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多无人机助力的无线供能通信网络中的最小吞吐量最大化。

Minimum-Throughput Maximization for Multi-UAV-Enabled Wireless-Powered Communication Networks.

机构信息

Jiangxi Province Key Laboratory of Intelligent Information Systems, Nanchang University, Nanchang 330031, China.

Information Engineering School, Nanchang University, Nanchang 330031, China.

出版信息

Sensors (Basel). 2019 Mar 27;19(7):1491. doi: 10.3390/s19071491.

Abstract

This paper considers a wireless-powered communication network (WPCN) system that uses multiple unmanned aerial vehicles (UAVs). Ground users (GUs) first harvest energy from a mobile wireless energy transfer (WET) UAV then use the energy to power their information transmission to a data gatherer (DG) UAV. We aim to maximize the minimum throughput for all GUs by jointly optimizing UAV trajectories, and the resource allocation of ET UAV and GUs. Because of the non-convexity of the formulated problem, we propose an alternating optimization algorithm, applying successive convex optimization techniques to solve the problem; the UAV trajectories and resource allocation are alternately optimized in each iteration. Numerical results show the efficiency of the proposed algorithm in different scenarios.

摘要

本文考虑了一种使用多架无人机(UAV)的无线供电通信网络(WPCN)系统。地面用户(GU)首先从移动无线能量传输(WET)无人机中获取能量,然后使用能量为向数据收集器(DG)无人机的信息传输供电。我们旨在通过联合优化无人机轨迹以及 ET 无人机和 GU 的资源分配,来最大化所有 GU 的最小吞吐量。由于所提出问题的非凸性,我们提出了一种交替优化算法,应用连续凸优化技术来解决该问题;在每次迭代中,交替优化无人机轨迹和资源分配。数值结果表明了在不同场景下该算法的有效性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4412/6480236/5068cd6ddb52/sensors-19-01491-g001.jpg

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