- 数字通信基础(英文版)
- - 作者：(美)乌帕马尼亚·麦德豪|责编:陈亮//夏丹
  - 出版社：世界图书出版公司
  - ISBN：9787519212452
  - 出版日期：2020/07/01
  - 页数：499
- 售价：55.2

内容大纲
本书是一本讲授数字通信系统设计基础概念与原理的简明教程。书中有大量从简单到最前沿的实例来展示理论是如何指导实践的。读者可以用计算和模拟来实现书中的算法，由此来理解其背后的理论。本书包含5G通信所使用的Turbo码和LDPC码等前沿内容，读者可以自己编程去实现性能评估与比较。本书还包括空时通信技术和对非相干通信和均衡的几何解释等特色内容。本书既可作为通信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。
作者介绍
乌帕马尼亚·麦德豪（Upamanyu Madhow）是美国加州大学圣芭芭拉分校电子与计算机工程系的教投。他是三家无线通信初创公司的共同创始人，并持有14项美国专利。麦德豪教授是国际电气电子工程师学会的杰出会士（IEEE Fellow），担任过IEEE Transactions on Information Theory, IEEE Transactions on Communications, IEEE Transactions on Information Forensics and Securiy等多家权成期刊的副主编。麦德豪教投还获得过IEEE无线通信最佳论文奖（IEEE Marconi Prize Paper Award in Wreless Communications），并入选ISI全球高引用科学家名单（ISI HighlyCited Researcher）。
目录
Preface
Acknowledgements
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 communieation
  4.5  .]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 demoxdulation
  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 and geometry
    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 MSK
    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 proceses
  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 Chenoff bound
Appendix C  Jensen's inequality
References
Index

内容大纲

作者介绍

目录

同类热销排行榜

推荐书目