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

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

doi:10.1109/access.2019.2927521

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.

Highlights

Unmanned aerial vehicles (UAVs) mounted with access points can serve as aerial base stations and form drone cells to provide additional association opportunities and resources for users in temporary or unexpected circumstances, which are expected to arise in future cellular networks [1], [2]
Benefitting from the flexible software-defined cellular networks (SDCN) structure, the real-time perception and update of multidimensional variables, such as user association and scheduling, 3D UAV placement and the fronthaul and backhaul spectrum allocation are jointly optimized by the maximization of data rate utility among overall users
The coupled multiple optimization variables are partitioned into three parallel blocks in the algorithm

Summary

INTRODUCTION

Unmanned aerial vehicles (UAVs) mounted with access points can serve as aerial base stations and form drone cells to provide additional association opportunities and resources for users in temporary or unexpected circumstances, which are expected to arise in future cellular networks [1], [2]. To improve the performance of multi-UAV enabled software-defined cellular networks, we have formulated a resource allocation optimization problem to maximize the aggregate users’ data rate utility. Based on the global view of the logical control plane in the SDCN, we investigate the joint optimal user scheduling and association, resource allocation and 3D UAV placement for the integrated ground-air cellular network for delay-tolerant services [12]. We utilize a distributed and parallel alternating maximization (AM) algorithm [20] and partition the coupled multidimensional optimization variables into three parallel blocks: the 3D UAV placement, the fronthaul and backhaul spectrum allocation, and the user scheduling and association. To improve the performance of multi-UAV enabled SDCN with wireless backhaul, we formulate a resource allocation optimization problem to maximize the aggregate users’ utility function.

SPECTRUM ALLOCATION OPTIMIZATION IN THE RAF MODULE

CONCLUSION