Network Energy-Efficiency Maximization in UAV-Enabled Air–Ground-Integrated Deployment
Yan Li, Shaoyi Xu, Yunpu Wu, Dongji Li
Abstract
The unmanned aerial vehicle (UAV) technique combined with the cellular network is a promising and reliable technique to provide a low-cost, flexible, and easy-to-expandable network. In this article, we propose a UAV-assisted cooperative transmission network (UCTN), where UAVs and the base station (BS) transmit data jointly through the cooodination of the software-defined network (SDN). As the UAV has limited on-board energy, we aim to maximize the network energy efficiency (EE) by jointly optimizing the UAV–user association, UAV location, BS resource allocation, and the load allocation between the two systems. The formulated problem is a mixed-integer nonconvex optimization problem, which is intractable. To solve it, alternative optimization (AO) and Dinkelbach’s method are adopted to recast the original problem into a tractable form. After that, the corresponding problem is divided into three subproblems and can be solved iteratively. An energy-constrained coalition game is proposed to solve the UAV–user association problem, and the UAV hovering point is carefully designed to balance the coalition serving time. Furthermore, the successive convex approximation (SCA) technique is adopted to optimize the BS transmit power and bandwidth allocation. Numerical experiments demonstrate that the proposed algorithm achieves significant performance gains over other benchmark schemes.