Green Laser-Powered UAV Far-Field Wireless Charging and Data Backhauling for a Large-Scale Sensor Network

被引:0
|
作者
Ma, Xiongbo [1 ]
Liu, Xilong [1 ]
Ansari, Nirwan [2 ]
机构
[1] Yunnan Univ, Sch Informat Sci & Engn, Kunming 650500, Yunnan, Peoples R China
[2] New Jersey Inst Technol, Helen & John C Hartmann Dept Elect & Comp Engn, Adv Networking Lab, Newark, NJ 07102 USA
来源
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 19期
基金
美国国家科学基金会;
关键词
Autonomous aerial vehicles; Trajectory; Inductive charging; Wireless communication; Wireless sensor networks; Clustering algorithms; Backhaul networks; Data backhauling; green energy far-field wireless charging; sixth-generation (6G) wireless communications; unmanned aerial vehicle (UAV); wireless rechargeable sensor networks (WRSNs); RESOURCE-ALLOCATION; DATA-COLLECTION; OPTIMIZATION; INTERNET;
D O I
10.1109/JIOT.2024.3422252
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Sixth-generation (6G) wireless communications greatly emphasizes the integration of sensing, communicating, and computing. Unmanned aerial vehicles (UAVs), by leveraging their feasibility and mobility, can naturally facilitate flexible far-field wireless charging and data backhauling for widely implemented wireless rechargeable sensor networks (WRSNs) across diverse domains, such as intelligent agriculture, smart cities, and modern factories. However, the energy constraints inherent to UAVs, coupled with the absence of joint optimization in clustering and trajectory design, present formidable challenges in efficiently leveraging UAVs for large-scale WRSN wireless charging and data backhauling. Therefore, in this work, we empower the green energy-powered base station (GBS) to power a UAV by laser charger to prolong the UAV's uptime. This enables the UAV to effectively perform wireless charging and data backhauling for a WRSN. By considering the GBS's green energy budget, we formulate an optimization problem focused on determining the optimal 3-D hovering points for UAV to maximize the number of sensor nodes (SNs) capable of receiving sufficient energy and uploading data. Given the NP-hard nature of this problem, we propose a two-step solution featuring corresponding heuristic algorithms designed to efficiently address it. Extensive simulations have been conducted to validate the efficacy of our proposed algorithms.
引用
收藏
页码:31932 / 31946
页数:15
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