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eess.SP2025

On Energy-Efficient Passive Beamforming Design of RIS-Assisted CoMP-NOMA Networks

Muhammad Umer, Muhammad Ahmed Mohsin, Aamir Mahmood +4

This paper investigates the synergistic potential of reconfigurable intelligent surfaces (RIS) and non-orthogonal multiple access (NOMA) to enhance the energy efficiency and perfor…

eess.SP2025

Continual Learning for Wireless Channel Prediction

Muhammad Ahmed Mohsin, Muhammad Umer, Ahsan Bilal +2

Modern 5G/6G deployments routinely face cross-configuration handovers--users traversing cells with different antenna layouts, carrier frequencies, and scattering statistics--which…

eess.SP2025

Resource Allocation for RIS-Assisted CoMP-NOMA Networks using Reinforcement Learning

Muhammad Umer, Muhammad Ahmed Mohsin, Huma Ghafoor +1

This thesis delves into the forefront of wireless communication by exploring the synergistic integration of three transformative technologies: STAR-RIS, CoMP, and NOMA. Driven by t…

eess.SP2025

Intelligent Spectrum Sharing in Integrated TN-NTNs: A Hierarchical Deep Reinforcement Learning Approach

Muhammad Umer, Muhammad Ahmed Mohsin, Ali Arshad Nasir +2

Integrating non-terrestrial networks (NTNs) with terrestrial networks (TNs) is key to enhancing coverage, capacity, and reliability in future wireless communications. However, the…

eess.SP2025

Hierarchical Deep Reinforcement Learning for Adaptive Resource Management in Integrated Terrestrial and Non-Terrestrial Networks

Muhammad Ahmed Mohsin, Hassan Rizwan, Muhammad Umer +3

Efficient spectrum allocation has become crucial as the surge in wireless-connected devices demands seamless support for more users and applications, a trend expected to grow with…