Joint Resource Allocation and Trajectory Optimization for UAV-Aided Relay Networks

In this paper, we study a UAV-aided relay network, where a number of ground users need to collect data from a base station (BS), and a UAV could fly around above the users and serve as a decode-and-forward (DF) mobile relay to improve the performance. Firstly, we develop a novel UAV-relay model, which maximizes the minimum throughput among users by optimizing the UAV trajectory, the user scheduling and bandwidth allocation. Moreover, we adopt the segmented ray- tracing channel model to characterize the practical urban channel. Then, by constructing surrogate functions of the nonconvex constraints, we approximate the problem into a convex one and develop a block successive convex approximation (BSCA) algorithm to solve it. In particular, through insightful auxiliary variables and linearly coupled equality constraints, we propose a low-complexity algorithm to solve the key subproblem in the iteration of the proposed BSCA algorithm. Finally, simulation results show that the proposed design significantly outperforms the existing algorithms.