Blind equalization and identification

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Blind equalization and identification / edited by Zhi Ding, Ye (Geoffrey) Li

資料種別:

図書

出版情報:

New York : Marcel Dekker, c2001

形態:

xiv, 409 p. ; 24 cm

シリーズ名:

Signal processing and communications series ; 9 <BA46596208>

著者名:

ISBN:

9780824704797 [0824704797]

書誌ID:

BA50289177

子書誌情報

フルテキスト

所蔵情報

他の版・巻

書誌詳細

注記:

Includes index

主題:

Digital communications; Signal processing--Digital techniques

言語:

英語

目次情報:

Series Introduction

Preface

Introduction / 1：

Blind Equalization: A Popular Research Topic / 1.1：

Motivation For This Book / 1.2：

Blind Equalization and Identification of Communication Channels / 1.3：

Network Collision Resolution of Transmitted Packets / 1.4：

Blind Deconvolution: A Related Application / 1.5：

A Brief History / 1.6：

1975 to Present: Blind Single Channel Equalization / 1.6.1：

1981 to Present: Blind Statistical Channel Identification / 1.6.2：

1991 to Present: Multichannel Identification and Equalization / 1.6.3：

Organization and Contents / 1.7：

Basic Concepts and Approaches / 2：

Channel Equalization in QAM Data Communication Systems / 2.1：

SISO and SIMO Discrete Channel Model / 2.2：

Channel Equalization / 2.3：

T-Spaced Equalizers / 2.3.1：

Fractionally-Spaced Equalizers / 2.3.2：

Nonlinear Equalization / 2.3.3：

The Need for Blind Channel Equalization and Identification / 2.4：

Basic Approaches to Blind Equalization and Identification / 2.5：

Blind SISO Equalization / 2.5.1：

Blind SISO Channel Identification / 2.5.2：

Blind SIMO Channel Identification / 2.5.3：

Blind Multichannel Equalization / 2.5.4：

Single Input Single Output Blind Equalization Algorithms / 3：

SISO Channel Equalization / 3.1：

Channel Equalization in QAM Communication Systems / 3.2.1：

Blind Adaptive Channel Equalizer / 3.2.2：

Basic Facts on Blind Adaptive Equalization / 3.2.3：

Adaptive Blind SISO Equalizers / 3.3：

FIR Linear Equalizers / 3.3.1：

Cost Functions and Associated Adaptive Algorithms / 3.3.2：

The Sato Algorithm and Its Generalizations / 3.4：

The Sato Algorithm / 3.4.1：

BGR Algorithms (an Extension of the Sato Algorithm) / 3.4.2：

Stop-and-Go Algorithms / 3.4.3：

Bussgang Algorithms / 3.4.4：

Constant Modulus Algorithms and Related Schemes / 3.5：

Constant Modulus (Godard) Algorithm / 3.5.1：

Shalvi and Weinstein Algorithms / 3.5.2：

Stochastic Gradient Descent Adaptation / 3.6：

A Blind Equalization Example / 3.7：

Convergence of Blind SISO Adaptive Algorithms / 3.8：

Convergence Requirement of Open Eye Equalizers / 3.8.1：

Some Known Convergence Results / 3.8.2：

Local Convergence of Blind Equalizers / 3.8.3：

Convergence Requirement of Bussgang Algorithms / 3.8.4：

Initialization Issues / 3.8.5：

QAM Algorithms Based on Convex Cost Functions / 3.9：

Background / 3.9.1：

Linearly Constrained Equalizer with Convex Cost / 3.9.2：

Convex Cost Function and Parameter Constraint / 3.9.3：

Global Convergence / 3.9.4：

Remarks and Comments / 3.9.5：

Implementation and Simulation / 3.9.6：

A Fast Linear Programming Algorithm for Convex Cost / 3.10：

Weakness of Batch and Adaptive Implementations / 3.10.1：

Linear Programming Formulations / 3.10.2：

Summary / 3.10.3：

Local Convergence Analysis of SISO Blind Equalizers / 4：

Convergence Equilibria of Blind Equalizers / 4.1：

The Constant Modulus Algorithm and Godard Algorithm / 4.2：

Undesirable Equilibria of Godard Algorithms / 4.2.1：

Stability Condition for the Undesirable Equilibria / 4.2.2：

Consequences of Ill-Convergence / 4.2.3：

Examples of Stable Undesirable Equilibria / 4.2.4：

Effect of Channel Noise and Mismodeling / 4.2.5：

Shalvi-Weinstein and Standard Cumulant Algorithms / 4.3：

Geometric Relationship between SWA and CMA / 4.3.1：

Initial Kurtosis Effect on SWA Finite Equalizer convergence / 4.3.2：

SWA Minimum Location and An Initialization Strategy / 4.3.3：

Extension of Results to QAM Communication Systems / 4.3.4：

Convergence Analysis of Equalizers Driven by SCA / 4.3.5：

Decision-Direct and Stop-and-Go Algorithms / 4.4：

Decision-Directed Equalizer / 4.5.1：

Computer Simulation Example / 4.5.3：

Non-Equivalence of Two Parameter Spaces / 4.6：

Nullspace Analysis for Causal Parameterizations / 4.6.1：

Nullspace Analysis for Doubly Infinite Parameterizations / 4.6.2：

Comments / 4.6.3：

Example / 4.6.4：

Length-Dependent and Cost-Dependent Local Minima / 4.7：

Length-Dependent Local Minima / 4.7.1：

Cost-Dependent Local Minima of Some Blind Algorithms / 4.7.2：

Static and Dynamic Convergence Behavior of FIR Equalizers / 4.8：

Basic Relationships / 4.8.1：

Properties of Prediction Error Function / 4.8.2：

Static Convergence Analysis / 4.8.3：

Dynamic Convergence Analysis / 4.8.4：

Computer Simulations / 4.8.5：

Summary and Further Reading / 4.9：

Linear Multichannel Identification Methods Based On Second Order Statistics / 5：

Multiple Discrete Channel Model for Identification / 5.1：

Linear Baseband Model / 5.2.1：

Channel Diversity from Integer Oversampling / 5.2.2：

Fractional Oversampling / 5.2.3：

Second Order Statistics of Multichannel Outputs / 5.3：

The TXK Time Domain SIMO Algorithm / 5.4：

Two SIMO Methods for Blind Identification / 5.5：

A Subspace Based Algorithm / 5.5.1：

A Subchannel Matching Algorithm / 5.5.2：

Exploiting Partial System Information / 5.6：

Motivations / 5.6.1：

Partial Knowledge of the Composite Channel / 5.6.2：

Simulation Results / 5.6.3：

Least Square Estimation Approaches to SIMO Identification / 5.7：

Multichannel Identification from Second Order Statistics / 5.7.1：

Linear Prediction Algorithm for Multichannel Identification / 5.7.2：

Outer-Product Decomposition Algorithm / 5.7.3：

Multi-Step Linear Prediction / 5.7.4：

Channel Estimation by Linear Smoothing / 5.7.5：

Channel Estimation by Constrained Output Energy Minimization / 5.7.6：

Discussion / 5.7.7：

Chapter Summary / 5.7.8：

Frequency Domain Approaches to Single User Channel Identification / 6：

Overview / 6.1：

Second Order Cyclostationarity / 6.2：

Channel Identification via Frequency Response Sampling / 6.3：

Channel Phase Information in Output SCD / 6.4：

Rational Transfer Function Identification / 6.5：

Discussions / 6.6：

SCD Estimation and Simulation / 6.7：

Estimating SCD from Data / 6.7.1：

Simulation Example / 6.7.2：

Discrete ARMA System Identification / 6.8：

Cyclostationary Channel Information / 6.8.1：

The Need for a Parametric Channel Model / 6.8.2：

A Parametric Identification Method for ARMA Channels / 6.9：

Basic Conditions / 6.9.1：

Identifying Poles and Zeros / 6.9.2：

Remarks / 6.9.3：

Non-Parametric Identification of ARMA Channels / 6.10：

Magnitude Identification / 6.10.1：

Phase Identification / 6.10.2：

Phase Distortion Analysis / 6.10.3：

Phase Unwrapping and a Combined Method / 6.10.4：

Simulation Results of Frequency Domain Methods / 6.11：

Phase Response Recovery Based on Partial Knowledge / 6.12：

Exploiting Known Phase Information / 6.12.1：

Adaptive Multichannel Equalization / 6.12.2：

Multichannel Equalization / 7.1：

SIMO Equalizers / 7.1.1：

MIMO Equalizers / 7.1.2：

SIMO Constant Modulus Algorithm / 7.2：

Basic Properties / 7.2.1：

Uniqueness of Hyper-cone / 7.2.2：

Global Convergence of CMA-FSE / 7.2.3：

Initialization of CMA-FSE / 7.2.4：

SIMO Super-Exponential Algorithm / 7.2.5：

An Unwilling Approximation in TSE Implementation / 7.3.1：

Exact Implementation in FSE / 7.3.2：

Convergence Issues / 7.3.3：

Higher Order Statistical Realization of SEA / 7.3.4：

General Convergence Properties of SIMO Equalizers (FSE) / 7.3.5：

Two Classes of Minima / 7.4.1：

Disappearance of LDM in FSE / 7.4.2：

Cost-Dependent Minima / 7.4.3：

MIMO CMA Equalizer / 7.5：

Linear Equalizability / 7.5.1：

CMA Signal Capturing / 7.5.2：

MIMO Signal Recovery Example / 7.5.3：

Multiple Signal Equalization and Recovery / 7.6：

CMA Cost Modification / 7.6.1：

Global Convergence of Modified CMA MIMO Equalizers / 7.6.2：

Local Convergence / 7.6.3：

Selected Topics in Multichannel Equalization / 7.6.4：

Deterministic Approaches to Blind Equalization / 8.1：

Direct Multichannel Blind Equalization / 8.1.1：

Direct Symbol Estimation / 8.1.2：

Deterministic Channel Equalization / 8.1.3：

Column Anchored Equalization / 8.2：

Input Statistical Information / 8.2.1：

Column Shifting / 8.2.2：

Fixed Delay Column Anchoring / 8.2.3：

Variable Delay Column Anchoring / 8.2.4：

Channel Noise Considerations / 8.2.5：

MMSE Equalization / 8.3：

Basic Assumptions and Matrix Properties / 8.3.1：

MMSE Blind Equalizers / 8.3.2：

Estimation of Cross-Correlation Vector / 8.3.3：

MMSE Blind Equalization for SIMO Systems / 8.3.4：

Simulation Examples / 8.3.5：

Scanning the Literature / 8.4：

Blind Channel Equalization and Symbol Estimation / 9.1：

Blind and Semi-blind Channel Identification / 9.2：

Applications in CDMA, OFDM, and Other Systems / 9.3：

Index

Series Introduction

Preface

Introduction / 1：

Blind Equalization: A Popular Research Topic / 1.1：

Motivation For This Book / 1.2：

Blind Equalization and Identification of Communication Channels / 1.3：

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