UAV-BS Site Planning Based on Circular Coverage Strategy

Future mobile communication technology will be used to build an integrated global coverage network. Unmanned aerial vehicles (UAVs) are the first choice for low-altitude networks due to their low cost, flexibility, and ease of operation. The characteristics of UAVs also bring new challenges to communication networks, such as short flight time, complex networking, and unstable communication quality. Therefore, it has become an urgent problem to reasonably plan the location of UAV Base Stations (UAV-BSs), reduce communication power consumption, optimize network performance, and build an efficient and stable UAV communication network (UAVCN). The traditional strategy only pays attention to the signal coverage, and ignores the influence of system transmission power on the network, which reduces the performance of the communication system. In this study, a circular coverage power optimization strategy (CCPO) based on system transmit power is proposed. The mathematical model of the circular coverage problem is used to describe the full coverage process of the UAV base station to ground users, and the deployment optimization is carried out with the goal of minimizing system transmit power, so as to obtain an efficient and reliable site planning scheme. In this paper, the binomial power function is used to continuously fit the discrete solution of the circle covering problem, and the circle covering power optimization formula is rearranged. By analyzing the convexity of the objective function under the circular coverage model, the convex optimization theory is used to solve the objective problem, and the optimal deployment number of UAVs and site planning scheme under the circular coverage power optimization strategy are given. Simulation verifies the superiority of the proposed method. Compared with the traditional hexagon strategy and the minimum power loss strategy, the circular coverage power optimization station location planning strategy can save 14.75% and 6.52% of power resources, providing a valuable reference for the design and optimization of UAV communication systems. It provides a promising solution for further improving the performance and efficiency of UAVCNs.