Energy harvesting assisted UAV sensing integrated system resource allocation

In the context of the deep integration of wireless communication and perception technology, this paper examines the resource allocation problem of an energy harvesting-assisted unmanned aerial vehicle (UAV) communication and perception integrated systems. Firstly, an energy harvesting-assisted UAV sensing integrated system was constructed, which consists of a sensing integrated base station, sensing terminals, and ground sensing energy stations. Then, based on the separate study of energy consumption models, communication models, and perception models, an integrated energy harvesting-assisted UAV sensing system model was established. Considering the optimization objectives of communication and perception, communication metrics were transformed into constraints and the research focussed on studying the perception performance of the system. A series of convex optimization methods were used to solve the conversion optimization problem, and the optimal energy harvesting time slot allocation was solved using the binary method. The established optimization model takes into account the deep coupling between the drone beamforming vector and the position decision variable. Finally, the optimal solution was obtained through alternating iterations using semi-definite programming (SDP), the Dinkelbach method, and the successful convex approximation (SCA) method. The simulation experiment fully verifies the effectiveness of the proposed algorithm.