On Applications of Machine Learning In IRS NOMA Architectures For 5G and Beyond

• Qatar Foundation - Researchers Exchange and Mobility Program (REMP) - The award was withdrawn due to COVID-19. (2023)

• Shehab, Muhammad; Elsayed, Mohamed; Almohamad, Abdullateef; Badawy, Ahmed; Khattab, ... (2024)
  Terahertz Multiple Access: A Deep Reinforcement Learning Controlled Multihop IRS Topology. In: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, vol. 5, pp. 1072-1087. ISSN 2644-125X
  Contributo su Rivista
• Shehab, Muhammad (2024)
  On Applications of Machine Learning In IRS NOMA Architectures For 5G and Beyond. relatore: TRINCHERO, Daniele; , 36. XXXVI Ciclo, P.: 134
  Doctoral Thesis
• Shehab, Muhammad; Badawy, Ahmed; Elsayed, Mohamed; Khattab, Tamer; Trinchero, Daniele (2023)
  DDPG Performance in THz Communications over Cascaded RISs: A Machine Learning Solution to the Over-Determined System. In: 2023 International Wireless Communications and Mobile Computing (IWCMC), Marrakesh, Morocco, 19-23 June 2023, pp. 210-215. ISBN: 979-8-3503-3339-8
  Contributo in Atti di Convegno (Proceeding)
• Shehab, Muhammad; Trinchero, Daniele (2022)
  Deep Reinforcement Learning Powered IRS-Assisted Downlink NOMA. In: IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, vol. 3, pp. 729-739. ISSN 2644-125X
  Contributo su Rivista
• Shehab, Muhammad; Kassem, I.; Kutty, A. A.; Kucukvar, M.; Onat, N; Khattab, T. (2022)
  5G Networks Towards Smart and Sustainable Cities: A Review of Recent Developments, Applications and Future Perspectives. In: IEEE ACCESS, vol. 10, pp. 2987-3006. ISSN 2169-3536
  Contributo su Rivista
• Shehab, Muhammad; Khattab, Tamer; Kucukvar, Murat; Trinchero, Daniele (2022)
  The Role of 5G/6G Networks in Building Sustainable and Energy-Efficient Smart Cities. In: 2022 IEEE 7th International Energy Conference (ENERGYCON), Riga, Latvia, 09-12 May 2022, pp. 1-7. ISBN: 978-1-6654-7982-0
  Contributo in Atti di Convegno (Proceeding)