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

• Published in: IEEE access Vol. 7; pp. 104279 - 104293
• Main Authors: Pan, Chunyu, Yi, Jirong, Yin, Changchuan, Yu, Jian, Li, Xuehua
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 3D UAV placement; Algorithms; alternating direction method of multipliers; alternating maximization; Base stations; Benchmarks; Cellular communication; Cellular networks; Computational geometry; Convexity; Drones; Ground stations; Iterative algorithms; Iterative methods; Maneuverability; Maximization; Mixed integer; Optimization; Performance enhancement; Placement; Resource allocation; Resource management; software-defined cellular network; software-defined network; Software-defined networking; successive convex optimization; Three-dimensional displays; Throughput; Unmanned aerial vehicles; user association; Wireless communication; Wireless networks
• DOI: 10.1109/ACCESS.2019.2927521
• ISSN: 2169-3536

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.