AI empowered wireless communications: from bits to semantics
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Author(s)
Type
Journal Article
Abstract
Artificial intelligence (AI) and machine learning (ML) have shown tremendous potential in reshaping the landscape of wireless communications and are, therefore, widely expected to be an indispensable part of the next-generation wireless network. This article presents an overview of how AI/ML and wireless communications interact synergistically to improve system performance and provides useful tips and tricks on realizing such performance gains when training AI/ML models. In particular, we discuss in detail the use of AI/ML to revolutionize key physical layer and lower medium access control (MAC) layer functionalities in traditional wireless communication systems. In addition, we provide a comprehensive overview of the AI/ML-enabled semantic communication systems, including key techniques from data generation to transmission. We also investigate the role of AI/ML as an optimization tool to facilitate the design of efficient resource allocation algorithms in wireless communication networks at both bit and semantic levels. Finally, we analyze major challenges and roadblocks in applying AI/ML in practical wireless system design and share our thoughts and insights on potential solutions.
Date Issued
2024-07-01
Date Acceptance
2024-07-22
Citation
Proceedings of the IEEE, 2024, 112 (7), pp.621-652
ISSN
0018-9219
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
621
End Page
652
Journal / Book Title
Proceedings of the IEEE
Volume
112
Issue
7
Copyright Statement
© 2024 The Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
License URL
Identifier
10.1109/JPROC.2024.3437730
Publication Status
Published
Date Publish Online
2024-08-20