Joint Beamforming and Trajectory Optimization for Multi-UAV-Assisted Integrated Sensing and Communication Systems

In this paper, we investigate beamforming design and trajectory optimization for a multi-unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) system, where multiple UAVs equipped with dual-functional radar-communication capabilities provide communication and sensing services simultaneously. In contrast to existing ISAC systems that mainly focus on single-UAV scenarios, this study explicitly considers multi-UAV coordination, jointly optimizing the beamforming and trajectory of UAVs. We formulate a joint optimization problem to maximize the sum rate of users while maintaining the target sensing performance. To address this challenging non-convex problem, we develop a block coordinate descent (BCD)-based iterative algorithm, where the beamforming design problem is addressed using fractional programming, while the UAV trajectory is refined through the deep deterministic policy gradient (DDPG) algorithm. The simulation results demonstrate that the proposed joint optimization approach achieves significant performance improvements in both communication throughput and sensing accuracy compared to conventional, separated designs. We also show that proper coordination of multiple UAVs through optimized trajectories and beamforming patterns can effectively balance the tradeoff between sensing and communication objectives.