Adaptive Beamforming for Low-Power IoT Networks: A Reinforcement Learning Approach

PAP-002Adaptive Beamforming for Low-Power IoT Networks: A Reinforcement Learning ApproachJournal of Applied Computing (Demo)We present a reinforcement-learning framework for adaptive beamforming in dense low-power IoT deployments, reducing energy per delivered bit by 34% in simulation across three interference regimes.Test AuthorSample University10.0000/pap-002