AI 中文总结
针对车载网络多基地ISAC的混合波束成形问题，提出PI-LPPO算法，可控制中断概率在阈值内、提升约束满足度并实现稳定感知性能。
AI 中文摘要
本研究针对车载网络中收发信机分离的多基地集成感知与通信（ISAC），研究可靠性约束下的混合波束成形问题。在中断概率、发射功率及模拟恒模约束下，构建目标位置克拉美罗下界最小化问题。为求解该带约束非凸问题，提出比例积分拉格朗日近端策略优化（PI-LPPO）算法。仿真结果表明，该算法可将平均中断概率控制在可靠性阈值（约8%-10%）及以下，提升约束满足度，并实现稳定的感知性能。
英文摘要
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.
Comments4 pages, 3 figures
