Digital Communications 4th editions
1
Introduction
1-1 Elements of
a Digital Communication System
1-2 Communication
Channels ' and Their Characteristics
1-3
Mathematical Models for Communication Channels
1-4 A
Historical Perspective in tbe Development of Digital Communications
1-5 Overview of
the Book
1-6
Bibliograpbical Noles and References
2
Probability and Stochastic Processes
2-1 Probability
2-1-1 Random
Variables, Probability Distributions.
and Probability
Densities
2-1-2 Functions
of Random Variables
2-1-3
Statistical Averages of Random Variables
2-1-4 Some
Useful Probability Distributions
2-1-5 Upper bounds
on the
Tail
Probability
2-1-6 Sums of
Random Variables and the Central limit
2-2 Stocbastic
Processes 62
2-2-1
Statistical Averages 64
2-2-2 Power Density
Spectrum 67
2-2-3 Response of a linear
Time-Invariant System to a Random Input Signal 68
2-2-4 Sampling
Theorem for Band-Limited Stochastic Processes 72
2-2-5
Discrete-Tune Stochastic Signals and Systems 74
2-2-6
Cyclostationary Processes
75
2-3
Bibliograpbical Notes and
References
77
Problems 77
3 Source Coding 82
3-1 Mathematical
Models for Information 82
3-2 A
Logarithmic Measure of Information 84
3-2-1 Average
Mutual Information and Entropy 87
3-2-2
Information Measures for Continuous Random Variables 91
3-3 Coding for
Discrete Sources 93
3-3-1 Coding for
Discrete Memoryless Sources 94
3-3-2 Discrete
Stationary Sources 103
3-3-3 The
Lempel-Ziv Algorithm 106
3-4 Coding for
Analog Sources-Optimum Quantization 108
3-4-1
Rate-Distortion Function 108
3-4-2 Scalar
Quantization 113
3-4-3 Vector
Quantization 118
3-5 Coding
Techniques for Analog Sources 125
3-5-1 Temporal
Waveform Coding 125
3-5-2 Spectral
Waveform Coding 136
3-5-3
Model-Based Source Coding 138
3-6
Bibliographical Notes and Refmmces 144
Problems 144
4 Characterization
of Communication Signals
and Systems 152
4-1
Representation of Bandpass Signals and Systems 152
4-1-1
Representation of Bandpass Signals 153
4-1-2
Representation of Unear Bandpass Systems 157
4-1-3 Response
of a Bandpass System to a Bandpass Signal 157
4-1-4
Representation of Bandpass Stationary Stochastic Processes 159
4-2 Signal Space
Representation 163
4-2-1 Vector
Space Concepts 163
4-2-2 Signal
Space Concepts 165
4-2-3 Orthogonal
Expansions of Signals 165
4-3 Represen
tation of Digitally Modulated Signals 173
4-3-1 Memoryless
Modulation Methods 174
4-3-2 Linear
Modulation With Memory 186
4-3-3 Nonlinear
Modulation Metbods with Memory 190
4-4 Spectral
Cbaracteristics of Digitally Modulated Signals 203
4-4-1 Power
Specua of Linearly Modulated Si&nals 204
4-4-2 Power
Spectra of CPFSK and CPM Signals 209
4-4-3 Power
Spe,<,ra of Modulated Signals with Memory 220
4-5
Bibliograpbical Notes and Referen~ 223
Problems 224
5 Optimum
Receivers for the Additive White Gaussian Noise Channel 233
5-1 Optimum
Receiver for Signals (Jorrupted by A WGN 233
5-1-1
Correlation Demodulator 234
5-1-2
Matched-Filter Demodulator 238
5-1-3 The Optimum
Detector 244
5-1-4 The
Maximum-Likelihood Sequence Detector 249
5-1-5 A Symbol-by-Symbol
MAP Detector for Signals with Memory 254
5-2 Performance of
the Optimum Receiver for Memoryless Modulation 257
5-2-1 Probability of
Error for Binary Modulation 257
5-2-2 Probability of
Error for M-ary Orthogonal Signals 260
5-2-3 Probability of
Error for M
-ary
Biorthogonal Signals 264
5-2-4 Probability of
Error for Simplex Signals 266
5-2-5 Probability of
Error for M-ary Binary-Coded Signals 266
5-2-6 Probability of
Error for M
-ary
PAM 267
5-2-7 Probability of
Error for M
-ary
PSK 269
5-2-8 Dilferelltial
PSK (DPSK) and its Perfonnance 274
5-2-9 Probability of
Error for QAM 278
5-2-10 Comparison of
Digital Modulation Methods 282
5-3 Optimum Receiver
for CPM Signals 284
5-3-] Optimum
Demodulation and Detection of CPM 285
5-3-2 Performance of
CfM Signals 2'lO
5-3-3 Symbol-by-Symbol
Detection of CPM Signals 296
5-4 Optimum Receiver
for Signals with Random Phase in A WGN Channel 301
5-4-1 Optimum
Receivedor Binary Signals 302
5-4-2 Optimum
Receiver>for M-ary Orthogonal Signals 308
5-4-3 Probability of
Error for Envelope Detection of M –ary Orthogonal Signals 308
5-4-4 Probability of
Error for Envelope Detection of Correlated Binary Signals 312
5-5 Regenerative
Repeaters and Link Budget Analysis 3!3
5-5-] Regenerative
Repeaters 314
5-5-2 Communication
Link Budget Analysis 316
5-6 Bibliographical
Notes and References 319
Problems 320
6
Carrier and Symbol Synchronization 333
6-1 Signal Parameter
Estimation 333
6-)-1 The Likelihood
Function 335
6-1-2 Carrier Recovery
and Symbol Synchronization
in Signal
Demodulation 336
6-2 Carrier Phase
Estimation 337
6-2-1 Maximum-Likelihood
carrier Phase ESlimation 339
6-2-2 The
Phase-Lock.ed Loop 341
6-2-3 Effect of
Additive Noise on the Phase Estimate 343
6-2-4 Decision-Directed
Loops 347
6-2-5 Non-Decision-Directed
Loops
350
6-3 Symbol Timing
Estimation 358
6-3-1 Maximum-Likelihood
TIming Estimation 359
6-3-2 Non-Decision-Directed
Timing Estimation 361
6-4 Joint Estimation
of Carrier Phase and Symbol Timing
6-5 Performance
Characteristics of ML Estimators
6-6
Bibliographical Notes and References
Problems
7 Channel
Capacity and Coding 374
7-1 Channel Models
and Channel Capacity 375
7-1-1 Channel
Models 375
7-1-2 Channel
Capacity 380
7-1-3 Achieving
Channel Capacity with Orthogonal Signals 387
7-\-4 Channel
Reliability Functions 389
7-2 Random Selection
of Codes 390
7-2-1 Random Coding
Based on M-ary Binary-Coded Signals 390
7-2-2 Random Coding
Based on
M-ary
Multiamplitude
Signals 397
7-2-3 Comparison of R:f with the
Capacity of the AWGN
Channel 399
7-3 Communication
System Design Based on the Cutoff Rate 400
7-4
Bibliographical NOles and References 406
Problems 406
8 Block and
Convolutional Channel Codes 413
8-1 Linear Block
Codes 413
8-1-1 The
Generator Matrix and the Parity Check Matrix 4\7
8-1-2 Some SpecifiC Linear Block
Codes 421
8-\-3 . Cyclic Codes 423
8-1-4 OpthlUm
Soft-Decision Decoding of Linear Block. Codes 436
8-1-5
Hard-Decision Decoding 445
8-1-6 Comparison of
Performance between Hard-Decision and
Soft-Decision
Decoding 456
8-1-7 Bounds on
Minimum Distance of
Linear
Block Codes 461
8-1-8 Nonbinary Block
Codes and Concatenated Block. Codes 464
8-1-9 Imerleaving 01 Coded Data for
Channels with Burst
Errors 468
8-2
Convolutional Codes 470
8-2-1 The
Transfer Function of a Convolutional Code 477
8-2-2 Optimum Decoding
of Convohllional Codes-
The Viterbi
Algorithm 483
8-2-3 Probability of
Error for
Soft-Decision
Decoding 486
8-2-4 Probability of
Error for
Hard-Decision
Decoding 489
8-2-5 Distance
Properties of
Binary
Convolutional Codes 492
8-2-6 Nonbinary
Dual-k Codes and Concatenated Codes 492
8-2-7 Otber Decoding
Algorithms for Convolutional C~ SOD
8-2-8 Practical
Considerations in the
Ajlpliallion
of
Convolutional
Codes 506
8-3 Coded
Modulation for Bandwidth-Constrained Channels 511
8-4 Bibliographical
Note, and References 526
Problems 528
9 Signal Design
for Band-Limited Channels 534
9-1 Characterization
of Band-Umited Channels 534
9-2 Signal Design
for Band-Limited Channels 540
9-2-1 Design of
Band-Umited Signals for No Intersymbol
Interference-The
Nyquist Criterion 542
9-2-2 Design of Band-Limited
SignaIs with Controlled ISIPartial-
Response Signals
548
9-2-3 Data Detettion
for Controlled lSI 551
9-2-4 Signal Design
for Channels with Distortion 557
9-3 Probability of
Error in Detection of PAM 561
9-3-1 Probability of
Error for Detettion of
PAM
with Zero lSI 561
9-3-2 Probability of
Error for Detettion of Partial-Response
Signals 562
9-3-3 Probability of
Error for Optimum Signals in Channel
with Distortion 565
9-4 Modulation Codes
for Spectrum Shaping 566
9-5 Bibliographical
Notes and References 576
Problems 576
19
Communication through Band-Limited Linear
Filter Channels
583
10-1 Optimum Receiver
for Channels with lSI and A WON 584
10-1-1 Optimum
Maximum-Likelihood Receiver 584
10-1-2 A Discrete-Time
Model for a Channel with lSI 586
10-1-3 The Viterbi
Algorithm for the DiscRte-Tune White
Noise Filter
Model 589
10-1-4 Perforrnaru::e
of MLSE for Channels with lSI 593
10-2 Linear
Equalization 601
10-2-1 Peak Distortion
Criterion 602
\0-2-2 Mean Square
Error (MSE) Criterion 607
10-2-3 Performaace
Characteristics of the MSE Equalizer 612
10-2-4 Fractionally
Spaced Equalizer 617
10-3 Decision-Feedback
Equalization 621
10-3-1 Coe8icient
Optimization 621
10-3-2 Performance
Characteristics of DFE 622
10-3-3 Predittive
Decision-Feedback Equalizer 626
10-4 Bibliograpbical
Notes and References 628
Problems 628
11 Adaptive·
Equalization 636
11-1 Adaptive Unear
Equalizer 636
11-1-1 The Zero-Forcing
Algorithm 637
11-1-2 The LMS aJaorithm 639
11-1-3 Converpnce Propertiea of the LMS Algorithm 642
11-1-4 Excess MSE Due
to Noisy Gradient Eatimates 644
11-1-S Baseband lIOd
Passband Unear
Equalizers
648
11-2 Adaptive Decision-Feedback
Equalizer 649
11-2-1 Adaptive
Equalization of
Trellia-Coded
Signals 6SO
Jl-3 An
Adaptive Channel Estimator for ML Sequence Detection 652
11-4 Recursive
Least-Squares Algorithms for Adaptive Equalization 654
11-4-1
Recursive Least-Squares (Kalman) Algorithm 656
11-4-2 Linear
Prediction and Ihe Lattice Filter 660
11-5
Self-Recovering (Blind) Equalization 664
11-5-1 Blind
Equalization Based on Maximum-Likelihood
Criterion 664
11-5-2 Stochastic
Gradient Algorithms 668
11-5-3 Blind
Equalization Algorithms Based on Secondand
Higher-Order
Signal Statistics 673
11-6 Bihliographical
Nores
and
References 675
Problems 676
12
Multichannel and Multicarrier Systems 6SO
12-1 Multichannel
Dig.tal Communication in AWGN Channels 680
12-1-1 Binary Signals 682
12-1-2 M-ory Orthogonal
Signals 684
12-2
MulticaTrier Communications 686
12-2-i Capacity of a
Non-Ideal Linear Filter Channel 687
12-2-2 An FFf-Based
Multicarrie, System 689
12-3
Bibiliographical Notes and References 692
Problems &93
13
Spread Spectrum Signals for Digital Communications 695
13-1 f..lodel of
Spread Spectrum Digital Communication System &97
13-2 Direct Sequence
Spread Spectrum Signals 698
13-2-1 Error
Rate Performance of Ihe Decoder 702
13-2-2 Some
Applications of OS Spread Spectrum Signals 712
13-2-3 Effect of
Pulsed Interference on OS Spread Spectmm
Systems 717
13-2-4 Generation of
PN Sequences 724
13-3 Frequcncy-Hoppped
Spread Spectrum Signals 729
13-3-1 Performance of
FH Spread Spectrum Signals in AWGN
Channel 732
13-3-2 Performance of
FH Spread Spectrum Signals in Partial-
Band
Interference 734
U-3-3 A COMA System
Based on FH Spread Spectrum Signals 741
13-4 Other Types of
Spread Spectrum Signals 743
13-5 Synchronilation
of Spread Spectrum Signals 744
13-6 Bibliographical
Notes and References 752
Probiems 753
14 Digital
Communication through Fading
Multipath
Channels
14-1
Characterization of Fading Multipath Channels
14-1-\ Channel
Correlation Functions and Power Spectra
14-/-2
Slalislieal Models for Fading Channels
14-2 The Ellect of Characteristics
on the Choice
of a Channel
Model
14-3
Frequency-Nonse1ective. Slowly Fading Channel
14-4 Diversity
Techniques for Fading Multipath Channels
14-4-1 Binary
Signals
14-4-2
Mu1tiphase Signals
14-4-3 M-ary
Orthogonal Signals
14-5 Digital
Signaling over a
Frequency-Selective,
Slowly Fading
Channel
14-5-1 A
Tapped-Delay-Line Channel Model
14-5-2 The RAKE
Demodulator
14-5-3
Performance of
RAKE Receiver
14-6 Coded
Waveforms (or Fading Channels
14-6-1
Probability of Error for
Soft-Decision
Decoding of Linear
Binary Block
Codes
14-6-2
Probability of Error for Hard-Decision Decoding of
Linear Binary
Block Codes
14-6-3 Upper
Bounds on the Performance of Convolutional
Codes for a
Raleigh Fading Channel
14-6-4 Usc of
Constant-Weight Codes and Concatenated Code.
for a Fading
Channel
14-6-5 System
Design Based on the Cutoll Rate
14-6-6
Trellis-Coded Modulation
14-7
Bibliographical Notes and References
Problems
15 Multiuser
Communications
15-1
Introduction to Multiple Access Techniques
15-2 Capacity of Mulliple Access
Methods
15-3
Code-Division Multiple Access
15-3-1 CDMA
Signal and Channel Models
15-3-2 The
Optimum Receiver
15-3-3
Suboptimum Detectors
15-3-4 Performance
Characteristics of Detectors
15-4 Random
Access Methods
15-4-1 ALOHA
System and Protocols
15-4-2 Carrier Sense Systems and
Protocols
15-5
Bibliographical Notes and References
Problems
AppeDdis: A
AppeDdis: B
The
Levinson-Durbin Algorithm
Error Probability
for Multichannel
Binary Signals
Appendix
C Error
Probabilities for Adaptive Reception
of M -phase
Signals
C-l
Mathematical Model for an M -phase Signaling
Communications
System
C-2
Characteristic Function and Probability Density
Function of the
Phase e
C-3 Error
Probabilities for Slowly Rayleigh Fading
Channels
C-4 Error
Probabilities for Time-Invariant and Ricean
Fading Channels
893
Appendix
D Square-Root
Factorization sen
References
and Bibliography 899
Index 917
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