Network information theory

This comprehensive treatment of network information theory and its applications provides the first unified coverage of both classical and recent results. With an approach that balances the introduction of new models and new coding techniques, readers are guided through Shannon's point-to-point information theory, single-hop networks, multi-hop networks, and extensions to distributed computing, secrecy, wireless communication and networking. Elementary mathematical tools and techniques are used throughout, requiring only basic knowledge of probability, whilst unified proofs of coding theorems are based on a few simple lemmas, making the text accessible to newcomers. Key topics covered include successive cancellation and superposition coding, MIMO wireless communication, network coding and cooperative relaying. Also covered are feedback and interactive communication, capacity approximations and scaling laws, and asynchronous and random access channels. Featuring a wealth of illustrations, worked examples, bibliographic notes and over 250 problems, this book is ideal for use in the classroom and for self-study.

Information measures and typicality -- Point-to-point information theory -- Multiple access channels -- Degraded broadcast channels -- Interference channels -- Channels with state -- General broadcast channels -- Gaussian vector channels -- Distributed lossless compression -- Lossy compression with side information -- Distributed lossy compression -- Multiple description coding -- Joint source-channel coding -- Graphical networks -- Relay channels -- Interactive channel coding -- Discrete memoryless networks -- Gaussian networks -- Compression over graphical networks -- Communication for computing -- Information theoretic secrecy -- Wireless fading channels -- 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.