Optimization of Multi-UAV-Aided Wireless Networking Over a Ray-Tracing Channel Model

Abstract

Recently, unmanned aerial vehicles (UAVs) have been utilized to extend the coverage and capacity of terrestrial wireless networks. In such a UAV-aided wireless network , we can exploit the more favorable line-of-sight (LOS) propagation in the UAV-user wireless link to achieve better coverage and higher capacity. Furthermore, the flexible deployment of UAVs makes them ideal for catering to ad hoc demand. Due to the lack of fixed-line backhaul, UAVs act like relays with wireless backhaul links in UAV-aided wireless networks. Unlike the conventional relays in terrestrial wireless networks, the positions of UAV-Rs can be optimized to maximize the system performance. Although the optimal UAV positioning problem has been studied under simple LOS/probabilistic channel models, the joint optimization of UAV positions, user association, and wireless backhaul capacity allocation remains unsolved under realistic channel models, which will be addressed in this paper. The joint optimization problem is a challenging mixed non-convex and combinatorial problem. Combining the block coordinate descent and successive convex approximation (SCA) methods, we propose a sparse parallel block SCA algorithm, which can find a near-optimal solution by exploiting the structures of the propagation model. The simulations verify the significant gain of the proposed solution over existing solutions.