Jointly Optimize Throughput and Localization Accuracy: UAV Trajectory Design for Multiuser Integrated Communication and Sensing

Unmanned aerial vehicle (UAV) is becoming a crucial aerial platform to provide emergency or enhanced communication and sensing services benefited from its unique features, including agile mobility and high probability of Line-of-Sight coverage. In this article, we investigate the novel UAV trajectory design problem where the UAV communicates with multiple users and simultaneously senses the positions of multiple targets, via the integrated communication and sensing design. To evaluate the overall system utility, we first derive the communication throughput and localization error Cramér-Rao bound (CRB) model and highlight the coupled challenge and tradeoffs on UAV’s trajectory. We thus model the three typical integrated sensing and communication scenarios: 1) communication centric; 2) sensing centric; and 3) tradeoff scenarios. We further introduce path discretization to support in-flight communication and hovering sensing, which make it possible to jointly optimize the UAV trajectory, communication throughput and target localization estimation error CRB with limited complexity. Because this optimization problem involves integer programming caused by multiuser association, we propose a novel trajectory initialization framework based on traveling salesman problem to determine the service order for sensing targets and the initial UAV trajectory. To address the nonconvexity of this optimization problem, we propose an efficient iterative algorithm using the successive convexity approximation technique to obtain the approximate optimal solution, which is dynamically reconfigured and optimized with updated information in flight. Extensive numerical results demonstrate that the proposed algorithm achieves superior performance in the tradeoff between average achievable rate and CRB in all three scenarios.