近十年来，数字通信技术发展迅猛，已经深入人们日常生活的每个角落。如宽带上网、手机、数字电视等。受这些应用的驱使，大量人才投身数字通信行业，但他们常常被通信理论所需的数学知识吓倒。

Madhow博士拥有多年科研和教学工作经验，深知如何通过讲解实例来减轻这种恐惧。本书旨在保持知识严谨性的同时，通过各种方式让读者轻松掌握通信理论。书中首先建立了调制和解调的经典基础概念，接着介绍了同步、非相干通信、信道均衡、信息论、信道编码、无线通信等高级概念；此外，还涵盖了Turbo码和LDPC码的相关内容，读者既可以据此实现并进行性能评估，也可以仅仅以它们为性能基准进行性能对比。

本书阐述了现代数字通信系统设计的基本知识，主要内容有：信号和噪声的复基带表述，调制和调解，分散信道通信，用信息理论计算性能基准点，现代解码方法基础知识，无线通信简介。书中实例丰富，每章还配有练习题，帮助读者深刻理解重要通信原理。

本书是通信专业高年级本科生和研究生教材，也可供工程技术人员参考。

1　Introduction

　1.1　Components of a digital communication system

　1.2　Text outline

　1.3　Further reading

2　Modulation

　2.1　Preliminaries

　2.2　Complex baseband representation

　2.3　Spectral description of random processes

　　2.3.1　Complex envelope for passband random processes

　2.4　Modulation degrees of freedom

　2.5　Linear modulation

　　2.5.1　Examples of linear modulation

　　2.5.2　Spectral occupancy of linearly modulated signals

　　2.5.3　The Nyquist criterion: relating bandwidth to symbol rate

　　2.5.4　Linear modulation as a building block

　2.6　Orthogonal and biorthogonal modulation

　2.7　Differential modulation

　2.8　Further reading

　2.9　Problems

　　2.9.1　Signals and systems

　　2.9.2　Complex baseband representation

　　2.9.3　Random processes

　　2.9.4　Modulation

3　Demodulation

　3.1　Gaussian basics

　3.2　Hypothesis testing basics

　3.3　Signal space concepts

　3.4　Optimal reception in AWGN

　　3.4.1　Geometry of the ML decision rule

　　3.4.2　Soft decisions

　3.5　Performance analysis of ML reception

　　3.5.1　Performance with binary signaling

　　3.5.2　Performance with M-ary signaling

　3.6　Bit-level demodulation

　　3.6.1　Bit-level soft decisions

　3.7　Elements of link budget analysis

　3.8　Further reading

　3.9　Problems

　　3.9.1　Gaussian basics

　　3.9.2　Hypothesis testing basics

　　3.9.3　Receiver design and performance analysis for the AWGN channel

　　3.9.4　Link budget analysis

　　3.9.5　Some mathematical derivations

4　Synchronization and noncoherent communication

　4.1　Receiver design requirements

　4.2　Parameter estimation basics

　　4.2.1　Likelihood function of a signal in AWGN

　4.3　Parameter estimation for synchronization

　4.4　Noncoherent communication

　　4.4.1　Composite hypothesis testing

　　4.4.2　Optimal noncoherent demodulation

　　4.4.3　Differential modulation and demodulation

　4.5　Performance of noncoherent communication

　　4.5.1　Proper complex Gaussianity

　　4.5.2　Performance of binary noncoherent communication

　　4.5.3　Performance of M-ary noncoherent orthogonal signaling

　　4.5.4　Performance of DPSK

　　4.5.5　Block noncoherent demodulation

　4.6　Further reading

　4.7　Problems

5　Channel equalization

　5.1　The channel model

　5.2　Receiver front end

　5.3　Eye diagrams

　5.4　Maximum likelihood sequence estimation

　　5.4.1　Alternative MLSE formulation

　5.5　Geometric model for suboptimal equalizer design

　5.6　Linear equalization

　　5.6.1　Adaptive implementations

　　5.6.2　Performance analysis

　5.7　Decision feedback equalization

　　5.7.1　Performance analysis

　5.8　Performance analysis of MLSE

　　5.8.1　Union bound

　　5.8.2　Transfer function bound

　5.9　Numerical comparison of equalization techniques

　5.10　Further reading

　5.11　Problems

　　5.11.1　MLSE

6　Information-theoretic limits and their computation

　6.1　Capacity of AWGN channel: modeling andgeometry

　　6.1.1　From continuous to discrete time

　　6.1.2　Capacity of the discrete-time AWGN channel

　　6.1.3　From discrete to continuous time

　　6.1.4　Summarizing the discrete-time AWGN model

　6.2　Shannon theory basics

　　6.2.1　Entropy, mutual information, and divergence

　　6.2.2　The channel coding theorem

　6.3　Some capacity computations

　　6.3.1　Capacity for standard constellations

　　6.3.2　Parallel Gaussian channels and waterfilling

　6.4　Optimizing the input distribution

　　6.4.1　Convex optimization

　　6.4.2　Characterizing optimal input distributions

　　6.4.3　Computing optimal input distributions

　6.5　Further reading

　6.6　Problems

7　Channel coding

　7.1　Binary convolutional codes

　　7.1.1　Nonrecursive nonsystematic encoding

　　7.1.2　Recursive systematic encoding

　　7.1.3　Maximum likelihood decoding

　　7.1.4　Performance analysis of ML decoding

　　7.1.5　Performance analysis for quantized observations

　7.2　Turbo codes and iterative decoding

　　7.2.1　The BCJR algorithm: soft-in, soft-out decoding

　　7.2.2　Logarithmic BCJR algorithm

　　7.2.3　Turbo constructions from convolutional codes

　　7.2.4　The BER performance of turbo codes

　　7.2.5　Extrinsic information transfer charts

　　7.2.6　Turbo weight enumeration

　7.3　Low density parity check codes

　　7.3.1　Some terminology from coding theory

　　7.3.2　Regular LDPC codes

　　7.3.3　Irregular LDPC codes

　　7.3.4　Message passing and density evolution

　　7.3.5　Belief propagation

　　7.3.6　Gaussian approximation

　7.4　Bandwidth-efficient coded modulation

　　7.4.1　Bit interleaved coded modulation

　　7.4.2　Trellis coded modulation

　7.5　Algebraic codes

　7.6　Further reading

　7.7　Problems

8　Wireless communication

　8.1　Channel modeling

　8.2　Fading and diversity

　　8.2.1　The problem with Rayleigh fading

　　8.2.2　Diversity through coding and interleaving

　　8.2.3　Receive diversity

　8.3　Orthogonal frequency division multiplexing

　8.4　Direct sequence spread spectrum

　　8.4.1　The rake receiver

　　8.4.2　Choice of spreading sequences

　　8.4.3　Performance of conventional reception in CDMA systems

　　8.4.4　Multiuser detection for DS-CDMA systems

　8.5　Frequency hop spread spectrum

　8.6　Continuous phase modulation

　　8.6.1　Gaussian MSK2

　　8.6.2　Receiver design and Laurent's expansion

　8.7　Space–time communication

　　8.7.1　Space–time channel modeling

　　8.7.2　Information-theoretic limits

　　8.7.3　Spatial multiplexing

　　8.7.4　Space–time coding

　　8.7.5　Transmit beamforming

　8.8　Further reading

　8.9　Problems

Appendix A　Probability, random variables, and random processes

　A.1　Basic probability

　A.2　Random variables

　A.3　Random processes

　　A.3.1　Wide sense stationary random processes through LTI systems

　　A.3.2　Discrete-time random processes

　A.4　Further reading

Appendix B　The Chernoff bound

Appendix C　Jensen's inequality

References

Index