A DRL agent learns a direct mapping from channel state information to near-optimal beamforming and hybrid RIS configurations, reaching 95% of the spectral efficiency of alternating optimization at far lower runtime complexity.
A survey on model-based, heuristic, and machine learning optimization approaches in ris-aided wireless networks,
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Deep Reinforcement Learning for Hybrid RIS Assisted MIMO Communications
A DRL agent learns a direct mapping from channel state information to near-optimal beamforming and hybrid RIS configurations, reaching 95% of the spectral efficiency of alternating optimization at far lower runtime complexity.