Actor–Critic Reinforcement Learning for Throughput-Optimized Power Allocation in Energy Harvesting NOMA Relay-Assisted Networks

Actor–Critic Reinforcement Learning for Throughput-Optimized Power Allocation in Energy Harvesting NOMA Relay-Assisted Networks

In fifth-generation (5G) and beyond (B5G) communication systems, the growing number of connected devices and the increased traffic on the network lead to substantial energy consumption, which requires energy-efficient and high-speed communication solutions. Integrating non-orthogonal multiple access...

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Bibliographic Details
Main Authors: Faeik T. Al Rabee, Ala'Eddin Masadeh, Sharief Abdel-Razeq, Haythem Bany Salameh
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Open Journal of the Communications Society
Subjects:
Fifth-generation
NOMA
energy harvesting
millimeter-wave
power-minimization
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10787238/
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