SHEHAB, MUHAMMAD

SHEHAB, MUHAMMAD  

Dipartimento di Elettronica e Telecomunicazioni  

070891  

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Citazione Data di pubblicazione Autori File
Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology / Shehab, Muhammad; Elsayed, Mohamed; Almohamad, Abdullateef; Badawy, Ahmed; Khattab, Tamer; Zorba, Nizar; Hasna, Mazen; Trinchero, Daniele. - In: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY. - ISSN 2644-125X. - ELETTRONICO. - 5:(2024), pp. 1072-1087. [10.1109/OJCOMS.2024.3357701] 1-gen-2024 Shehab, MuhammadBadawy, AhmedTrinchero, Daniele + Trinchero-Terahertz.pdfTrinchero-Terahertz_editoriale.pdf
5G Networks Towards Smart and Sustainable Cities: A Review of Recent Developments, Applications and Future Perspectives / Shehab, Muhammad; Kassem, I.; Kutty, A. A.; Kucukvar, M.; Onat, N; Khattab, T.. - In: IEEE ACCESS. - ISSN 2169-3536. - ELETTRONICO. - 10:(2022), pp. 2987-3006. [10.1109/ACCESS.2021.3139436] 1-gen-2022 Shehab, Muhammad + 5G_Networks_Towards_Smart_and_Sustainable_Cities_A_Review_of_Recent_Developments_Applications_and_Future_Perspectives.pdf
Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA / Shehab, Muhammad; Trinchero, Daniele. - In: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY. - ISSN 2644-125X. - ELETTRONICO. - 3:(2022), pp. 729-739. [10.1109/OJCOMS.2022.3165590] 1-gen-2022 Muhammad ShehabDaniele Trinchero Shehab-Deep.pdf