Toward Energy-Efficient Dynamic Resource Allocation in Uplink NOMA Systems: Deep Reinforcement Learning for Single and Multi-Cell NOMA Systems

Ayman Rabee; Imad Barhumi

doi:10.1109/tvt.2025.3540940

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Toward Energy-Efficient Dynamic Resource Allocation in Uplink NOMA Systems: Deep Reinforcement Learning for Single and Multi-Cell NOMA Systems

Ayman Rabee Imad Barhumi

Year: 2025 Journal: IEEE Transactions on Vehicular Technology Vol: 74 (6)Pages: 9313-9327 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tvt.2025.3540940

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Keywords:

Noma Telecommunications link Reinforcement learning Computer science Energy (signal processing) Resource allocation Resource management (computing) Engineering Computer network Artificial intelligence

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Advanced Wireless Communication Technologies

Physical Sciences → Engineering → Electrical and Electronic Engineering

Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

Optical Wireless Communication Technologies

Physical Sciences → Engineering → Electrical and Electronic Engineering

Toward Energy-Efficient Dynamic Resource Allocation in Uplink NOMA Systems: Deep Reinforcement Learning for Single and Multi-Cell NOMA Systems

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