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數字通信原理(自上而下的方法英文版)

  • 作者:(瑞士)比克西奧·里莫爾迪|責編:陳亮//夏丹
  • 出版社:世界圖書出版公司
  • ISBN:9787519220655
  • 出版日期:2020/07/01
  • 裝幀:平裝
  • 頁數:289
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內容大鋼
    本書內容全面,易於理解,通過自上而下的反向教學方法來講授數字通信的基礎知識。這種獨特的教學方法突出數字通信中的傳輸問題,在講述發射機之前先教授接收機的知識。這樣做直接切入了數字通信核心問題,使學生能以最少的背景知識快速、直觀地進行學習。從解碼器的決策問題開始,涵蓋不同通道的接收機設計、硬體設計折衷、卷積編碼與維特比解碼以及帶通通信,書中對系統級設計和實際工程應用進行了詳細講授,並且通過大量示例、作業問題和MATLAB模擬練習來幫助讀者自學。本書既可作為通信類專業高年級本科生和研究生教材,又可供工程技術人員參考。

作者介紹
(瑞士)比克西奧·里莫爾迪|責編:陳亮//夏丹
    比克西奧·里莫爾迪(Bixio Rimoldi)是瑞士洛桑聯邦理工學院的教授,並曾在美國華盛頓大學、斯坦福大學、麻省理工學院和加州大學伯克利分校任教。里莫爾迪教授是國際電氣電子工程師學會的傑出會士(IEEE Fellow),並曾擔任國際資訊理論學會的主席。

目錄
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

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