Turbo Codes Principles and Applications

This book grew out of our research, industry consulting and con­ tinuing education courses. Turbo coding initially seemed to belong to a restricted research area, while now has become a part of the mainstream telecommu­ nication theory and practice. The turbo decoding principles have found widesprea...

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Bibliographic Details
Main Authors: Vucetic, Branka, Jinhong Yuan (Author)
Format: eBook
Language:English
Published: New York, NY Springer US 2000, 2000
Edition:1st ed. 2000
Series:The Springer International Series in Engineering and Computer Science
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • 6.6 Comparison Between Analytical Upper Bounds and Simulation Results
  • 6.7 Asymptotic Behavior of Turbo Codes
  • 6.8 Iterative SOVA Decoding of Turbo Codes
  • 6.9 Comparison of MAP and SOVA Iterative Decoding Algorithms
  • 6.10 Iterative MAP Decoding of Serial Concatenated Convolutional Codes
  • 6.11 Iterative SOVA Decoding of Serial Concatenated Convolutional Codes
  • 6.12 Serial Concatenated Convolutional Codes with Iterative Decoding
  • 7 Interleavers
  • 7.1 Interleaving
  • 7.2 Interleaving with Error Control Coding
  • 7.3 Interleaving in Turbo Coding
  • 7.4 Block Type Interleavers
  • 7.5 Convolutional Type Interleavers
  • 7.6 Random Type Interleavers
  • 7.7 Code Matched Interleavers
  • 7.8 Design of Code Matched Interleavers
  • 7.9 Performance of Turbo Codes with Code Matched Interleavers
  • 7.10 Performance of Turbo Codes with Cyclic Shift Interleavers
  • 8 Turbo Coding for Fading Channels
  • 8.1 Introduction
  • 8.2 Fading Channels
  • 3.12 Punctured Convolutional Codes
  • 4 Turbo Coding Performance Analysis and Code Design
  • 4.1 Introduction
  • 4.2 Turbo Coding
  • 4.3 Performance Upper Bounds of Turbo Codes
  • 4.4 Turbo Code Performance Evaluation
  • 4.5 Turbo Code Design
  • 4.6 Serial Concatenated Convolutional Codes
  • 5 Trellis Based Decoding of Linear Codes
  • 5.1 Introduction
  • 5.2 System Model
  • 5.3 Optimization Criteria
  • 5.4 The Viterbi Algorithm
  • 5.5 The Bidirectional Soft Output Viterbi Algorithm .
  • 5.6 Sliding Window SOVA
  • 5.7 The MAP Algorithm
  • 5.8 The Max-Log-MAP Algorithm
  • 5.9 The Log-MAP Algorithm
  • 5.10 Comparison of Decoding Algorithms
  • 6 Iterative Decoding
  • 6.1 Optimum Decoding of Turbo Codes
  • 6.2 Iterative Decoding of Turbo Codes Based on the MAP Algorithm
  • 6.3 The Effect of the Number of Iterations on Turbo Code Performance
  • 6.4 The Effect of Interleaver Size onTurbo Code Performance
  • 6.5 The Effect of Puncturing Component Codes on Turbo Code Performance
  • 8.3 Statistical Models for Fading Channels
  • 8.4 Capacity of Fading Channels
  • 8.5 Performance Upper Bounds on Fading Channels
  • 8.6 Iterative Decoding on Fading Channels
  • 8.7 Performance Simulation Results on Fading Channels
  • 9 Turbo Trellis Coded Modulation Schemes
  • 9.1 Introduction
  • 9.2 Binary Turbo Coded Modulation
  • 9.3 Turbo Trellis Coded Modulation
  • 9.4 I-Q Turbo Coded Modulation for Fading Channels
  • 10 Applications of Turbo Codes
  • 10.1 Turbo Codes for Deep Space Communications . . .
  • 10.2 Turbo Codes for CDMA2000
  • 10.3 Turbo Codes for 3GPP
  • 10.4 Turbo Codes for Satellite Communications
  • 1 Introduction
  • 1.1 Digital Communication System Structure
  • 1.2 Fundamental Limits
  • 2 Block Codes
  • 2.1 Block Codes
  • 2.2 Linear Systematic Block Codes
  • 2.3 Parity Check Matrix
  • 2.4 The Minimum Distance of a Block Code
  • 2.5 Maximum Likelihood Decoding of Block Codes for a BSC Channel
  • 2.6 Maximum Likelihood Decoding of Block Codes for a Gaussian Channel
  • 2.7 Weight Distribution of Block Codes
  • 2.8 Performance Upper Bounds
  • 2.9 Coding Gain
  • 2.10 Soft Decision Decoding of Block Codes
  • 2.11 Trellis Structure of Linear Binary Block Codes
  • 3 Convolutional Codes
  • 3.1 Introduction
  • 3.2 The Structure of (n,1)Convolutional Codes
  • 3.3 The Structure of (n,k) Convolutional Codes
  • 3.4 Systematic Form
  • 3.5 Parity Check Matrix
  • 3.6 Catastrophic Codes
  • 3.7 Systematic Encoders
  • 3.8 State Diagram
  • 3.9 Trellis Diagram
  • 3.10 Distance Properties of Convolutional Codes
  • 3.11 Weight Distribution of Convolutional Codes