Wireless Communication Systems

Wireless Communication Systems : Advanced Techniques for Signal Reception

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Appropriate for all courses in wireless receiver design, and for advanced courses in signal processing.As the performance and power requirements for wireless devices become increasingly challenging, engineers have recognized that advanced signal processing techniques are more crucial than ever. This book presents a unified framework for understanding the state-of-the-art in signal processing for wireless communications.Dr. Xiadong Wang and Dr. H. Vincent Poor focus on the development, analysis, and use of explicit algorithms for performing advanced processing tasks that arise in receiver design for emerging wireless systems, and provide a comprehensive set of algorithms for addressing physical issues, including multi-path, dispersion, interference, dynamism, and multiple-antenna systems. Many of the methods detailed here were developed by the co-authors themselves, notably in the areas of turbo processing, multiple-antenna systems, and low-complexity adaptive algorithms.
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Product details

  • Hardback | 704 pages
  • 176.3 x 246.9 x 30.2mm | 1,179.35g
  • Prentice Hall
  • Upper Saddle River, United States
  • English
  • 0130214353
  • 9780130214355

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A unified framework for using today's most advanced signal processing techniques

Driven by the rapidly escalating capacity demands of emerging wireless systems, researchers havedeveloped a wide array of novel signal processing techniques for use in such systems. Now, twoleading researchers synthesize the field's vast new literature, giving working engineers practicalguidance for designing advanced wireless receivers.

Drs. Xiaodong Wang and H. Vincent Poor offer a complete framework for developing, analyzing, andunderstanding the explicit algorithms needed for advanced processing in emerging wireless systems.They address a full range of physical-layer issues, including multipath, dispersion, interference, dynamism, and multiple-antenna systems. In many cases, the authors themselves developed the methodsthey present. Coverage includes: An overview of contemporary wireless signaling environments and basic receiver signal processing techniquesBlind, group-blind, space-time, and turbo multiuser detectionRobust multiuser detection in non-Gaussian channelsNarrowband interference suppression: linear and non-linear predictive techniques, performance comparisons, and moreMonte Carlo Bayesian signal processingSignal processing for fast fading channelsAdvanced signal processing for coded OFDM systems
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Table of contents

Preface. 1. Introduction. Motivation. Wireless Signaling Environment. Basic Receiver Signal Processing for Wireless. Outline of the Book. 2. Blind Multiuser Detection. Introduction. Linear Receivers for Synchronous CDMA. Blind Multiuser Detection: Direct Methods. Blind Multiuser Detection: Subspace Methods. Performance of Blind Multiuser Detectors. Subspace Tracking Algorithms. Blind Multiuser Detection in Multipath Channels. Appendix. 3. Group-Blind Multiuser Detection. Introduction. Linear Group-Blind Multiuser Detection for Synchronous CDMA. Performance of Group-Blind Multiuser Detectors. Nonlinear Group-Blind Multiuser Detection for Synchronous CDMA. Group-Blind Multiuser Detection in Multipath Channels. Appendix. 4. Robust Multiuser Detection in Non-Gaussian Channels. Introduction. Multiuser Detection via Robust Regression. Asymptotic Performance of Robust Multiuser Detection. Implementation of Robust Multiuser Detectors. Robust Blind Multiuser Detection. Robust Multiuser Detection Based on Local Likelihood Search. Robust Group-Blind Multiuser Detection. Extension to Multipath Channels. Robust Multiuser Detection in Stable Noise. Appendix. 5. Space-Time Multiuser Detection. Introduction. Adaptive Array Processing in TDMA Systems. Optimal Space-Time Multiuser Detection. Linear Space-Time Multiuser Detection. Adaptive Space-Time Multiuser Detection in Synchronous CDMA. Adaptive Space-Time Multiuser Detection in Multipath CDMA. 6. Turbo Multiuser Detection. Introduction to Turbo Processing. MAP Decoding Algorithm for Convolutional Codes. Turbo Multiuser Detection for Synchronous CDMA. Turbo Multiuser Detection with Unknown Interferers. Turbo Multiuser Detection in CDMA with Multipath Fading. Turbo Multiuser Detection in CDMA with Turbo Coding. Turbo Multiuser Detection in Space-Time Block-Coded Systems. Turbo Multiuser Detection in Space-Time Trellis-Coded Systems. Appendix. 7. Narrowband Interference Suppression. Introduction. Linear Predictive Techniques. Nonlinear Predictive Techniques. Code-Aided Techniques. Performance Comparisons of NBI Suppression Techniques. Near.Far Resistance to Both NBI and MAI by Linear MMSE Detector. Adaptive Linear MMSE NBI Suppression. Maximum-Likelihood Code-Aided Method. Appendix: Convergence of the RLS Linear MMSE Detector. 8. Monte Carlo Bayesian Signal Processing. Introduction. Bayesian Signal Processing. Markov Chain Monte Carlo Signal Processing. Bayesian Multiuser Detection via MCMC. Sequential Monte Carlo Signal Processing. Blind Adaptive Equalization of MIMO Channels via SMC. Appendix. 9. Signal Processing For Fading Channels. Introduction. Statistical Modeling of Multipath Fading Channels. Coherent Detection in Fading Channels Based on the EM Algorithm. Decision-Feedback Differential Detection in Fading Channels. Adaptive SMC Receivers for Flat-Fading Channels. Appendix. 10. Advanced Signal Processing for Coded OFDM Systems. Introduction. OFDM Communication System. Blind MCMC Receiver for Coded OFDM with Frequency-Selective Fading and Frequency Offset. Pilot-Symbol-Aided Turbo Receiver for Space-Time Block-Coded OFDM Systems. LDPC-Based Space-Time Coded OFDM Systems. Appendix. Acronyms. Bibliography. Index.
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About Xiaodong Wang

XIAODONG WANG, Assistant Professor in the Department of Electrical Engineering, ColumbiaUniversity, has done extensive research in wireless communications and signal processing. Hereceived the National Science Foundation Career Award and the IEEE Communications Society andInformation Theory Society Joint Paper Award. H. VINCENT POOR, Professor of Electrical Engineeringat Princeton University, currently researches statistical signal processing applications inwireless communications. An IEEE Fellow and member of the National Academy of Engineering, he hasreceived the ASEE Frederick E. Terman Award, the IEEE Graduate Teaching Award, the NSF Director'sAward for Distinguished Teaching Scholars, and a Guggenheim Fellowship.
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