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Title:
Trellis and turbo coding
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Publication Information:
Piscataway, NJ : IEEE Press, 2004
ISBN:
9780471227557
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30000003593484 TK5102.96 S33 2004 Open Access Book Book
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30000010150306 TK5102.96 S33 2004 Open Access Book Book
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Summary

Summary

Trellis and turbo coding are used to compress and clean communications signals to allow greater bandwidth and clarity Presents the basics, theory, and applications of these techniques with a focus on potential standard state-of-the art methods in the future Provides a classic basis for anyone who works in the area of digital communications

A Wiley-IEEE Press Publication


Author Notes

Christian B. Schlegel, PhD, is iCORE Professor of Digital Communications at the University of Alberta, Canada
Lance C. Perez, PhD, is currently a member of the faculty in the Department of Electrical Engineering at the University of Nebraska in Lincoln, Nebraska


Table of Contents

Prefacep. xiii
1 Introductionp. 1
1.1 Modern Digital Communicationsp. 1
1.2 The Rise of Digital Communicationsp. 2
1.3 Communication Systemsp. 3
1.4 Error Control Codingp. 5
1.5 Bandwidth, Power, and Complexityp. 10
1.6 A Brief History--The Drive Toward Capacityp. 18
Bibliographyp. 20
2 Communication Theory Basicsp. 25
2.1 The Probabilistic Viewpointp. 25
2.2 Vector Communication Channelsp. 26
2.3 Optimum Receiversp. 29
2.4 Matched Filtersp. 31
2.5 Message Sequencesp. 32
2.6 The Complex Equivalent Baseband Modelp. 36
2.7 Spectral Behaviorp. 40
2.8 Multiple Antenna Channels (MIMO Channels)p. 42
Appendix 2.Ap. 47
Bibliographyp. 49
3 Trellis-Coded Modulationp. 51
3.1 An Introductory Examplep. 51
3.2 Group-Trellis Codesp. 55
3.3 The Mapping Functionp. 57
3.4 Construction of Codesp. 60
3.5 Latticesp. 65
3.6 Lattice Formulation of Trellis Codesp. 71
3.7 Rotational Invariancep. 77
3.8 V.fastp. 83
3.9 Geometric Uniformityp. 85
3.10 Historical Notesp. 92
Bibliographyp. 92
4 Convolutional Codesp. 95
4.1 Convolutional Codes as Binary Trellis Codesp. 95
4.2 Codes and Encodersp. 97
4.3 Fundamental Theorems from Basic Algebrap. 103
4.4 Systematic Encodersp. 113
4.5 Systematic Feedback and Recursive Systematic Encoder Realizationsp. 115
4.6 Maximum Free-Distance Convolutional Codesp. 117
Appendix 4.Ap. 121
Bibliographyp. 122
5 Link to Block Codesp. 125
5.1 Preliminariesp. 125
5.2 Block Code Primerp. 126
5.3 Trellis Description of Block Codesp. 127
5.4 Minimal Trellisesp. 128
5.5 Minimum-Span Generator Matricesp. 133
5.6 Construction of the PC Trellisp. 136
5.7 Tail-Biting Trellisesp. 138
5.8 The Squaring Construction and the Trellis of Latticesp. 141
5.9 The Construction of Reed-Muller Codesp. 147
5.10 A Decoding Examplep. 149
Bibliographyp. 152
6 Performance Boundsp. 155
6.1 Error Analysisp. 155
6.2 The Error Event Probabilityp. 155
6.3 Finite-State Machine Description of Error Eventsp. 160
6.4 The Transfer Function Boundp. 163
6.5 Reduction Theoremsp. 166
6.6 Random Coding Boundsp. 170
Appendix 6.Ap. 180
Appendix 6.Bp. 180
Bibliographyp. 181
7 Decoding Strategiesp. 183
7.1 Background and Introductionp. 183
7.2 Tree Decodersp. 184
7.3 The Stack Algorithmp. 187
7.4 The Fano Algorithmp. 188
7.5 The M-Algorithmp. 190
7.6 Maximum Likelihood Decodingp. 200
7.7 A Posteriori Probability Symbol Decodingp. 203
7.8 Log-APP and Approximationsp. 209
7.9 Random Coding Analysis of Sequential Decodingp. 213
7.10 Some Final Remarksp. 218
Appendix 7.Ap. 219
Bibliographyp. 223
8 Factor Graphsp. 227
8.1 Factor Graphs: Introduction and Historyp. 227
8.2 Graphical Function Representationp. 228
8.3 The Sum-Product Algorithmp. 231
8.4 Iterative Probability Propagationp. 232
8.5 The Factor Graph of Trellisesp. 235
8.6 Exactness of the Sum-Product Algorithm for Treesp. 238
8.7 Binary Factor Graphsp. 242
Variable Node Messagesp. 242
Parity-Check Node Messagesp. 243
Log Likelihood Ratio (LLR)p. 243
LLR Variable Node Messagesp. 243
LLR Check Node Messagesp. 244
8.8 Normal Factor Graphsp. 245
Symbol Variable Replicationp. 246
State Variable Replicationp. 247
Bibliographyp. 247
9 Low-Density Parity-Check Codesp. 251
9.1 Introductionp. 251
9.2 LDPC Codes and Graphsp. 252
9.3 Message Passing Decoding Algorithmsp. 255
9.4 Density Evolutionp. 259
9.5 Density Evolution for Binary Erasure Channelsp. 260
9.6 Binary Symmetric Channels and the Gallager Algorithmsp. 265
9.7 The AWGN Channelp. 269
9.8 LDPC Encodingp. 275
9.9 Encoding via Message-Passingp. 277
9.10 Repeat Accumulate Codes on Graphsp. 280
Bibliographyp. 283
10 Parallel Concatenation (Turbo Codes)p. 285
10.1 Introductionp. 285
10.2 Parallel Concatenated Convolutional Codesp. 287
10.3 Distance Spectrum Analysis of Turbo Codesp. 290
10.4 The Free Distance of a Turbo Codep. 292
10.5 The Distance Spectrum of a Turbo Codep. 297
10.6 Weight Enumerator Analysis of Turbo Codesp. 300
10.7 Iterative Decoding of Turbo Codesp. 307
10.8 EXIT Analysisp. 310
10.9 Interleaversp. 317
10.10 Turbo Codes in Telecommunication Standardsp. 320
10.10.1 The Space Data System Standardp. 320
10.10.2 3G Wireless Standardsp. 322
10.10.3 Digital Video Broadcast Standardsp. 323
10.11 Epilogp. 324
Bibliographyp. 325
11 Serial Concatenationp. 329
11.1 Introductionp. 329
11.2 An Introductory Examplep. 330
11.3 Weight Enumerator Analysis of SCCCsp. 331
11.3.1 Design Rule Examplesp. 338
11.4 Iterative Decoding and Performance of SCCCsp. 341
11.4.1 Performance of SCCCs and PCCCsp. 343
11.5 EXIT Analysis of Serially Concatenated Codesp. 344
11.6 Conclusionp. 348
Bibliographyp. 348
12 Turbo-Coded Modulationp. 351
12.1 Introductionp. 351
12.2 Turbo-Trellis-Coded Modulation (TTCM)p. 351
12.3 Serial Concatenationp. 355
12.4 EXIT Analysisp. 356
12.5 Differential-Coded Modulationp. 358
12.6 Concatenated Space-Time Codingp. 363
12.7 Product Codes and Block Turbo Decodingp. 368
12.8 Approximate APP Decodingp. 369
12.9 Product Codes with High-Order Modulationsp. 372
12.10 The IEEE 802.16 Standardp. 374
Bibliographyp. 375
Indexp. 379