UAV-Enabled Integrated Sensing and Communications for Internet of Things: Trajectory Optimization and Beamforming Design

In this paper, we propose an unmanned aerial vehicle (UAV) assisted integrated sensing and communication (ISAC) system for the Internet of Things (IoT), where the UAV beams simultaneously sense the status information of multiple IoT sensing nodes and transmit the sensing data to a data center. The main objective is to enable the UAV to perform sensing using radar beams and then transmit the collected information to the data center via communication beams. To evaluate the sensing performance of the ISAC system, we introduce radar mutual information as a key metric from an information-theoretic perspective. Considering the mutual interference between sensing and communication as well as the communication rate limitations, we aim to maximize radar mutual information by optimizing the UAV flight trajectory and transmit beamforming. To address this problem, we propose a joint optimization algorithm that employs semi-finite and concave programming techniques to maintain rank-1 constraints with low complexity. Numerical results demonstrate the effectiveness of the proposed algorithm in achieving the maximum radar estimation rate, thereby validating the rationality and feasibility of the proposed design approach.