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Lattice coding for signals and networks : a structured coding approach to quantization, modulation, and multi-user information theory /
"Unifying information theory and digital communication through the language of lattice codes, this book provides a detailed overview for students, researchers and industry practitioners. It covers classical work by leading researchers in the field of lattice codes and complementary work on dith...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge :
Cambridge University Press,
2014.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Half title; Title; Copyright; Dedication; Contents; Preface; Acknowledgements; List of notation; 1 Introduction; 1.1 Source and channel coding; 1.2 The information theoretic view; 1.3 Structured codes; 1.4 Preview; 2 Lattices; 2.1 Representation; 2.2 Partition; 2.3 Equivalent cells and coset leaders; 2.4 Transformation and tiling; 2.5 Algebraic constructions; Summary; Problems; Interesting facts about lattices; 3 Figures of merit; 3.1 Sphere packing and covering; 3.2 Quantization: normalized second moment; 3.3 Modulation: volume to noise ratio; Summary; Problems; Historical notes.
- 4 Dithering and estimation4.1 Crypto lemma; 4.2 Generalized dither; 4.3 White dither spectrum; 4.4 Wiener estimation; 4.5 Filtered dithered quantization; Summary; Problems; Historical notes; 5 Entropy-coded quantization; 5.1 The Shannon entropy; 5.2 Quantizer entropy; 5.3 Joint and sequential entropy coding*; 5.4 Entropy-distortion trade-off; 5.5 Redundancy over Shannon; 5.6 Optimum test-channel simulation; 5.7 Comparison with Lloyd's conditions; 5.8 Is random dither really necessary?; 5.9 Universal quantization*; Summary; Problems; Historical notes.
- 6 Infinite constellation for modulation6.1 Rate per unit volume; 6.2 ML decoding and error probability; 6.3 Gap to capacity; 6.4 Non-AWGN and mismatch; 6.5 Non-equiprobable signaling; 6.6 Maximum a posteriori decoding*; Summary; Problems; Historical notes; 7 Asymptotic goodness; 7.1 Sphere bounds; 7.2 Sphere-Gaussian equivalence; 7.3 Good covering and quantization; 7.4 Does packing imply modulation?; 7.5 The Minkowski-Hlawka theorem; 7.6 Good packing; 7.7 Good modulation; 7.8 Non-AWGN; 7.9 Simultaneous goodness; Summary; Problems; Historical notes; 8 Nested lattices.
- 8.1 Definition and properties8.2 Cosets and Voronoi codebooks; 8.3 Nested linear, lattice and trellis codes; 8.4 Dithered codebook; 8.5 Good nested lattices; Summary; Problems; Historical notes; 9 Lattice shaping; 9.1 Voronoi modulation; 9.2 Syndrome dilution scheme; 9.3 The high SNR case; 9.4 Shannon meets Wiener (at medium SNR); 9.5 The mod channel; 9.6 Achieving C[sub(AWGN)] for all SNR; 9.7 Geometric interpretation; 9.8 Noise-matched decoding; 9.9 Is the dither really necessary?; 9.10 Voronoi quantization; Summary; Problems; Historical notes; 10 Side-information problems.
- 10.1 Syndrome coding10.2 Gaussian multi-terminal problems; 10.3 Rate distortion with side information; 10.4 Lattice Wyner-Ziv coding; 10.5 Channels with side information; 10.6 Lattice dirty-paper coding; Summary; Problems; Historical notes; 11 Modulo-lattice modulation; 11.1 Separation versus JSCC; 11.2 Figures of merit for JSCC; 11.3 Joint Wyner-Ziv/dirty-paper coding; 11.4 Bandwidth conversion; Summary; Problems; Historical notes; 12 Gaussian networks; 12.1 The two-help-one problem; 12.2 Dirty multiple-access channel; 12.3 Lattice network coding; 12.4 Interference alignment.