Machine Learning: A Catalyst for THz Wireless Networks - Boulogeorgos, Alexandros-Apostolos A.; Yaqub, Edwin; di Renzo, Marco; Alexiou, Angeliki; Desai, Rachana; Klinkenberg, Ralf (Frontiers in Communications and Networks, 2021)
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 categorized into the physical layer, medium, and multiple access control, resource allocation and management, network and transport layer related ones. 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.