| Titre : | Principles of digital communication : a top-down approach / |
| Auteurs : | Bixio Rimoldi |
| Type de document : | Monographie imprimée |
| ISBN/ISSN/EAN : | 978-1-107-11645-0 |
| Format : | pages cm |
| Index. décimale : | 621.382 (Techniques des communications) |
| Catégories : |
[Agneaux] Computer networks. [Agneaux] Digital communications. |
| Résumé : |
This comprehensive and accessible text teaches the fundamentals of digital communication via a top-down-reversed approach, specifically formulated for a one-semester course. The unique approach focuses on the transmission problem and develops knowledge of receivers before transmitters. In doing so it cuts straight to the heart of the digital communication problem, enabling students to learn quickly, intuitively, and with minimal background knowledge. Beginning with the decision problem faced by a decoder and going on to cover receiver designs for different channels, hardware constraints, design trade-offs, convolutional coding, Viterbi decoding, and passband communication, detail is given on system-level design as well as practical applications in engineering. All of this is supported by numerous worked examples, homework problems, and MATLAB simulation exercises to aid self-study, providing a solid basis for students to specialize in the field of digital communication and making it suitable for both traditional and flipped classroom teaching. |
| Sommaire : |
Half-title
Endorsements Title page Copyright information Dedication Table of contents 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 n-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 differentiabletransformations 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: mathcal L[sub(2)], 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 P[sub(b)] 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 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 |
Disponibilité (1)
| Cote | Support | Localisation | Statut | Emplacement | |
|---|---|---|---|---|---|
| SI8/3018 | Livre | BIB.FAC.ST. | Empruntable | Magazin |
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