A DQN-based controller dynamically selects CU/DU placement and functional split in hybrid non-terrestrial O-RAN and reports 20 percent lower normalized power than a baseline in simulation.
Energy-aware dynamic vnf splitting in o-ran using deep reinforcement learning,
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Energy-efficient Deep Reinforcement Learning-based Network Function Disaggregation in Hybrid Non-terrestrial Open Radio Access Networks
A DQN-based controller dynamically selects CU/DU placement and functional split in hybrid non-terrestrial O-RAN and reports 20 percent lower normalized power than a baseline in simulation.