Abstract
This paper considers a laser-powered unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system. In the system, a UAV is dispatched as an energy transmitter to replenish energy for battery-limited sensors in a wireless rechargeable sensor network (WRSN) by transferring radio frequency (RF) signals, and a mobile unmanned vehicle (MUV)-loaded laser transmitter travels on a fixed path to charge the on-board energy-limited UAV when it arrives just below the UAV. Based on the system, we investigate the trajectory optimization of laser-charged UAVs for charging WRSNs (TOLC problem), which aims to optimize the flight trajectories of a UAV and the travel plans of an MUV cooperatively to minimize the total working time of the UAV so that the energy of every sensor is greater than or equal to the threshold. Then, we prove that the problem is NP-hard. To solve the TOLC problem, we first propose the weighted centered minimum coverage (WCMC) algorithm to cluster the sensors and compute the weighted center of each cluster. Based on the WCMC algorithm, we propose the TOLC algorithm (TOLCA) to design the detailed flight trajectory of a UAV and the travel plans of an MUV, which consists of the flight trajectory of a UAV, the hovering points of a UAV with the corresponding hovering times used for the charging sensors, the hovering points of a UAV with the corresponding hovering times used for replenishing energy itself, and the hovering times of a UAV waiting for an MUV. Numerical results are provided to verify that the suggested strategy provides an effective method for supplying wireless rechargeable sensor networks with sustainable energy.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference23 articles.
1. Fine-grained trajectory optimization of multiple UAVs for efficient data gathering from WSNs;Luo;IEEE/ACM Trans. Netw.,2020
2. Resource allocation for energy harvesting-powered d2d communication underlaying uav-assisted networks;Wang;IEEE Trans. Green Communications Netw.,2017
3. Jie, X., Yong, Z., and Rui, Z. (2017, January 4–8). Uav-enabled wireless power transfer: Trajectory design and energy region characterization. Proceedings of the 2017 IEEE Globecom Workshops (GC Wkshps), Singapore.
4. Ku, S., Jung, S., and Lee, C. (2019, January 23–26). Uav trajectory design based on reinforcement learning for wireless power transfer. Proceedings of the 2019 34th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC), JeJu, Korea.
5. Wu, Y., Qiu, L., and Xu, J. (2018, January 28–31). Uav-enabled wireless power transfer with directional antenna: A two-user case (invited paper). Proceedings of the 2018 15th International Symposium on Wireless Communication Systems (ISWCS), Lisbon, Portugal.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献