Situation-Aware Hybrid Sensing and Position Control for UAV-Assisted ISAC Systems

The high flexibility and controllable mobility of unmanned aerial vehicles (UAVs) make it possible to construct the line-of-sight transmission link between devices in plant and the remote center, where the channel state condition heavily depends on the position of UAV. In this work, integrated sensing and communication (ISAC) is adopted to simultaneously perform position awareness and data transmission with limited radio resources. In particular, a situation-aware hybrid sensing pattern is proposed to reduce energy consumption and the interference of sensing to communication. In this hybrid pattern, the sensing function is activated on demand based on the channel state condition that is heavily affected by the position of UAV. Besides, the position control of UAV is performed based on the sensing result to further improve the transmission rate. Then, a joint optimization problem of beamforming design and power allocation is formulated to maximize energy efficiency. To solve this mixed integer nonlinear problem, the original problem is decomposed into subproblems in Phase I and Phase II. Finally, the golden-section based Dinkelbach algorithm and the penalty based approximation algorithm are proposed to solve the Phase I subproblem with the fractional objective function and rank-one constraints. Moreover, a quadratic transform enabled joint design of remote center beamforming and UAV transmit power is proposed to solve the Phase II subproblem. Simulation results verify that the proposed UAV-assisted integration of sensing, communication, and control approach outperforms compared approaches regarding data volume and energy efficiency.