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.
Inhaltsangabe
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.
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.
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