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Article Dans Une Revue Frontiers in Communications and Networks Année : 2021

Machine Learning: A Catalyst for THz Wireless Networks

Résumé

With the vision to transform the current wireless network into a cyber-physical intelligent platform capable of supporting bandwidth-hungry and latency-constrained applications, both academia and industry turned their attention to the development of artificial intelligence (AI) enabled terahertz (THz) wireless networks. In this article, we list the applications of THz wireless systems in the beyond fifth generation era and discuss their enabling technologies and fundamental challenges that can be formulated as AI problems. These problems are related to physical, medium/multiple access control, radio resource management, network and transport layer. For each of them, we report the AI approaches, which have been recognized as possible solutions in the technical literature, emphasizing their principles and limitations. Finally, we provide an insightful discussion concerning research gaps and possible future directions.
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hal-04488137 , version 1 (02-04-2024)

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Alexandros-Apostolos Boulogeorgos, Edwin Yaqub, Marco Di Renzo, Angeliki Alexiou, Rachana Desai, et al.. Machine Learning: A Catalyst for THz Wireless Networks. Frontiers in Communications and Networks, 2021, 2, ⟨10.3389/frcmn.2021.704546⟩. ⟨hal-04488137⟩
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