Fr. 193.20

Deep Reinforcement Learning for Reconfigurable Intelligent Surfaces and UAV Empowered Smart 6G Communications

Inglese · Copertina rigida

Spedizione di solito entro 3 a 5 settimane (il titolo viene procurato in modo speciale)

Descrizione

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This co-authored book explores the many challenges arising from real-time and autonomous decision-making for 6G by covering crucial advanced signal control and real-time decision-making methods for UAV- and RIS-assisted 6G wireless communications including the serious constraints in real-time optimisation problems.


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Antonino Masaracchia is a Lecturer at Queen Mary University of London. Previously, he was a research fellow at the Centre for Wireless Innovation at Queen's University Belfast, UK. His research activities are focused on optimal resource allocation for enabling URLLCs services in future 5G and 6G networks, and the investigation of innovative real-time optimisation systems for future wireless networks with digital twins. His research interests include digital twins, URLLCs, UAV communications, real-time optimisation, and AI and ML techniques for wireless communication networks. He has authored or co-authored 50+books, book chapters, journals, and conference papers. He has been awarded with the seal of excellence for the project proposal UAV-SURE and UAV-DRESS submitted under the Horizon 2020 s Marie Sklodowska-Curie actions call H2020-MSCA-IF-2020 (September 2020), and Horizon Europe Marie Skodowska-Curie Actions call HORIZON-MSCA-2021-PF-01-01 MSCA Postdoctoral Fellowships (October 2021), respectively.


Riassunto

This co-authored book explores the many challenges arising from real-time and autonomous decision-making for 6G by covering crucial advanced signal control and real-time decision-making methods for UAV- and RIS-assisted 6G wireless communications including the serious constraints in real-time optimisation problems.

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