Joint UAV Deployment and Energy Transmission Design for Throughput Maximization in IoRT Networks

Jiarong Lu, Ying Wang, Yuanbin Chen, Huaiqi Jia
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引用次数: 2

Abstract

On account of the difficulty of deploying the ground base station (BS) and the limited power consumption of smart devices in Internet of Remote Things (IoRT) networks, it is necessary to construct a system assisted by unmanned aerial vehicles (UAVs) for sustainable communication. This paper aims to study a resource allocation problem in the wireless powered communication network (WPCN) while a UAV serves as an aerial BS. The optimization goal of this paper is to maximize the minimum throughput of ground terminals (GTs) by jointly optimizing the UAV deployment, time resource allocation, and power control. Nevertheless, the optimization problem is nonlinear and non-convex, which is difficult to solve directly. Therefore, it is transformed into two sub-problems, which can be iterated alternately to maximize the minimum throughput of each device in WPCN. The successive convex approximation (SCA) technique and variable substitution are used to transform two non-convex sub-problems into solvable problems. Finally, an iterative algorithm combining two sub-problems is designed to obtain the resource allocation strategies. The numerical results show that the communication resource can be fully shared by adjusting the position of the UAV, and the efficiency and performance of the algorithm are verified.
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面向IoRT网络吞吐量最大化的联合无人机部署与能量传输设计
由于远程物联网(IoRT)网络中地面基站(BS)的部署困难和智能设备的功耗有限,需要构建无人机辅助的系统来实现可持续通信。本文旨在研究无人机作为空中基站时无线供电通信网络(WPCN)资源分配问题。本文的优化目标是通过联合优化无人机部署、时间资源分配和功率控制,使地面终端的最小吞吐量最大化。然而,优化问题是非线性的、非凸的,很难直接求解。因此,将其转化为两个子问题,可交替迭代,以实现WPCN中每个设备的最小吞吐量最大化。采用逐次凸逼近技术和变量代换将两个非凸子问题转化为可解问题。最后,设计了一种结合两个子问题的迭代算法来获得资源分配策略。数值结果表明,通过调整无人机的位置,可以实现通信资源的充分共享,验证了该算法的效率和性能。
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