《数字通信 英文版 第3版》求取 ⇩

1 Introduction1

1-1 Elements of a Digital Communication System1

1-2 Communication Channels and Their Characteristics3

1-3 Mathematical Models for Communication Channels11

1-4 A Historical Perspective in the Development of Digital Communications13

1-5 Overview of the Book16

1-6 Bibliographical Notes and References16

2 Probability and Stochastic Processes17

2-1 Probability17

2-1-1 Random Variables, Probability Distributions, and Probability Densities22

2-1-2 Functions of Random Variables28

2-1-3 Statistical Averages of Random Variables33

2-1-4 Some Useful Probability Distributions37

2-1-5 Upper bounds on the Tail Probability53

2-1-6 Sums of Random Variables and the Central Limit Theorem58

2-2 Stochastic Processes62

2-2-1 Statistical Averages64

2-2-2 Power Density Spectrum67

2-2-3 Response of a Linear Time-Invariant System to a Random Input Signal68

2-2-4 Sampling Theorem for Band-Limited Stochastic Processes72

2-2-5 Discrete-Time Stochastic Signals and Systems74

2-2-6 Cyclostationary Processes75

2-3 Bibliographical Notes and References77

Problems77

3 Source Coding82

3-1 Mathematical Models for Information82

3-2 A Logarithmic Measure of Information84

3-2-1 Average Mutual Information and Entropy87

3-2-2 Information Measures for Continuous Random Variables91

3-3 Coding for Discrete Sources93

3-3-1 Coding for Discrete Memoryless Sources94

3-3-2 Discrete Stationary Sources103

3-3-3 The Lemple-Ziv Algorithm106

3-4-1 Rate-Distortion Function108

3-4 Coding for Analog Sources-Optimum Quantization108

3-4-2 Scalar Quantization113

3-4-3 Vector Quantization118

3-5 Coding Techniques for Analog Sources125

3-5-1 Temporal Waveform Coding125

3-5-2 Spectral Waveform Coding136

3-5-3 Model-Based Source Coding138

Problems144

3-6 Bibliographical Notes and References144

4 Characterization of Communication Signals and Systems152

4-1 Representation of Bandpass Signals and Systems152

4-1-1 Representation of Bandpass Signals153

4-1-2 Representation of Linear Bandpass Systems157

4-1-3 Response of a Bandpass System to a Bandpass Signal157

4-1-4 Representation of Bandpass Stationary Stochastic Processes159

4-2-1 Vector Space Concepts163

4-2 Signal Space Representation163

4-2-2 Signal Space Concepts165

4-2-3 Orthogonal Expansions of Signals165

4-3 Representation of Digitally Modulated Signals173

4-3-1 Memoryless Modulation Methods174

4-3-2 Linear Modulation with Memory186

4-3-3 Nonlinear Modulation Methods with Memory190

4-4 Spectral Characteristics of Digitally Modulated Signals203

4-4-1 Power Spectra of Linearly Modulated Signals204

4-4-2 Power Spectra of CPFSK and CPM Signals209

4-4-3 Power Spectra of Modulated Signals with Memory220

4-5 Bibliographical Notes and References223

Problems224

5 Optimum Receivers for the Additive White Gaussian Noise Channel233

5-1 Optimum Receiver for Signals Corrupted by AWGN233

5-1-1 Correlation Demodulator234

5-1-2 Matched-Filter Demodulator238

5-1-3 The Optimum Detector244

5-1-4 The Maximum-Likelihood Sequence Detector249

5-1-5 A Symbol-by-Symbol MAP Detector for Signals with Memory254

5-2 Performance of the Optimum Receiver for Memoryless Modulation257

5-2-1 Probability of Error for Binary Modulation257

5-2-2 Probability of Error for M-ary Orthogonal Signals260

5-2-3 Probability of Error for M-ary Biorthogonal Signals264

5-2-4 Probability of Error for Simplex Signals266

5-2-5 Probability of Error for M-ary Binary-Coded Signals266

5-2-6 Probability of Error for M-ary PAM267

5-2-7 Probability of Error for M-ary PSK269

5-2-8 Differential PSK(DPSK)and its performance274

5-2-9 Probability of Error for QAM278

5-2-10 Comparison of Digital Modulation Methods282

5-3 Optimum Receiver for CPM Signals284

5-3-1 Optimum Demodulation and Detection of CPM285

5-3-2 Performance of CPM Signals290

5-3-3 Symbol-by Symbol Detection of CPM Signals296

5-4 Optimum Receiver for Signals with Random Phase in AWGN Channel301

5-4-1 Optimum Receiver for Binary Signals302

5-4-2 Optimum Receiver for M-ary Orthogonal Signals308

5-4-3 Probability of Error for Envelope Detection of M-ary Orthogonal Signals308

5-4-4 Probability of Error for Envelope Detection of Correlated Binary Signals312

5-5 Regenerative Repeaters and Link Budget Analysis313

5-5-1 Regenerative Repeaters314

5-5-2 Communication Link Budget Analysis316

5-6 Bibliographical Notes and References319

Problems320

6 Carrier and Symbol Synchronization333

6-1 Signal Parameter Estimation333

6-1-1 The Likelihood Function335

6-1-2 Carrier Recovery and Symbol Synchronization in Signal Demodulation336

6-2 Carrier Phase Estimation337

6-2-1 Maximum-Likelihood Carrier Phase Estimation339

6-2-2 The Phase-locked Loop341

6-2-3 Effect of Additive Noise on the Phase Estimate343

6-2-4 Decision-Directed Loops347

6-2-5 Non-Decision-Directed Loops350

6-3 Symbol Timing Estimation358

6-3-1 Maximum-Likelihod Timing Estimation359

6-3-1 Non-Decision-Directed Timing Estimation361

6-4 Joint Estimation of Carrier Phase and Symbol Timing365

6-5 Performance Characteristics of ML Estimators367

6-6 Bibliographical Notes and References370

Problems371

7 Channel Capacity and Coding374

7-1 Channel Models and Channel Capacity375

7-1-1 Channel Models375

7-1-2 Channel Capacity380

7-1-3 Achieving Channel Capacity with Orthogonal Signals387

7-1-4 Channel Reliability Functions389

7-2 Random Selection of Codes390

7-2-1 Random Coding Based on M-ary Binary-Coded Signals390

7-2-2 Random Coding Based on M-ary Multiamplitude Signals397

7-2-3 Comparison of ? with the Capacity of the A WGN Channle399

7-3 Communication System Design Based on the Cutoff Rate400

7-4 Bibliographical Notes and References406

Problems406

8 Block and Convolutional Channel Codes413

8-1 Linear Block Codes413

8-1-1 The Generator Matrix and the Parity Check Matrix417

8-1-2 Some Specific Linear Block Codes421

8-1-3 Cyclic Codes423

8-1-4 Optimum Soft-Decision Decoding of Linear Block Codes436

8-1-5 Hard-Decision Decoding445

8-1-6 Comparison of Performance between Hard-Decision and Soft-Decision Decoding456

8-1-7 Bounds on Minimum Distance of Linear Block Codes461

8-1-8 Nonbinary Block Codes and Concatenated Block Codes464

8-1-9 Interleaving of Coded Data for Channels with Burst Errors468

8-2 Convolutional Codes470

8-2-1 The Transfer Function of a Convolutional Code477

8-2-2 Optimum Decoding of Convolutional Codes—The Viterbi Algorithm483

8-2-3 Probability of Error for Soft-Decision Decoding486

8-2-4 Probability of Error for Hard-Decision Decoding489

8-2-5 Distance Properties of Binary Convolutional Codes492

8-2-6 Nonbinary Dual-k Codes and Concatenated Codes492

8-2-7 Other Decoding Algorithms for Convolutional Codes500

8-2-8 Practical Considerations in the Application of Convolutional Codes506

8-3 Coded Modulation for Bandwidth-Constrained Channels511

8-4 Bibliographical Notes and References526

Problems528

9-1 Characterization of Band-Limited Channels534

9 Signal Design for Band-Limited Channels534

9-2 Signal Design for Band-Limited Channels540

9-2-1 Design of Band-Limited Signals for No Intersymbol Interference-The Nyquist Criterion542

9-2-2 Design of Band-Limited Sygnals with Controlled ISI-Partial-Response Signals548

9-2-3 Data Detection for Controlled ISI551

9-2-4 Signal Design for Channels with Distortion557

9-3 Probability of Error in Detection of PAM561

9-3-1 Probability of Error for Detection of PAM with Zero ISI561

9-3-2 Probability of Error for Detection of Partial-Response Signals562

9-3-3 Probability of Error for Optimum Signals in Channel with Distortion565

9-4 Modulation Codes for Spectrum Shaping566

9-5 Bibliographical Notes and References576

Problems576

10 Communication through Band-Limited Linear Filter Channels583

10-1 Optimum Receiver for Channels with ISI and AWGN584

10-1-1 Optimum Maximum-Likelihood Receiver584

10-1-2 A Discrete-Time Model for a Channel with ISI586

10-1-3 The Viterbi Algorithm for the Discrete-Time White Noise Filter Model589

10-1-4 Performance of MLSE for Channels with ISI593

10-2 Linear Equalization601

10-2-1 Peak Distortion Criterion602

10-2-2 Mean Square Error (MSE) Criterion607

10-2-3 Performance Characteristics of the MSE Equalizer612

10-2-4 Fractionally Spaced Equalizer617

10-3 Decision-Feedback Equalization621

10-3-1 Coefficient Optimization621

10-3-2 Performance Characteristics of DFE622

10-3-3 Predictive Decision-Feedback Equalizer626

10-4 Bibliographical Notes and References628

Problems628

11 Adaptive Equalization636

11-1 Adaptive Linear Equalizer636

11-1-1 The Zero-Forcing Algorithm637

11-1-2 The LMS algorithm639

11-1-3 Convergence Properties of the LMS Algorithm642

11-1-4 Excess MSE Due to Noisy Gradient Estimates644

11-1-5 Baseband and Passband Linear Equalizers648

11-2 Adaptive Decision-Feedback Equalizer649

11-2-1 Adaptive Equalization of Trellis-Coded Signals650

11-3 An Adaptive Channel Estimator for ML Sequence Detection652

11-4 Recursive Least-Squares Algorithms for Adaptive Equalization654

11-4-1 Recursive Least-Squares (Kalman) Algorithm656

11-4-2 Linear Prediction and the Lattice Filter660

11-5 Self-Recovering (Blind) Equalization664

11-5-1 Blind Equalization Based on Maximum-Likelihood Criterion664

11-5-2 Stochastic Gradient Algorithms668

11-5-3 Blind Equalization Algorithms Based on Second-and Higher-Order Signal Statistics673

11-6 Bibliographical Notes and References675

Problems676

12 Multichannel and Multicarrier Systems680

12-1 Multichannel Digital Communication in AWGN Channels680

12-1-1 Binary Signals682

12-1-2 M-ary Orthogonal Signals684

12-2 Multicarrier Communications686

12-2-1 Capacity of a Non-Ideal Linear Filter Channel687

12-2-2 An FFT-Based Multicarrier System689

12-3 Bibiliographical Notes and References692

Problems693

13 Spread Spectrum Signals for Digital Communications695

13-1 Model of Spread Spectrum Digital Communication System697

13-2 Direct Sequence Spread Spectrum Signals698

13-2-1 Error Rate Performance of the Decoder702

13-2-2 Some Applications of DS Spread Spectrum Signals712

13-2-3 Effect of Pulsed Interference on DS Spread Spectrum Systems717

13-2-4 Generation of PN Sequences724

13-3 Frequency-Hopped Spread Spectrum Signals729

13-3-1 Performance of FH Spread Spectrum Signals in AWGN Channel732

13-3-2 Performance of FH Spread Spectrum Signals in Partial-Band Interference734

13-3-3 A CDMA System Based on FH Spread Spectrum Signals741

13-4 Other Types of Spread Spectrum Signals743

13-5 Synchronization of Spread Spectrum Signals744

13-6 Bibliographical Notes and References752

Problems753

14 Digital Communication through Fading Multipath Channds758

14-1 Characterization of Fading Multipath Channels759

14-1-1 Channel Correlation Functions and Power Spectra762

14-1-2 Statistical Models for Fading Channels767

14-2 The Effect of Characteristics on the Choice of a Channel Model770

14-3 Frequency-Nonselective, Slowly Fading Channel772

14-4 Diversity Techniques for Fading Multipath Channels777

14-4-1 Binary Signals778

14-4-2 Multiphase Signals785

14-4-3 M-ary Orthogonal Signals787

14-5 Digital Signaling over a Frequency-Selective, Slowly Fading Channel795

14-5-1 A Tapped-Delay-Line Channel Model795

14-5-2 The RAKE Demodulator797

14-5-3 Performance of RAKE Receiver798

14-6 Coded Waveforms for Fading Channels806

14-6-1 Probability of Error for Soft-Decision Decoding of Linear Binary Block Codes808

14-6-2 Probability of Error for Hard-Decision Decoding of Linear Binary Block Codes811

14-6-3 Upper Bounds on the Performance of Convolutional Codes for a Raleigh Fading Channel811

14-6-4 Usc of Constant-Weight Codes and Concatenated Codes for a Fading Channel814

14-6-5 System Design Based on the Cutoff Rate825

14-6-6 Trellis-Coded Modulation830

14-7 Bibliographical Notes and References832

Problems833

15 Multiuser Communications840

15-1 Introduction to Multiple Access Techniques840

15-2 Capacity of Multiple Access Methods843

15-3 Code-Division Multiple Access849

15-3-1 CDMA Signal and Channel Models849

15-3-2 The Optimum Receiver851

15-3-3 Suboptimum Detectors854

15-3-4 Performance Characteristics of Detectors859

15-4 Random Access Methods862

15-4-1 ALOHA System and Protocols863

15-4-2 Carrier Sense Systems and Protocols867

15-5 Bibliographical Notes and References872

Problems873

Appendix A The Levinson-Durbin Algorithm879

Appendix B Error Probability for Multichannel Binary Signals882

Appendix C Error Probabilities for Adaptive Reception of M-phase Signals887

C-1 Mathematical Model for an M-phase Signaling Communications System887

C-2 Characteristic Function and Probability Denstiy Function of the Phase?889

C-3 Error Probabilities for Slowly Rayleigh Fading Channels891

C-4 Error Probabilities for Time-Invariant and Ricean Fading Channels893

Appendix D Square-Root Factorization897

References and Bibliography899

Index917