Simulation results show that the proposed proportional-integral Lagrangian proximal policy optimization algorithm keeps the average outage probability at or below the reliability threshold, improves constraint satisfaction, and achieves stable sensing performance.
Abstract
This letter investigates reliability constrained hybrid beamforming for transceiver separated multistatic integrated sensing and communication in vehicular networks. A target position Cramer Rao bound minimization problem is formulated under outage probability, transmit-power, and analog constant modulus constraints. To handle the constrained non convex problem, we develop a proportional-integral Lagrangian proximal policy optimization algorithm. Simulation results show that the proposed algorithm keeps the average outage probability at or below the reliability threshold, around 8%-10%, improves constraint satisfaction, and achieves stable sensing performance.
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