This paper investigates the resource allocation optimization for cooperative communication with non-cooperative localization in integrated sensing and communications (ISAC)-enabled multi-unmanned aerial vehicle (UAV) cooperative networks. Our goal is to maximize the weighted sum of the system's average sum rate and the localization quality of service (QoS) by jointly optimizing cell association, communication power allocation, and sensing power allocation. Since the formulated problem is a mixed-integer nonconvex problem, we propose the alternating iteration algorithm based on optimal transport theory (AIBOT) to solve the optimization problem more effectively. Simulation results demonstrate that the AIBOT can improve the system sum rate by nearly 12% and reduce the localization Cr'amer-Rao bound (CRB) by almost 29% compared to benchmark algorithms.

翻译：本文研究了集成感知与通信(ISAC)多无人机协同网络中，非合作定位场景下的协作通信资源分配优化问题。我们的目标是通过联合优化小区关联、通信功率分配与感知功率分配，最大化系统平均总速率与定位服务质量(QoS)的加权和。由于所构建问题属于混合整数非凸优化问题，本文提出基于最优传输理论的交替迭代算法(AIBOT)以更有效地求解该优化问题。仿真结果表明，与基准算法相比，AIBOT可使系统总速率提升近12%，并将定位克拉美-罗界(CRB)降低约29%。