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Generative AI-driven reinforcement learning for beamforming and scheduling in multi-cell MIMO-NOMA systems

Abuzar B. M. AdamInterdisciplinary Centre for Security, Reliability and Trust (SnT), University of Luxembourg, 1855 Luxembourg City, LuxembourgElhadj Moustapha DialloSchool of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, ChinaMohammed Saleh Ali MuthannaDepartment of International Business Management, Tashkent State University of Economics, Tashkent 100066, UzbekistanReem AlkanhelDepartment of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi ArabiaAmmar MuthannaPeoples’ Friendship University of Russia (RUDN University), 117198 Moscow, RussiaMohammad HammoudehInformation and Computer Science Department, King Fahd University of Petroleum and Minerals, Academic Belt Road, Dhahran, Saudi Arabia
Physical Communicationjournal2025en
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