Green Laser-Powered UAV Far-Field Wireless Charging and Data Backhauling for a Large-Scale Sensor Network
Xiongbo Ma, Xilong Liu, Nirwan Ansari
Abstract
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.