Energy-Efficient Joint Scheduling and Resource Management for UAV-Enabled Multicell Networks

Abstract

Unmanned aerial vehicles (UAVs) have attracted much attention recently in wireless communication networks due to their low-cost and flexible deployment. In this paper, we address the energy-efficient joint scheduling and resource management in UAV-enabled multicell networks, where multiple UAVs act as aerial base stations (BSs) to serve ground devices. We devise the scheduling and resource management that jointly solve the problem of optimizing the UAVs' locations and resource management, in order to maximize the network energy efficiency (EE). Accordingly, we propose two approaches: a coordinated approach, where all UAVs coordinate with each other to achieve the overall network EE with sharing their information and decision, and an uncoordinated approach, where each UAV selfishly maximizes its own EE without sharing its information and decision. We transform the coordinated optimization problem into a convex form, and adopt the noncooperative game theory to model the uncoordinated formulation. Moreover, we extend the two approaches to time-varying UAV-enabled systems to handle the dynamic environments. Simulation results evaluate the performance of the proposed coordinated approach and the uncoordinated approach under both dynamic and stationary cases, and reveal the respective advantages of the two approaches.