期刊
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
卷 41, 期 1, 页码 5-41出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSAC.2022.3223408
关键词
6G; semantic communications; semantic distortion; goal-oriented communications; joint source-channel coding; deep learning (DL); rate-distortion theory; information bottleneck (IB); pragmatic communications; remote inference; distributed learning
This tutorial summarizes the efforts in communication systems to integrate message semantics and goals of communication into their designs, as well as incorporating the context of communication exchange. It covers the foundations, algorithms, and potential implementations, with a focus on utilizing information theory and learning in semantics and task-aware communications.
Communication systems to date primarily aim at reliably communicating bit sequences. Such an approach provides efficient engineering designs that are agnostic to the meanings of the messages or to the goal that the message exchange aims to achieve. Next generation systems, however, can be potentially enriched by folding message semantics and goals of communication into their design. Further, these systems can be made cognizant of the context in which communication exchange takes place, thereby providing avenues for novel design insights. This tutorial summarizes the efforts to date, starting from its early adaptations, semantic-aware and task-oriented communications, covering the foundations, algorithms and potential implementations. The focus is on approaches that utilize information theory to provide the foundations, as well as the significant role of learning in semantics and task-aware communications.
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