A replication study of PPO and ACER for O-RAN resource allocation that qualitatively claims DRL beats greedy, but contains an internal contradiction and no quantitative results.
”Reinforcement learning-based mobile edge com- puting and transmission scheduling for video surveillance.” IEEE Trans- actions on Emerging Topics in Computing , pages 1–1, 2021
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Dynamics of Resource Allocation in O-RANs: An In-depth Exploration of On-Policy and Off-Policy Deep Reinforcement Learning for Real-Time Applications
A replication study of PPO and ACER for O-RAN resource allocation that qualitatively claims DRL beats greedy, but contains an internal contradiction and no quantitative results.