Trajectory Optimization Research of Wireless Power Communication Networks Assisted by Aerial Intelligent Reflecting Surface

被引：0
作者：
Zhou, Yi [1 ,2 ]
Jin, Zhanqi [1 ,2 ]
Shi, Huaguang [1 ,3 ]
Tian, Yuxiang [1 ,2 ]
Shi, Lei [1 ,2 ]
Zhang, Yanyu [1 ,2 ]
机构：
[1] School of Artificial Intelligence, Henan University, Zhengzhou
[2] International Joint Research Laboratory for Cooperative Vehicular Networks of Henan, Zhengzhou
[3] Henan Engineering Research Center for Industrial Internet of Things, Zhengzhou
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2024年 / 46卷 / 07期
基金：
中国国家自然科学基金; 中国博士后科学基金;
关键词：
Intelligent Reflecting Surface(IRS); Trajectory optimization; Unmanned Aerial Vehicle(UAV); Wireless Powered Communication Network(WPCN);
D O I：
10.11999/JEIT230830
中图分类号：
学科分类号：
摘要：
Unmanned Aerial Vehicle (UAV) equipped with Intelligent Reflecting Surface (IRS) can effectively solve the problem of inefficient information and energy transmission between the hybrid access point and nodes in complex wireless scenarios due to obstacle occlusion. A novel framework for aerial IRS-assisted wireless powered communication networks is proposed that exploits the flexibility of aerial IRS to improve the performance of the network. The architecture achieves the transmission of energy and data for each time slot employing the harvest-then-transmit scheme. A multi-variable coupled optimization problem that combines the flight trajectory, node selection association variable, time slot allocation ratio, and the phase is established while satisfying the node energy harvesting threshold. Thus, the block coordinate descent algorithm is utilized to decompose the optimization problem into four sub-problems to be solved separately. Firstly, the closed-form solution for the optimal phase of the intelligent reflecting surface is derived based on the beam alignment theory. Secondly, the non-convex problem is transformed into a convex problem by introducing auxiliary variables and employing a successive convex approximation algorithm. Finally, the solution is iteratively solved utilizing the block coordinate descent algorithm. Simulation results show that the proposed scheme has excellent convergence performance and significantly improve the average throughput. © 2024 Science Press. All rights reserved.
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收藏
页码：2812 / 2820
页数：8
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