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.
Sensing-communication-computing-control closed-loop optimization for 6G digital twin-empowered robotic systems,
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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.