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Iterative Detection: Adaptivity, Complexity Reduction, and Applications is a primary resource for both researchers and teachers in the field of communication.
Unlike other books in the area, it presents a general view of iterative detection that does not rely heavily on coding theory or graph theory. The features of the text include:

• Both theoretical background and numerous real-world applications.
• Over 70 detailed examples, 100 problems, 180 illustrations, tables of notation and acronyms, and an extensive bibliography and subject index.
• A whole chapter devoted to a case study on turbo decoder design.
• Receiver design guidelines, rules and suggestions.
• The most advanced view of iterative (turbo) detection based only on block diagrams and standard detection and estimation theory.
• Development of adaptive iterative detection theory.
• Application of adaptive iterative detection to phase and channel tracking in turbo coded systems and systems representative of digital mobile radio designs.
• An entire chapter dedicated to complexity reduction.
• Numerous recent research results.
• Discussion of open problems at the end of each chapter.

Among the applications considered in this book are joint equalization and decoding, turbo codes, multiuser detection and decoding, broadband wireless channel equalization, and applications to two-dimensional storage and imaging systems.
Audience: Iterative Detection: Adaptivity, Complexity Reduction, and Applications provides an accessible and detailed reference for researchers, practicing engineers, and students working in the field of detection and estimation. It will be of particular interest to those who would like to learn how iterative detection can be applied to equalization, interference mitigation, and general signal processing tasks. Researchers and practicing engineers interested in learning the turbo decoding algorithm should also have this book.

Iterative Detection: Adaptivity, Complexity Reduction, and Applications is a primary resource for both researchers and teachers in the field of communication.
Unlike other books in the area, it presents a general view of iterative detection that does not rely heavily on coding theory or graph theory. The features of the text include:

• Both theoretical background and numerous real-world applications.
• Over 70 detailed examples, 100 problems, 180 illustrations, tables of notation and acronyms, and an extensive bibliography and subject index.
• A whole chapter devoted to a case study on turbo decoder design.
• Receiver design guidelines, rules and suggestions.
• The most advanced view of iterative (turbo) detection based only on block diagrams and standard detection and estimation theory.
• Development of adaptive iterative detection theory.
• Application of adaptive iterative detection to phase and channel tracking in turbo coded systems and systems representative of digital mobile radio designs.
• An entire chapter dedicated to complexity reduction.
• Numerous recent research results.
• Discussion of open problems at the end of each chapter.

Among the applications considered in this book are joint equalization and decoding, turbo codes, multiuser detection and decoding, broadband wireless channel equalization, and applications to two-dimensional storage and imaging systems.
Audience: Iterative Detection: Adaptivity, Complexity Reduction, and Applications provides an accessible and detailed reference for researchers, practicing engineers, and students working in the field of detection and estimation. It will be of particular interest to those who would like to learn how iterative detection can be applied to equalization, interference mitigation, and general signal processing tasks. Researchers and practicing engineers interested in learning the turbo decoding algorithm should also have this book.

정보제공 :

Preface. Introduction. 1. Overview of Non-Iterative  Detection. 2. Principles of Iterative Detection. 3.  Iterative Detection for Complexity Reduction. 4. Adaptive  Iterative Detection. 5. Applications in Two Dimensional Systems.  6. Implementation Issues: A Turbo Decoder Design Case Study.  References. Index.

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