Multi-UAV-Assisted Green Energy Far-Field Wireless Charging for Large-Scale WRSNs

With the rapid development of Internet of Things (IoT), wireless rechargeable sensor networks (WRSNs) have found widespread applications in modern society. However, due to the dynamic energy consumption of sensor nodes (SNs) and the challenges associated with battery replacement, ensuring a timely energy supply to SNs is a pressing concern. Currently, employing unmanned aerial vehicles (UAVs) for far-field wireless charging emerges as a promising solution to charge SNs. However, with the expansion of WRSNs, existing solutions face challenges in meeting the energy demands of large-scale WRSNs. Therefore, we propose to leverage multiple green energy powered UAVs to facilitate far-field wireless charging for large-scale WRSNs. We first segment the SNs into clusters and propose the dynamic energy consumption models for UAVs and SNs. Then, we formulate the UAVs' charging service efficiency maximization problem, enabling more SNs to receive sufficient energy replenishment. As this problem is proved to be an NP-hard problem, we further propose the dyNamic wIreless chaRging (NIR) algorithm to efficiently determine the charging sequences of the SNs and reduce the UAVs' energy consumption. Extensive simulations have validated that NIR notably improves the charging service efficiency of the UAVs, thereby prolonging the WRSN's lifespan.