Joint source-channel coding of discrete-time signals with continuous amplitudes /

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This book provides the first comprehensive and easy-to-read discussion of joint source-channel encoding and decoding for source signals with continuous amplitudes. It is a state-of-the-art presentation of this exciting, thriving field of research, making pioneering contributions to the new concept o...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Goertz, Norbert
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Singapore ; Hackensack, NJ : Imperial College Press ; Distributed by World Scientific Pub., ©2007.
Colección:Communications and signal processing (London, England) ; v. 1.
Temas:
Coding theory.
Adaptive signal processing.
Traitement adaptatif du signal.
COMPUTERS > Information Theory.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Contents
  • Preface
  • 1. Introduction
  • 2. Joint Source-Channel Coding: An Overview
  • 2.1 System Model
  • 2.1.1 Channel
  • 2.1.2 Encoder
  • 2.1.3 Decoder
  • 2.2 System Distortion
  • 2.3 Optimal Decoder for a Given Encoder
  • 2.4 Optimal Encoder
  • 2.5 Special Cases
  • 2.5.1 Preliminary Remarks
  • 2.5.2 Gaussian Source and Gaussian Channel
  • 2.5.3 Channels with Binary Input: Channel-Optimized Vector Quantization
  • 2.6 Practical Approaches to Source-Channel Coding
  • 2.6.1 Systems for Multimedia Transmission
  • 2.6.2 Separation of Source and Channel Coding
  • 2.6.3 Approaches to Joint Source-Channel Decoding
  • 2.6.4 Approaches to Joint Source-Channel Encoding
  • 3. Joint Source-Channel Decoding
  • 3.1 Introduction and System Model
  • 3.2 Near Optimum Joint Source-Channel Decoding
  • 3.2.1 Specialization and Generalization
  • 3.3 Iterative Source-Channel Decoding (ISCD)
  • 3.3.1 Principle and Derivation
  • 3.3.2 Efficient Implementation of ISCD by L-values
  • 3.3.3 Simulation Results for ISCD
  • 3.4 Quantizer Bit Mappings for ISCD
  • 3.4.1 Basic Considerations
  • 3.4.2 Optimization by Binary Switching
  • 3.4.3 Simulation Results with Optimized Bit Mappings
  • 3.5 Conclusions
  • 4. Channel-Adaptive Scaled Vector Quantization
  • 4.1 Introduction
  • 4.2 Memory and Complexity Issues for Vector Quantization (VQ) and Channel-Optimized VQ
  • 4.3 Channel-Adaptive Scaled Vector Quantization
  • 4.3.1 Basic Principle
  • 4.3.2 Optimization of CASVQ
  • 4.3.3 Complexity and Memory Requirements of CASVQ for Transmission over Time-Varying Channels
  • 4.4 Simulation Results
  • 4.5 Conclusions
  • 5. Index Assignments for Multiple Descriptions
  • 5.1 Introduction
  • 5.2 System Model
  • 5.3 Optimal Decoder for a Given Index Assignment
  • 5.4 Quality Criterion for the Index Assignments
  • 5.5 Optimization of the Index Assignments
  • 5.5.1 The Complexity Problem
  • 5.5.2 Index Optimization by the Binary Switching Algorithm for a System with a Single Description
  • 5.5.3 Binary Switching for Multiple Descriptions
  • 5.6 Simulation Results
  • 5.7 Conclusions
  • 6. Source-Adaptive Modulation
  • 6.1 Introduction
  • 6.2 Conventional System Model
  • 6.2.1 Conventional Hard-Decision Receiver
  • 6.2.2 Conventional Soft-Decision Receiver
  • 6.3 Principle of Source-Adaptive Modulation (SAM)
  • 6.4 SAM for Detection of M-PSK Signal Sets
  • 6.4.1 Derivation of the Optimal Solution
  • 6.4.2 Test-Point Method
  • 6.4.3 Analytical Approximation
  • 6.4.4 Simulation Results
  • 6.5 SAM for Quadrature Amplitude Modulation
  • 6.5.1 Discussion of Potential Signal-Point Locations
  • 6.5.2 Simulation Results for SAM with QAM .
  • 6.6 Conclusions
  • 7. Source-Adaptive Power Allocation
  • 7.1 Introduction
  • 7.2 System Model
  • 7.3 Principle of Source-Adaptive Power Allocation
  • 7.4 Conventional Soft-Decision Receiver
  • 7.5 Simulation Results
  • 7.6 Conclusions
  • 8. Concluding Remarks
  • Appendix A Theoretical Performance Limits
  • A.1 Preliminary Remarks
  • A.2 Important Distortion-Rate Functions
  • A.2.1 Memoryless Sources
  • A.2.2 Comparison with Practical Quantization Schemes
  • A.2.3 Gaussian Sources with Memory
  • A.3 Capacities of Practically Important Channels
  • A.3.1 Binary Symmetric Channel (BSC)
  • A.3.2 Binary Erasure Channel (BEC)
  • T$1867.

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