PPO-based bandwidth allocation among collaborative sensors, using mutual-information distortion noise under Kalman–LQR control, lowers simulated LQR cost versus sensing- and rate-oriented baselines.
A systematic review on fusion techniques and approaches used in applications,
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Deep Reinforcement Learning-Empowered Wireless Sensor Networking for 6G Closed-Loop Controls
PPO-based bandwidth allocation among collaborative sensors, using mutual-information distortion noise under Kalman–LQR control, lowers simulated LQR cost versus sensing- and rate-oriented baselines.