Channel Equalization for Wireless Communications E-Book

Gregory E. Bottomley

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Serie: IEEE Press Series on Digital & Mobile Communication
• Sprache: Englisch

Seitenzahl: 379

Veröffentlichungsjahr: 2012

Beschreibung

The most thorough, up-to-date reference on channel equalization--from basic concepts to complex modeling techniques In today's instant-access society, a high premium is placed on information that can be stored and communicated effectively. As a result, storage densities and communications rates are being pushed to capacity, causing information symbols to interfere with one another. To help unclog pathways for the clearer conveyance of information, this book offers in-depth discussion of the significant contributions and future adaptability of channel equalization and a set of approaches for solving the problem of intersymbol interference (ISI). Chapter explorations in Channel Equalization include: * Channel equalization topics presented with incremental learning methodology--from the very fundamental concept to more advanced mathematical knowledge * Coverage of technology used in second-, third- and fourth-generation cellular communication systems * A set of homework problems that reinforce concepts discussed in the book * Tutorial explanations of recent developments currently captured in IEEE technical journals Unlike existing digital communications books that devote cursory attention to channel equalization, this invaluable guide addresses a crucial need by focusing solely on the background, current state, and future direction of this increasingly important technology. A unique mix of basic concepts and complex frameworks for delivering digitized data make Channel Equalization a valuable reference for all practicing wireless communication engineers and students dealing with the pressing demands of the information age.

Leseprobe

CONTENTS

Cover

Title page

Copyright page

Dedication

List of Figures

List of Tables

Prologue

Preface

Acknowledgments

Acronyms

Chapter 1: Introduction

1.1 The Idea

1.2 More Details

1.3 The Math

1.4 More Math

1.5 An Example

1.6 The Literature

Problems

Chapter 2: Matched Filtering

2.1 The Idea

2.2 More Details

2.3 The Math

2.4 More Math

2.5 An Example

2.6 The Literature

Problems

Chapter 3: Zero-Forcing Decision Feedback Equalization

3.1 The Idea

3.2 More Details

3.3 The Math

3.4 More Math

3.5 An Example

3.6 The Literature

Problems

Chapter 4: Linear Equalization

4.1 The Idea

4.2 More Details

4.3 The Math

4.4 More Math

4.5 An Example

4.6 The Literature

Problems

Chapter 5: MMSE and ML Decision Feedback Equalization

5.1 The Idea

5.2 More Details

5.3 The Math

5.4 More Math

5.5 An Example

5.6 The Literature

Problems

Chapter 6: Maximum Likelihood Sequence Detection

6.1 The Idea

6.2 More Details

6.3 The Math

6.4 More Math

6.5 An Example

6.6 The Literature

Problems

Chapter 7: Advanced Topics

7.1 The Idea

7.2 More Details

7.3 The Math

7.4 More Math

7.5 An Example

7.6 The Literature

Problems

Chapter 8: Practical Considerations

8.1 The Idea

8.2 More Details

8.3 The Math

8.4 More practical aspects

8.5 An Example

8.6 The Literature

Problems

Epilogue

Appendix A: Simulation Notes

A.1 Fading channels

A.2 Matched filter and matched filter bound

A.3 Simulation calibration

Appendix B: Notation

References

Index

Copyright © 2011 by the Institute of Electrical and Electronics Engineers, Inc.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. All rights reserved.

Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data is available.

ISBN 9780470874271

oBook ISBN: 9781118105252ePDF ISBN: 9781118105283ePub ISBN: 9781118105276MOBI ISBN: 9781118105269

To my colleagues at Ericsson

LIST OF TABLES

1.1 Possible messages

1.2 Walsh codes of length 4

1.3 TDM codes of length 4

1.4 Main block OFDM sequences of length 4

4.1 Example of MMSE LE decision variables

6.1 Example of sequence metrics

7.1 Example of MAPSD symbol metrics

7.2 Example of message metrics formed from MAPSD metrics

7.3 Example of message metrics formed from MMSE LE metrics

7.4 Example of normalized sequence metrics

7.5 (7,4) Hamming code bit positions

7.6 Example of message metrics for (7,4) Hamming code

Prologue

Alice was nervous. Would Bob receive the message correctly? They were playing a new cell phone version of Truth or Dare, and Bob had picked Truth. Alice was given a list of three questions and had selected one to ask him. But Bob was far from the cell tower that was sending her message to him. Her message was bouncing off of buildings and arriving at Bob’s phone like multiple echoes. Would Bob’s phone be able to figure out the message? Would she be able to receive his response?

PREFACE

The working title of this book was Channel Equalization for Everyone. Channel equalization for everyone? Well, for high school students, channel equalization provides a simple, interesting example of how mathematics and physics can be used to solve real-world problems. It also introduces them to the way engineers think, perhaps inspiring them to pursue a degree in engineering. Similar reasoning applies to first-year undergraduate engineering students.

For senior undergraduate students and graduate students in electrical engineering, channel equalization is a useful topic in communications. Data rates on wireless and wireline connections continue to rise, as do information densities on storage devices. Packing more and more digital symbols in time or space ultimately leads to intersymbol interference, requiring some form of equalization. Each new communications air interface or data storage device poses its own challenges, keeping channel equalization a topic of research as well.

So how can one book be used to teach channel equalization to such different audiences? Each chapter is divided into the following sections.

1. The Idea: The idea is described at a level suitable for junior/senior high school students and first-year undergraduate students with a background in algebra.

2. More Details: More information is provided that is intended for senior undergraduate students but is perhaps more suitable for first-year graduate students more comfortable with many variables in algebra. Differential calculus and complex numbers are used in a few places. A little bit of probability theory is introduced as needed, A set of equations is sometimes written in matrix form, but linear algebra concepts such as matrix inverses are not used.

3. The Math: The idea is described in more general, mathematical terms suitable for second-year graduate students with a background in calculus, communication theory, linear algebra, and probability theory. To avoid getting lost in the math, the simple case of time-division multiplexing is considered with single transmit and receive antennas. Performance results are provided along with simulation notes.

4. More Math: The idea is described in even more general terms, considering symbols multiplexed in parallel (e.g., code-division multiplexing (CDM) and orthogonal frequency division multiplexing (OFDM)), multiple transmit antennas, and multiple receive antennas. More sophisticated noise models are also considered.

5. An Example: The idea is applied to a cellular communications system.

6. The Literature: Bibliographic sources are given as well as helpful references on advanced topics for further exploration.

Homework problems are also provided, corresponding to the first three sections.

Thus, a guest lecture for a junior/senior-level high school math class or first-year undergraduate introductory engineering course can be created from the first sections of several chapters. The first and second sections can be used to develop a series of lectures or an entire course for senior undergraduate students. The remaining sections of each chapter provide the basis for a graduate course and a foundation for those performing research.

The scope of the book is primarily the understanding of coherent equalization and the use of digital signal processing (we assume the signal is initially filtered and sampled). Parameter estimation is briefly touched on in the last chapter, and other areas such as blind equalization and performance analysis are not addressed. Basic digital communication theory is introduced where needed, but certain aspects such as system design for a particular channel are not addressed. Specific mathematical tools are not described in detail, as such descriptions are available elsewhere. By keeping the book focused, the hope is that insights and understanding will not get lost. Such an understanding is important when designing equalization algorithms, which often involves taking short cuts to keep costs down while maintaining performance.

The book integrates concepts that are often studied separately. Multiple receive antennas are often studied separately in the array processing literature. Multiple transmit antennas are sometimes considered separately in the MIMO literature. Multiple parallel channels are considered in the multiuser detection literature.

My hope is that the reader will discover the joy of solving the puzzle of channel equalization.

G. E. Bottomley

Raleigh, North Carolina

February 2011

ACKNOWLEDGMENTS

I would like to thank my colleagues at Ericsson for helping me learn about equalization and giving me interesting opportunities to develop and apply that knowledge. Another source of learning was the digital communications textbook by John Proakis [Pro89], which I have relied on heavily in writing this book.

Yet another source of learning was the IEEE. Much of the material in this book is based upon IEEE journal and conference publications. I appreciate the effort involved by authors, reviewers, editors, and IEEE staff. I would also like to thank Mary Mann, Taisuke Soda, the anonymous reviewers, and the rest of the IEEE Press and Wiley publishing organizations for making this book possible.

I would like to thank Prof. Keith Townsend for facilitating my stay at N. C. State University (NCSU) as a Visiting Scholar while writing this book. I also need to thank him, Prof. Brian Hughes, and the rest of the Electrical and Computer Engineering faculty at NCSU for welcoming me and giving me good advice.

Finally, I would like to thank my wife, Dr. Laura J. Bottomley, for providing support and encouragement as well as inspiring the concept of this book through her work as Director of Women in Engineering and Director of Outreach at the College of Engineering at N. C. State University.

G. E. B.

ACRONYMS

ACAlternating CurrentA/DAnalog-to-DigitalADCAmerican Digital CellularAMLDAssisted Maximum Likelihood DetectionAMPSAdvanced Mobile Phone ServiceASKAmplitude Shift KeyingAWGNAdditive White Gaussian NoiseBERBit Error RateBPSKBinary Shift KeyingBCJRBahl, Cocke, Jelinek, and RavivCDFCumulative Distribution FunctionCDMCode-Division MultiplexingCDMACode-Division Multiple AccessCRCCyclic Redundancy CodeD-AMPSDigital Advanced Mobile Phone ServiceDDFSEDelayed Decision-Feedback Sequence EstimationDCDirect CurrentDFEDecision Feedback EqualizationDFSEDecision Feedback Sequence EstimationDFTDiscrete Fourier TransformEDGEEnhanced Data rates for GSM EvolutionEMExpectation-MaximizationEVDOoriginally EVolution, Data Only, now EVolution, Data OptimizedFBFFeedback FilterFECForward Error CorrectionFFForward FilterFFFFeedforward FilterFFTFast Fourier TransformFIRFinite Impulse ResponseGMSKGaussian Minimum Shift KeyingGSMGroupe Spéciale Mobile (French), now Global System for Mobile communicationsHSDPAHigh Speed Data Packet AccessI/QIn-phase/QuadratureIRCInterference Rejection CombiningISInterim StandardIS-95Interim Standard 95, US CDMAISIInterSymbol InterferenceLDPCLow-Density Parity CheckLELinear EqualizationLLFLog-Likelihood FunctionLLRLog-Likelihood RatioLMSLeast Mean-SquareLOSLine-Of-SightLSBLeast Significant BitLTELong Term EvolutionMAPMaximum A PosterioriMAPPDMAP Packet DetectionMAPSDMAP Symbol DetectionMFMatched FilteringMFBMatched Filter BoundMIMOMultiple-Input Multiple-OutputMISIMinimum InterSymbol InterferenceMMSEMinimum Mean-Square ErrorMLMaximum LikelihoodMLDMaximum Likelihood DetectionMLPDMaximum Likelihood Packet DetectionMLSDMaximum Likelihood Sequence DetectionMLSEMaximum Likelihood Sequence EstimationMRCMaximal Ratio CombiningMSEMean-Square ErrorMSBMost Significant BitOFDMOrthogonal Frequency Division MultiplexingPDFProbability Density FunctionPMCParallel Multiplexing ChannelPSPPer-Survivor ProcessingPZFPartial Zero-ForcingQAMQuadrature Amplitude ModulationQPSKQuadrature Phase Shift Keyingr.h.s.right-hand sideRRCRoot-Raised CosineRSSEReduced State Sequence Estimationr.v.random variableSAICSingle Antenna Interference CancellationSINRSignal-to-Interference-plus-Noise RatioSISOSingle-Input Single-OutputSNRSignal-to-Noise RatioSPSet PartitioningTDMTime-Division MultiplexingTDMATime-Division Multiple AccessUS CDMAUnited States CDMA, also IS-95, EVDOUS TDMAUnited States TDMA, also D-AMPS, ADC, IS-54, IS-136WCDMAWideband CDMAWMFWhitened Matched Filteringw.r.t.with respect toZFZero-Forcing

CHAPTER 1

INTRODUCTION

In this chapter we will define the problem we are solving and give mathematical models of the problem, based on the physical laws of nature. Before we do this, let’s jump in with an example.

Alice and Bob

Alice has just sent Bob a question in a game of Truth or Dare. The question is represented by two digital symbols (s1 and s2) as shown in Table 1.1. After sending an initial symbol s0, the symbols are sent one at a time. Each is modified as it travels along a direct path to the receiver, so that it gets multiplied by −10. The symbols also travel along a second path, bouncing off a building, as shown in Fig. 1.1. The signal along this path gets multiplied by 9 and delayed so that it arrives at the same time as the next symbol arrives along the direct path. There is also noise which is added to the received signal.

Table 1.1 Possible messages

IndexRepresentation s1s2Message1+ 1 −1“Do you like classical music?”2−1 −1“Do you like soccer?”3+ 1 +1“Do you like me?”

Figure 1.1 Dispersive scenario.

At Bob’s phone, the received values can be as