P. P. Vaidyanathan, See-May Phoong, Yuan-Pei LinCambridge University PressEdition: Illustrated, 3/11/2010EAN 9780521760799, ISBN10: 0521760798Hardcover, 874 pages, 25.4 x 18 x 4.3 cmLanguage: EnglishPresenting the first complete treatment of MIMO transceiver optimization, this self-contained book provides all the mathematical information needed to understand transceiver optimization in a single volume. It begins with a review of digital communication fundamentals, and then moves on to a detailed study of joint transceiver optimization, starting from simple single-input single-output channels all the way to minimum bit error rate transceivers for MIMO channels. Crucial background material is covered, such as Schur convex functions, matrix calculus, and constrained optimization, together with eight appendices providing further background material on topics such as matrix theory, random processes, and sampling theory. A final ninth appendix provides a grand summary of all the optimization results. With 360 illustrations, over 70 worked examples, and numerous summary tables provided to aid understanding of key concepts, this book is ideal for graduate students, practitioners, and researchers in the fields of communications and signal processing.Part I. Communication Fundamentals1. Introduction2. Review of basic ideas from digital communication3. Digital communication systems and filter banks4. Discrete time representations5. Classical transceiver techniques6. Channel capacity7. Channel equalization with transmitter redundancy8. The lazy precoder with a zero-forcing equalizerPart II. Transceiver Optimization9. History and outline10. Single-input single-output transceiver optimization11. Optimal transceivers for diagonal channels12. MMSE transceivers with zero-forcing equalizers13. MMSE transceivers without zero forcing14. Bit allocation and power minimization15. Transceivers with orthonormal precoders16. Minimization of error probability in transceivers17. Optimization of cyclic prefix transceivers18. Optimization of zero padded systems19. Transceivers with decision feedback equalizersPart III. Mathematical Background20. Matrix differentiation21. Convexity, Schur convexity and majorization theory22. Optimization with equality and inequality constraintsPart IV. AppendicesA. Inner products, norms, and inequalitiesB. Matricesa brief overviewC. Singular value decompositionD. Properties of pseudocirculant matricesE. Random processesF. Wiener filteringG. Review of concepts from sampling theoryH. Euclid's algorithmI. Transceiver optimizationSummary and tablesGlossary and acronymsBibliography.
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