Energy-Aware Resource Allocation and Trajectory Design for UAV-Enabled ISAC

In this paper, we investigate joint resource allocation and trajectory design for multi-user multi-target unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC). To be compatible with practical UAV-based sensing systems, sensing is carried out while the UAV hovers. In particular, we jointly optimize the two-dimensional trajectory, the velocity, and the downlink information and sensing beamformers of a fixed-altitude UAV for minimization of the average power consumption, while ensuring the quality of service of the communication users and the sensing tasks. To tackle the resulting non-convex mixed integer non-linear program (MINLP), we exploit semidefinite relaxation, the big-M method, and successive convex approximation to develop an alternating optimization-based algorithm. Our simulation results demonstrate the significant power savings enabled by the proposed scheme compared to two baseline schemes employing heuristic trajectories.