Reprint

Information Theory for Data Communications and Processing

Edited by
January 2021
294 pages
  • ISBN978-3-03943-817-4 (Hardback)
  • ISBN978-3-03943-818-1 (PDF)

This book is a reprint of the Special Issue Information Theory for Data Communications and Processing that was published in

Chemistry & Materials Science
Computer Science & Mathematics
Physical Sciences
Summary
Modern, current, and future communications/processing aspects motivate basic information-theoretic research for a wide variety of systems for which we do not have the ultimate theoretical solutions (for example, a variety of problems in network information theory as the broadcast/interference and relay channels, which mostly remain unsolved in terms of determining capacity regions and the like). Technologies such as 5/6G cellular communications, Internet of Things (IoT), and mobile edge networks, among others, not only require reliable rates of information measured by the relevant capacity and capacity regions, but are also subject to issues such as latency vs. reliability, availability of system state information, priority of information, secrecy demands, energy consumption per mobile equipment, sharing of communications resources (time/frequency/space), etc. This book, composed of a collection of papers that have appeared in the Special Issue of the Entropy journal dedicated to “Information Theory for Data Communications and Processing”, reflects, in its eleven chapters, novel contributions based on the firm basic grounds of information theory. The book chapters address timely theoretical and practical aspects that constitute both interesting and relevant theoretical contributions, as well as direct implications for modern current and future communications systems.
Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
computer-aided analysis; information theory; network slicing; RoC; URLLC; eMBB; C-RAN; Gaussian multiple access channel; one-bit quantizer; capacity region; capacity; decode-forward; multicast; relaying; MIMO; channel capacity; amplitude constraint; input distrbution; capacity bounds; CEO problem; mean squared error; multiterminal source coding; rate-distortion; remote source coding; caching networks; random fractional caching; coded caching; coded multicasting; index coding; finite-length analysis; graph coloring; approximation algorithms; robust compression; congestion; packet-based fronthaul; multiple description coding; cloud radio access network; broadcast coding; eCPRI; ultra dense network; cross-entropy; proactive caching; user association; CoMP; information bottleneck; rate distortion theory; logarithmic loss; representation learning; clustering; unsupervised learning; Gaussian mixture model; information bottleneck; information theory; data communications; data processing