Joint 3D UAV Placement and Resource Allocation in Software-Defined Cellular Networks With Wireless Backhaul

Chunyu Pan, Jirong Yi, Changchuan Yin, Jian Yu, Xuehua Li

Abstract:

Cellular networks assisted by flexibly placed high-maneuverability unmanned aerial
vehicles (UAVs) have attracted virtual interests recently. In this paper, the utility maximization problem
is investigated to determine how to improve the performance of multi-UAV enabled software-defined
cellular networks (SDCNs) with wireless backhaul. The formulated problem jointly optimizes the three
dimensional (3D) UAV placement, user scheduling and association, and spectrum resource allocation. The
proposed problem is intractable since it is a mixed-integer combined non-convex problem. Thus, an efficient
distributed alternating maximization (AM) iterative algorithm is developed to solve the proposed problem.
Then, the original optimization problem is decomposed into three subproblems that are solved alternatively
via the successive convex optimization (SCO) technique and the modified alternating direction method of
multipliers (ADMM) in the proposed algorithm. The theoretical analysis and the simulation results confirm
the convergence performance of the proposed algorithm. The extensive numerical results substantiate the
superiority of the proposed algorithm, which significantly increases the throughput and utility of the overall
users relative to the traditional overlaid ground base station (GBS) and UAV structure and other benchmark
methods. The maximal throughput gain is as large as 74.9% on average for all users, in contrast to other
benchmark schemes.