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Trellis and turbo coding /

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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...

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Bibliographic Details
Main Authors: Schlegel, Christian (Author), Perez, Lance (Author)
Corporate Author: Ebook Library
Format: eBook
Language:English
Published: Piscataway, NJ : Hoboken, NJ : IEEE Press ; Wiley-Interscience, [2004]
Series:IEEE series on mobile & digital communication.
Subjects:
Error-correcting codes (Information theory)
Trellis-coded modulation.
Digital communications.
Coding theory.
TECHNOLOGY & ENGINEERING > Telecommunications.
Codes correcteurs d'erreurs (théorie de l'information)
Transmission numérique.
Codage.
Turbo-codes.
Trelliscodierte Modulation.
Turbo-Code.
Communication technology.
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • 1. Introduction
  • 1.1. Modern Digital Communications
  • 1.2. The Rise of Digital Communications
  • 1.3. Communication Systems
  • 1.4. Error Control Coding
  • 1.5. Bandwidth, Power, and Complexity
  • 1.6. A Brief History--The Drive Toward Capacity
  • 2. Communication Theory Basics
  • 2.1. The Probabilistic Viewpoint
  • 2.2. Vector Communication Channels
  • 2.3. Optimum Receivers
  • 2.4. Matched Filters
  • 2.5. Message Sequences
  • 2.6. The Complex Equivalent Baseband Moel
  • 2.7. Spectral Behavior
  • 2.8. Multiple Antenna Channels (MIMO Channels)
  • Appendix 2.A
  • 3. Trellis-Coded Modulation
  • 3.1. An Introductory Example
  • 3.2. Group-Trellis Codes
  • 3.3. The Mapping Function
  • 3.4. Construction of Codes
  • 3.5. Lattices
  • 3.6. Lattice Formulation of Trellis Codes
  • 3.7. Rotational Invariance
  • 3.8. V.fast
  • 3.9. Geometric Uniformity
  • 3.10. Historical Notes
  • 4. Convolutional Codes
  • 4.1. Convolutional Codes as Binary Trellis Codes
  • 4.2. Codes and Encoders
  • 4.3. Fundamental Theorems from Basic Algebra
  • 4.4. Systematic Encoders
  • 4.5. Systematic Feedback and Recursive Systematic Encoder Realizations
  • 4.6. Maximum Free-Distance Convolutional Codes
  • Appendix 4.A
  • 5. Link to Block Codes
  • 5.1. Preliminaries
  • 5.2. Block Code Primer
  • 5.3. Trellis Description of Block Codes
  • 5.4. Minimal Trellises
  • 5.5. Minimum-Span Generator Matrices
  • 5.6. Construction of the PC Trellis
  • 5.7. Tail-Biting Trellises
  • 5.8. The Squaring Construction and the Trellis of Lattices
  • 5.9. The Construction of Reed-Muller Codes
  • 5.10. A Decoding Example
  • 6. Performance Bounds
  • 6.1. Error Analysis
  • 6.2. The Error Event Probability
  • 6.3. Finite-State Machine Description of Error Events
  • 6.4. The Transfer Function Bound
  • 6.5. Reduction Theorems
  • 6.6. Random Coding Bounds
  • Appendix 6.A
  • Appendix 6.B
  • 7. Decoding Strategies
  • 7.1. Background and Introduction
  • 7.2. Tree Decoders
  • 7.3. The Stack Algorithm
  • 7.4. The Fano Algorithm
  • 7.5. The M-Algorithm
  • 7.6. Maximum Likelihood Decoding
  • 7.7. A Posteriori Probability Symbol Decoding
  • 7.8. Log-APP and Approximations
  • 7.9. Random Coding Analysis of Sequential Decoding
  • 7.10. Some Final Remarks
  • Appendix 7.A
  • 8. Factor Graphs
  • 8.1. Factor Graphs: Introduction and History
  • 8.2. Graphical Function Representation
  • 8.3. The Sum-Product Algorithm
  • 8.4. Iterative Probability Propagation
  • 8.5. The Factor Graph of Trellises
  • 8.6. Exactness of the Sum-Product Algorithm for Trees
  • 8.7. Binary Factor Graphs
  • 8.8. Normal Factor Graphs
  • 9. Low-Density Parity-Check Codes
  • 9.1. Introduction
  • 9.2. LDPC Codes and Graphs
  • 9.3. Message Passing Decoding Algorithms
  • 9.4. Density Evolution
  • 9.5. Density Evolution for Binary Erasure Channels
  • 9.6. Binary Symmetric Channels and the Gallager Algorithms
  • 9.7. The AWGN Channel
  • 9.8. LDPC Encoding
  • 9.9. Encoding via Message-Passing
  • 9.10. Repeat Accumulate Codes on Graphs
  • 10. Parallel Concatenation (Turbo Codes)
  • 10.1. Introduction
  • 10.2. Parallel Concatenated Convolutional Codes
  • 10.3. Distance Spectrum Analysis of Turbo Codes
  • 10.4. The Free Distance of a Turbo Code
  • 10.5. The Distance Spectrum of a Turbo Code
  • 10.6. Weight Enumerator Analysis of Turbo Codes
  • 10.7. Iterative Decoding of Turbo Codes
  • 10.8. EXIT Analysis
  • 10.9. Interleavers
  • 10.10. Turbo Codes in Telecommunication Standards
  • 10.11. Epilog
  • 11. Serial Concatenation
  • 11.1. Introduction
  • 11.2. An Introductory Example
  • 11.3. Weight Enumerator Analysis of SCCCs
  • 11.3.1. Design Rule Examples
  • 11.4. Iterative Decoding and Performance of SCCCs
  • 11.4.1. Performance of SCCCs and PCCCs
  • 11.5. EXIT Analysis of Serially Concatenated Codes
  • 11.6. Conclusion
  • 12. Turbo-Coded Modulation
  • 12.1. Introduction
  • 12.2. Turbo-Trellis-Coded Modulation (TTCM)
  • 12.3. Serial Concatenation
  • 12.4. EXIT Analysis
  • 12.5. Differential-Coded Modulation
  • 12.6. Concatenated Space-Time Coding
  • 12.7. Product Codes and Block Turbo Decoding
  • 12.8. Approximate APP Decoding
  • 12.9. Product Codes with High-Order Modulations
  • 12.10. The IEEE 802.16 Standard.