UAV-Assisted ISCC Networks: Joint Resource and Trajectory Optimization

This letter proposes a framework of unmanned aerial vehicle (UAV)-assisted integrated sensing, communication and computing (ISCC), where the treble-functional UAV performs radar detection, edge computing, with the computational assistance of ground access points for the tasks offloaded from the UAV. Since the UAV-assisted ISCC system has limited computing capability, the computing efficiency maximization problem is formulated by jointly optimizing UAV trajectory, beamforming vector, and offloading strategy, subject to the constraint on the required sensing threshold. To handle the intractable fractional programming problem, the Dinkelbach approach is used to transform it into a parametric problem, which is solved by the semi-definite programming method and the successive convex approximation. Then we propose a joint resource and trajectory optimization algorithm. Simulation results show the effectiveness of the proposed algorithm in terms of obtaining the optimized trajectory, beamforming vector, and offloading strategy compared to the benchmark schemes.