Joint Beamforming Design and Trajectory Optimization for UAV-Enabled Cell-Free ISAC MIMO Systems

This paper presents a comprehensive investigation into beamforming design and trajectory optimization for integrated sensing and communication (ISAC) systems under a cell-free architecture, supported by multiple unmanned aerial vehicles (UAVs). To effectively incorporate sensing into communication tasks, we propose an efficient tracking scheme based on the extended Kalman filter (EKF) to estimate the positions of mobile user equipments (UEs), which are then used for beamforming design and trajectory optimization. The originally complex non-convex optimization problem is decomposed into several tractable subproblems, which are efficiently addressed using the block coordinate descent (BCD) method and fractional programming (FP). Numerical simulations validate the effectiveness of the proposed framework, demonstrating notable improvements in both average sum-rate and sensing accuracy.