Joint Trajectory and Resource Allocation Optimization for Air-ground Collaborative Integrated Sensing and Communication Systems

An air-ground collaborative integrated sensing and communication system is studied, where the air-ground collaborative network is composed of an Unmanned Ground Vehicle (UGV) base station and Unmanned Aerial Vehicle (UAV) relays. The network provides communication service for ground users while detecting and sensing target areas. The air-ground channels are modeled as the accurate Rician fading channel model. On the constraints of the sensing frequency and the effective sensing power threshold of the target areas, the minimum average communication rate of all users is maximized by jointly optimizing the communication and sensing association of the system, the transmit power and flight trajectory of the UAV relays, as well as the transmit power and trajectory of the UGV base station. To solve the resultant non-convex integer optimization problem with highly coupled variables, the block coordinate descent method is applied to decompose the original optimization problem into four sub-problems, where relaxation variables are introduced, and the integer constraints are converted into penalty terms. Then, it is proved that the effective sensing power is a composition function of the trajectory variables and the relaxation variables and is a jointly convex function of them, so that the non-convex terms are tackled by using the successive convex optimization method. Lastly, a two-layer iterative algorithm is proposed to obtain the suboptimal solution efficiently. It is shown by simulation results that compared to some benchmark algorithms, the proposed algorithm significantly increases the minimum average communication rate of all users while achieving the same sensing performance and achieves a better performance trade-off between communication and sensing with good convergence performance. © 2024 Science Press. All rights reserved.