UAV Aided Integrated Sensing and Communications

This paper investigates an unmanned aerial vehicle (UAV) aided integrated radar sensing and communications (ISAC) network, where the UAV senses multiple targets via onboard radar devices and transmits the data to a ground base station (BS) for decision. The freshness of sensed data significantly affects the accuracy of BS decision and can be quantified by the peak age of information (PAoI). To guarantee the PAoI performance of the UAV-aided system, we design a joint optimization problem with consideration of the UAV trajectory, the scheduling order of the targets, and the time and power allocation for packet sensing and communication. Since the joint programming is a non-convex problem mainly due to the variable coupling and binary constraints, an efficient successive convex approximation (SCA) iterative algorithm is proposed, which transforms this non-convex problem into a convex problem with the help of fractional programming and penalty method. Simulation results show that the proposed algorithm outperforms the alternate optimization (AO) based algorithm in terms of the PAoI and convergence rate.