·本书是国际信息论学会前主席所著的极具特色的数字通信入门教材。
·本书通过自上而下的反向教学方法突出数字通信中的传输问题,直接切入了数字通信核心。
本书内容全面,易于理解,通过自上而下的反向教学方法来讲授数字通信的基础知识。这种独特的教学方法突出数字通信中的传输问题,在讲述发射机之前先教授接收机的知识。这样做直接切入了数字通信核心问题,使学生能以最少的背景知识快速、直观地进行学习。从解码器的决策问题开始,涵盖不同信道的接收机设计、硬件设计折衷、卷积编码与维特比解码以及带通通信,书中对系统级设计和实际工程应用进行了详细讲授,并且通过大量示例、作业问题和MATLAB仿真练习来帮助读者自学。本书既可作为通信类专业高年级本科生和研究生教材,又可供工程技术人员参考。
Preface
Acknowledgments
List of symbols
List of abbreviations
1 Introduction and objectives
1.1 The big picture through the OSI layering model
1.2 The topic of this text and some historical perspective
1.3 Problem formulation and preview
1.4 Digital versus analog communication
1.5 Notation
1.6 A few anecdotes
1.7 Supplementary reading
1.8 Appendix: Sources and source coding
1.9 Exercises
2 Receiver design for discrete-time observations: First layer
2.1 Introduction
2.2 Hypothesis testing
2.2.1 Binary hypothesis testing
2.2.2 m-ary hypothesis testing
2.3 The Q function
2.4 Receiver design for the discrete time AWGN channel
2.4.1 Binary decision for scalar observations
2.4.2 Binary decision for n-tuple observations
2.4.3 m-ary decision for -tuple observations
2.5 Irrelevance and sufficient statistic
2.6 Error probability bounds
2.6.1 Union bound
2.6.2 Union Bhattacharyya bound
2.7 Summary
2.8 Appendix: Facts about matrices
2.9 Appendix: Densities after one-to-one differentiable transformations
2.10 Appendix: Gaussian random vectors
2.11 Appendix: A fact about triangles
2.12 Appendix: Inner product spaces
2.12.1 Vector space
2.12.2 Inner product space
2.13 Exercises
3 Receiver design for the continuous-time AWGN channel: Second layer
3.1 Introduction
3.2 White Gaussian noise
3.3 Observables and sufficient statistics
3.4 Transmitter and receiver architecture
3.5 Generalization and alternative receiver structures
3.6 Continuous-time channels revisited
3.7 Summary
3.8 Appendix: A simple simulation
3.9 Appendix: Dirac-delta-based definition of white Gaussian noise
3.10 Appendix: Thermal noise
3.11 Appendix: Channel modeling,a case study
3.12 Exercises
4 Signal design trade-offs
4.1 Introduction
4.2 Isometric transformations applied to the codebook
4.3 Isometric transformations applied to the waveform set
4.4 Building intuition about scalability: n versus k
4.4.1 Keeping n fixed as k grows
4.4.2 Growing n linearly with k
4.4.3 Growing n exponentially with k
4.5 Duration,bandwidth,and dimensionality
4.6 Bit-by-bit versus block-orthogonal
4.7 Summary
4.8 Appendix: Isometries and error probability
4.9 Appendix: Bandwidth definitions
4.10 Exercises
5 Symbol-by-symbol on a pulse train: Second layer revisited
5.1 Introduction
5.2 The ideal lowpass case
5.3 Power spectral density
5.4 Nyquist criterion for orthonormal bases
5.5 Root-raised-cosine family
5.6 Eye diagrams
5.7 Symbol synchronization
5.7.1 Maximum likelihood approach
5.7.2 Delay locked loop approach
5.8 Summary
5.9 Appendix: C2,and Lebesgue integral: A primer
5.10 Appendix: Fourier transform: A review
5.11 Appendix: Fourier series: A review
5.12 Appendix: Proof of the sampling theorem
5.13 Appendix: A review of stochastic processes
5.14 Appendix: Root-raised-cosine impulse response
5.15 Appendix: The picket fence “miracle”
5.16 Exercises
6 Convolutional coding and Viterbi decoding: First layer revisited
6.1 Introduction
6.2 The encoder
6.3 The decoder
6.4 Bit-error probability
6.4.1 Counting detours
6.4.2 Upper bound to Po
6.5 Summary
6.6 Appendix: Formal definition of the Viterbi algorithm
6.7 Exercises
7 Passband communication via up/down conversion: Third layer
7.1 Introduction
7.2 The baseband-equivalent of a passband signal
7.2.1 Analog amplitude modulations: DSB, AM, SSB, QAM
7.3 The third layer
7.4 Baseband-equivalent channel model
7.5 Parameter estimation
7.6 Non-coherent detection eot bmosse
7.7 Summary
7.8 Appendix: Relationship between real-and complex-valued operations
7.9 Appendix: Complex-valued random vectors
7.9.1 General statements
7.9.2 The Gaussian case
7.9.3 The circularly symmetric Gaussian case
7.10 Exercises
Bibliography
Index