators 295
8.3.2 Midandcoarse-grainedword-lengthoperators 297
8.4 Fixed-pointconversionprocess 299
8.5 Integer-partword-lengthselection 301
8.5.1 Dynamicrangeevaluation 301
8.5.2 IWLdeterminationandinsertionofscalingoperations 308
8.6 Fractional-partword-lengthdetermination 309
8.6.1 Word-lengthoptimisation 309
8.6.2 Accuracyevaluation 314
8.7 Conclusion 318
References 318
9 Adaptivefiltering 327
RomualdRocher,PascalScalart,andRobinGerzaguet
9.1 Introduction 327
9.2 Algorithmpresentations 328
9.2.1 Leastmeansquarealgorithm 328
9.2.2 Affineprojectionalgorithms 331