Low-Complexity Joint Resource Allocation and Trajectory Design for UAV-Aided Relay Networks With the Segmented Ray-Tracing Channel Model

Unmanned aerial vehicles (UAVs) have been applied in many different communication scenarios due to their mobility and manipuility. In this paper, we investigate a UAV-aided relay network, where a number of ground users in the urban area with many obstructions 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 transmission coverage and performance. In this situation, channel can be represented by the segmented ray-tracing model. To ensure fairness, we aim to maximize the minimum throughput among all the users by jointly optimizing the three-dimensional (3D) UAV trajectory, user scheduling, and bandwidth allocation. To tackle the non-convex objective function and coupling constraints, we first construct surrogate functions, and then approximate the problem into a convex one and develop a constrained successive convex approximation (CSCA) algorithm. In particular, through insightful auxiliary variables and linearly coupled equality (LCE) constraints, we propose a low-complexity algorithm based on the alternating direction method of multipliers (ADMM) to solve the approximated convex problem in the iteration of the proposed CSCA algorithm. Furthermore, we prove the convergence of the proposed algorithm and analyze its complexity. The proposed algorithm can be easily extended to the multi-UAV scenario. Simulation results show that the proposed design significantly outperforms the existing schemes.