Efficient Green Energy Far-Field Wireless Charging for Internet of Things

With the worldwide ubiquitous implementation of Internet of Things (IoT), IoT devices (IoTDs) and their emerging applications are commendably enriching people's daily life with intelligence and convenience. However, a tremendous number of IoTDs all over the world, incurring a huge amount of energy consumption, are exacerbating the global electric grid load and natural environment changes while the electronic equipment traditional charging approaches are unable to efficiently power the IoTDs. Leveraging green energy to remotely charge the IoTDs (i.e., green energy far-filed wireless charging) is the essential solution to revolutionarily resolve these problems. In this work, we propose a two-step green energy wireless charging (TREE) algorithm to efficiently power the IoTDs for the multiple-green base stations (GBSs)-to-multiple IoTDs charging scenarios. First, we propose the recharging threshold model for IoTDs and schedule the IoTDs to be efficiently charged by their associated GBSs within the green wireless charging time period. Second, for those IoTDs that will not be fully charged, we propose the multi-GBS joint accumulative charging scheme to fulfill most of the IoTDs' charging requirements within the charging period. Finally, we validate the performance of the proposed algorithm through extensive simulations.