A selective update sensing approach for UAV-ISAC enabled relaying network

This paper proposes a selective sensing information update scheme for communication between a base station (BS) and multiple unmanned aerial vehicles (UAVs) in a relaying network. The UAVs, equipped with integrated sensing and communication (ISAC) capabilities, utilize environmental sensing measurements to facilitate communication in blockage-prone scenarios, such as disaster recovery and remote connectivity. Specifically, user parameters are estimated from the sensing measurements at the UAVs. Given the non-linear relationship between the sensing measurements and the communication parameters, we propose a two-stage design approach. In the first stage, the measurements are transformed into a range-and-angle-based model to determine the optimal beam between the UAVs and multiple mobile user equipment (UEs). In the second stage, a selective update mechanism, guided by a predictive rate criterion, is used to optimize the frequency of sensing information updates between the BS and the UAVs. Simulation results demonstrate the superiority of the proposed method and show an improvement in the system throughput compared to baseline schemes, while significantly reducing sensing overhead.