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Network Information Theory
Abstract
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, multihop 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. This book is ideal for use in the classroom, for self-study, and as a reference for researchers and engineers in industry and academia.
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Cited by
Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar
Liu, X., Huang, T., Shlezinger, N., Liu, Y., Zhou, J., & Eldar, Y. C. (2020) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2020.3004739 · Cited by 992
Wilde, M. M., Winter, A., & Yang, D. (2014) · Communications in Mathematical Physics · doi:10.1007/s00220-014-2122-x · Cited by 516
Task-Oriented Communication for Multidevice Cooperative Edge Inference
Shao, J., Mao, Y., & Zhang, J. (2023) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2022.3191118 · Cited by 209
Deep Learning for Distributed Channel Feedback and Multiuser Precoding in FDD Massive MIMO
Sohrabi, F., Attiah, K. M., & Yu, W. (2021) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2021.3055202 · Cited by 169
Distributed Variational Representation Learning
Aguerri, I. E., & Zaidi, A. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2928806 · Cited by 84
Metadata
- Authors
- El Gamal, A., & Kim, Y.-H.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 2011-12-08
- OpenAlex
- W4300840296
- Cited by
- 2,716
- References
- 0
- FWCI
- 109.41
- Type
- book
- Language
- en
- Open access
- closed
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