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.
The role and use of the stochastic linear-quadratic-Gaussian problem in control system design,
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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.