Joint Trajectory and Power Optimization for UAV-Assisted Communication Networks

UAVs have become a key tool to assist communication networks in performing their tasks due to their mobility, flexibility and low cost. This study focuses on how to solve the problem of decreasing effective user coverage caused by increasing user data demand during data distribution of a single UAV-assisted communication network system, and proposes a method to jointly optimize the flight trajectory and transmission power of UAVs to minimize the decreasing trend of effective coverage. The problem is modeled as a mixed integer non-convex optimization problem. Therefore, a block coordinate descent algorithm based on continuous convex approximation (SCA) technique is proposed in this paper. The algorithm alternately optimizes the flight trajectory and transmission power of UAVs in each iteration, and uses SCA technology to deal with the non-convexity of trajectory and power, and transforms two non-convexity optimization problems into approximately convex optimization problems. In addition, the complexity of the algorithm is also analyzed. The experimental results show that compared with the existing benchmark scheme, the proposed scheme can effectively alleviate the problem that the effective coverage of user decreases due to the increase of user data demand.