Fr. 96.00

Network Information Theory

English · Paperback / Softback

Shipping usually within 1 to 3 weeks (not available at short notice)

Description

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The first complete and unified coverage of both classical and recent results, including numerous worked examples and over 250 exercises.

List of contents










1. Introduction; Part I. Preliminaries: 2. Information measures and typicality; 3. Point-to-point information theory; Part II. Single-Hop Networks: 4. Multiple access channels; 5. Degraded broadcast channels; 6. Interference channels; 7. Channels with state; 8. General broadcast channels; 9. Gaussian vector channels; 10. Distributed lossless compression; 11. Lossy compression with side information; 12. Distributed lossy compression; 13. Multiple description coding; 14. Joint source-channel coding; Part III. Multihop Networks: 15. Graphical networks; 16. Relay channels; 17. Interactive channel coding; 18. Discrete memoryless networks; 19. Gaussian networks; 20. Compression over graphical networks; Part IV. Extensions: 21. Communication for computing; 22. Information theoretic secrecy; 23. Wireless fading channels; 24. Networking and information theory; Appendices: A. Convex sets and functions; B. Probability and estimation; C. Cardinality bounding techniques; D. Fourier-Motzkin elimination; E. Convex optimization.

About the author

Abbas El Gamal is the Hitachi America Chaired Professor in the School of Engineering and the Chair of the Department of Electrical Engineering at Stanford University, California. In the field of network information theory, he is best known for his seminal contributions to the relay, broadcast, and interference channels; multiple description coding; coding for noisy networks; and energy-efficient packet scheduling and throughput-delay tradeoffs in wireless networks. He is a Fellow of the Institute of Electrical and Electronics Engineers and the winner of the 2012 Claude E. Shannon Award, the highest honor in the field of information theory.Young-Han Kim is an Associate Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego. His research focuses on information theory and statistical signal processing. He is a recipient of the 2012 Institute of Electrical and Electronics Engineers Information Theory Paper Award and the 2008 National Science Foundation Faculty Early Career Development (CAREER) Award.

Summary

Providing a coherent and accessible presentation of the field, this is the first complete and unified coverage of both classical and recent results. Featuring a wealth of illustrations, worked examples, bibliographic notes and over 250 end-of-chapter problems, this book is ideal for students, researchers and practitioners alike.

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