Behavioral Modeling and Linearization of RF Power Amplifiers

379 Pages·2014·17.14 MB·English

by  John Wood

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Behavioral Modeling and
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Wireless voice and data communications have made great improvements, with
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connectivity now virtually ubiquitous. Users are demanding essentially perfect n
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transmission and reception of voice and data. The infrastructure that supports e
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this wide connectivity and nearly error-free delivery of information is complex, a
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costly, and continually being improved. r
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This resource describes the mathematical methods and practical implementations r
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of linearization techniques for RF power amplifiers for mobile communications. ta linearization
This includes a review of RF power amplifier design for high efficiency operation. il
Readers are also provided with mathematical approaches to modeling nonlinear o M
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dynamical systems, which can be applied in the context of modeling the PA for
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identification in a pre-distortion system. This book presents typical approaches to o
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linearization and digital pre-distortion that are used in practice. f
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Contents Overview: Introduction; Models, Modeling, and Simulation; Linear fi aMPlifiers
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Systems and Identification; Modeling PA Nonlinearities; Memory Effects;
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Nonlinear Dynamical Models; Digital Pre-Distortion; Crest Factor Reduction of
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Digital Communication Signals; RF Pre-Distortion; Frequency Domain Models a
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John Wood is a senior professional in the microwave industry, and an ed
John Wood
acknowledged expert on behavioral modeling and linearization of RF and r
Microwave power amplifiers. He earned his Ph.D. in electrical and electronic a
engineering from the University of Leeds, UK. M
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Include bar code i
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ISBN 13: 978-1-60807-120-3 e
ISBN 10: 1-60807-120-0 r
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BOSTON LONDON
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Behavioral Modeling and Linearization
of RF Power Amplifi ers
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Behavioral Modeling and Linearization
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John Wood
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Cover design by Adam Renvoize
ISBN 13: 978-1-60807-120-3
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Contents
Preface xiii
Chapter1 Introduction 1
1.1 ABriefHistoryofMobileWirelessCommunications 3
1.1.1 IntroductiontoDigitalModulation 6
1.1.2 FiltersforDigitalCommunicationSystems 14
1.1.3 MeasuresforDigitalCommunicationSignals 16
1.2 RFPowerAmplifiers:LinearityandEfficiency 20
1.2.1 HarmonicLoading 23
1.2.2 TheDohertyAmplifier 31
1.2.3 ThePolarAmplifier 34
1.2.4 OtherHigh-EfficiencyPATechniques 38
1.2.5 High-EfficiencyPASummary 38
1.3 LinearizationTechniquesforRFPAs 39
1.3.1 Feedback 39
1.3.2 PolarFeedback 40
1.3.3 CartesianFeedback 41
1.3.4 Feedforward 42
1.3.5 Pre-distortion 43
1.4 BehavioralModeling 47
1.5 ConcludingRemarksandBibliography 50
References 52
Chapter2 Models,Modeling,andSimulation 53
2.1 APerspective 54
2.2 TheModel 54
vii
viii BehavioralModelingandLinearizationofRFPowerAmplifiers
2.2.1 Data-orMeasurement-BasedModels 59
2.2.2 PhysicallyBasedModels 62
2.2.3 EquivalentCircuitModels 67
2.2.4 CompactModels 69
2.2.5 BehavioralModels 69
2.3 Modeling 72
2.3.1 FunctionFittingandFunctionApproximation 75
2.3.2 ModelValidation 80
2.4 Simulation 81
2.4.1 CircuitSimulation 81
2.4.2 ElectromagneticSimulation 82
2.4.3 DevicePhysicalSimulation 83
2.4.4 ThermalSimulation 85
2.4.5 SystemSimulation 87
2.5 ConcludingRemarks 87
References 87
Chapter3 LinearSystemsandIdentification 91
3.1 AReviewofLinearSystemProperties 92
3.1.1 InstantaneousandDynamicSystems 93
3.1.2 TimeDomainorFrequencyDomain? 94
3.1.3 ConvolutionIntegralandImpulseResponse 95
3.1.4 StateSpaceRepresentation 96
3.2 DiscreteTimeRepresentation 99
3.3 GeneralTransferFunctionModels 101
3.3.1 NoiseandDisturbanceSignals 101
3.3.2 GeneralModelStructure 103
3.4 ModelBuilding 105
3.4.1 BasisFunctions 105
3.4.2 LeastSquaresAlgorithm 106
3.4.3 ErrorMeasures 106
3.5 SystemIdentification 107
3.5.1 NonlinearSystemIdentification 108
Bibliography 110
Chapter4 ModelingPANonlinearities 111
4.1 GainCompressioninthePA 112
4.1.1 ModelingtheCWInput-OutputRelationship 113
4.2 PhaseCharacteristic:AM-to-PMBehavior 121
Contents ix
4.3 Two-ToneAnalysis 125
4.3.1 CommentsontheTwo-ToneAnalysis 131
4.3.2 DoWeNeedtheEven-DegreeTermsinthePolyno-
mial? 131
4.4 SummaryRemarks 133
References 134
Chapter5 MemoryEffects 135
5.1 Introduction 135
5.1.1 Short-TermMemoryEffects 137
5.1.2 Long-TermMemoryEffects 138
5.2 MatchingNetworks 139
5.3 ChargeStorageintheTransistor 142
5.4 ThermalEffects 145
5.5 TrappingofCharge 148
5.6 BiasandSupplyLines 150
5.7 IncludingMemoryEffectsintheNonlinearModel 152
References 153
Chapter6 NonlinearDynamicalModels 155
6.1 IntroductiontoVolterraSeries 156
6.1.1 VolterraSeriesasaDevelopmentofaTaylorSeries 158
6.1.2 VolterraSeriesasaDevelopmentofaLinearSystem 159
6.1.3 VolterraSeriesfromtheCascadeofLinearandNon-
linearComponents 160
6.1.4 TheHigher-OrderKernels 161
6.1.5 Discrete-TimeExpressionsforVolterraSeries 164
6.1.6 SomeRemarksonVolterraSeriesModelingofPower
Amplifiers 165
6.2 SomeExamplesofVolterraModelsforPower
Amplifiers 168
6.2.1 ANonlinearFeedbackModel 168
6.2.2 WienerandHammersteinModels 169
6.2.3 MemoryPolynomialModel 171
6.2.4 ParallelCascade 173
6.2.5 OrthogonalBasisFunctions 174
6.3 AdvancedVolterraSeriesModels 178
6.3.1 DynamicDeviationModel 180