数字通信基础

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用数字形式传输消息或用数字形式对载波信号进行调制后再传输的通信方式。常规的电话和电视都属于模拟通信。电话和电视模拟信号经数字化后,再进行数字信号的调制和传输,便称为数字电话和数字电视。以计算机为终端机的相互间的数据通信,因信号本身就是数字形式,而属于数字通信。卫星通信中采用时分或码分的多路通信也属于数字通信。 数字通信系统的模型如图1所示,图中信源输出的是模拟信号,经过数字终端的信源编码器成为数字信号,终端输出的数字信号,经过信道编码器后变成适合于信道传输的数字信号,然后由解调器把数字信号调制到系统所使用的数字信道上,再传输到接收端,经过相反的转换后最终送到信宿
Fundamentals of Digital Communication This textbook presents the fundamental concepts underlying the design of modern digital communication systems, which include the wireline, wire less, and storage systems that pervade our everyday lives. Using a highly accessible, lecture style exposition, this rigorous textbook first establishes a firm grounding in classical concepts of modulation and demodulation, and hen builds on these to introduce advanced concepts in synchronization, non coherent communication, channel equalization, information theory, channel coding, and wireless communication. This up-to-date textbook covers turbo and LDPC codes in sufficient detail and clarity to enable hands-on imple- mentation and performance evaluation, as well as"just enough"information theory to enable computation of performance benchmarks to compare them against Other unique features include the use of complex baseband represen tation as a unifying framework for transceiver design and implementation wireless link design for a number of modulation formats, including space- time communication; geometric insights into noncoherent communication and equalization The presentation is self-contained and the topics are selected so as to bring the reader to the cutting edge of digital communications research and development Numerous examples are used to illustrate the key principles, with a view to allowing the reader to perform detailed computations and simulations based on the ideas presented in the text With homework problems and numerous examples for each chapter, this textbook is suitable for advanced undergraduate and graduate students of electrical and computer engineering and can be used as the basis for a one or two semester course in digital communication. It will also be a valuable resource for practitioners in the communications industry Additional resources for this title, including instructor-only solutions, are availableonlineatwww.cambridge.org/9780521874144. Upamanyu Madhow is Professor of Electrical and Computer Engineering at the University of California, Santa Barbara. He received his Ph D. in Electrical Engineering from the University of Illinois, Urbana-Champaign, in 1990, where he later served on the faculty. A Fellow of the IEEe, he worked for several years at Telcordia before moving to academia Fundamentals of Digital Communication Upamanyu Madhow University of California, Santa Barbara 感题 CAMBRIDGE 想罗 UNIVERSITY PRESS CAMBRIDGE UNIVERSITY PRESS Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, Sao Paulo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of america by Cambridge university Press, New York www.cambridge.org Informationonthistitlewww.cambridgeorg/9780521874144 o Cambridge University Press 2008 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press First published in print format 2008 ISBN-13978-0-511-38606-0 eBook(EBL) ISBN-13978-0-521-87414-4 arabah Cambridge university press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate To my family Contents Preface page xill Acknowledgements XVI 1 Introduction 1.1 Components of a digital communication system 1.2 Text outline 1.3 Further reading 2 Modulation 25678 2.1 Preliminaries 2.2 Complex baseband representation 18 2.3 Spectral description of random processes 2.3. 1 Complex envelope for passband random processes 40 2.4 Modulation degrees of freedom 2.5 Linear modulation 43 2.5.1 Examples of linear modulation 44 2.5.2 Spectral occupancy of linearly modulated signals 46 2.5.3 The Nyquist criterion: relating bandwidth to symbol rate 49 2.5.4 Linear modulation as a building block 2.6 Orthogonal and biorthogonal modulation 55 2.7 Differential modulation 57 2.8 Further reading 60 2.9 Problems 60 2.9.1 Signals and systems 2.9.2 Complex baseband representation 62 2.9.3 Random processes 64 2.9.4 Modulation 66 3 Demodulation 74 3.1 Gaussian basics 75 3.2 Hypothesis testing basics 88 VIl Contents 3.3 Signal space concepts 4 3.4 Optimal reception in AWGN 102 3. 4.1 Geometry of the ml decision rule 106 3.4.2 Soft decisions 107 3.5 Performance analysis of ML reception 109 3.5.1 Performance with binary signalin 110 3.5.2 Performance with M-ary signalin 114 3. 6 Bit-level demodulation 127 3.6.1 Bit-level soft decisions 131 3.7 Elements of link budget analysis 133 3. 8 Further reading 136 3.9 Problems 136 3.9.1 Gaussian basics 136 3.9.2 Hypothesis testing basics 138 3.9.3 Receiver design and performance analysis for the awgn channel 140 3.9.4 Link budget analysis 149 3.9.5 Some mathematical derivations 150 4 Synchronization and noncoherent communication 153 4.1 Receiver design requirements 155 4.2 Parameter estimation basics 15 4.2.1 Likelihood function of a signal in AWGn 162 4.3 Parameter estimation for synchronization 165 4. 4 Noncoherent communication 4.4.1 Composite hypothesis testing 171 4.4.2 Optimal oherent demodulation 172 4. 4.3 Differential modulation and demodulation 173 4.5 Performance of noncoherent communication 4.5. 1 Proper complex gaussianity 176 4.5.2 Performance of binary noncoherent communication 181 4.5.3 Performance of M-ary noncoherent orthogonal signaling 185 4.5.4 Performance of dPsK 187 4.5.5 Block noncoherent demodulation 188 4.6 Further reading 189 4.7 Problems 190 5 Channel equalization 199 5.1 The channel model 200 5.2 Receiver front end 20 5.3 Eye diagrams 203 5.4 Maximum likelihood sequence estimation 204 5.4.1 Alternative Mlse formulation 212 5.5 Geometric model for suboptimal equalizer design 5.6 Linear equalization 216

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