Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks

TLDR

UAVs, valued for their maneuverability, flexibility, and low cost, are increasingly used to enhance wireless communication, yet the resulting mixed‑integer nonconvex optimization problem remains challenging to solve. The study aims to maximize the minimum downlink throughput for ground users in a multi‑UAV system by jointly optimizing user scheduling, association, UAV trajectories, and power control. An iterative algorithm based on block coordinate descent and successive convex optimization alternately optimizes scheduling, association, UAV trajectory, and transmit power, using convex approximations for trajectory and power and a low‑complexity circular‑trajectory initialization scheme. The algorithm converges reliably and, according to extensive simulations, yields substantial throughput gains over benchmark schemes.

Abstract

Due to the high maneuverability, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAV's trajectory and power control. The formulated problem is a mixed integer nonconvex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the nonconvex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.