Dynamic deployment of multi-UAV base stations with deep reinforcement learning

被引：1

作者：

Wu, Guanhan ^{[1
]}

Jia, Weimin ^{[1
]}

Zhao, Jianwei ^{[1
]}

机构：

[1] Xian Res Inst Hitech, Xian, Shaanxi, Peoples R China

来源：

ELECTRONICS LETTERS | 2021年 / 57卷 / 15期

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1049/ell2.12205

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Unmanned aerial vehicles (UAVs) can be utilized as aerial base stations (BSs) to provide auxiliary communication services. In this letter, we propose a deep reinforcement learning (DRL)-based dynamic deployment method for multi-UAV communications. The phasic policy gradient (PPG) is designed to improve the sample efficiency and the attention of the multi-UAV deployment. Simulation results are provided to verify the effectiveness of the proposed method.

引用

页码：600 / 602

页数：3

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