Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

To process and transfer large amounts of data in emerging wireless services, it has become increasingly appealing to exploit distributed data communication and learning. Specifically, edge learning (EL) enables local model training on geographically disperse edge nodes and minimizes the need for fre...

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Bibliographic Details
Published in:	IEEE journal of selected topics in signal processing Vol. 17; no. 1; pp. 9 - 39
Main Authors:	Xu, Wei, Yang, Zhaohui, Ng, Derrick Wing Kwan, Levorato, Marco, Eldar, Yonina C., Debbah, Merouane
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial intelligence (AI) beyond 5G (B5G) Communication Communication networks communication optimization Communications networks Communications systems Data communication Data exchange Deep learning deep learning (DL) Edge computing edge learning (EL) Entropy (Information theory) federated learning (FL) Information theory Internet-of-Everything (IoE) Learning Mathematical models Measurement multi-agent reinforcement learning (MARL) Optimization Performance measurement Reinforcement learning Semantics Signal processing Signal processing algorithms Training Wireless communication Wireless communications Wireless networks
ISSN:	1932-4553, 1941-0484
Online Access:	Get full text
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