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• W4312597511 abstract "Powering a huge number of Internet of Things Devices (IoTDs), necessitated in many Internet of Things (IoT) applications, is a dreadful problem in many circumstances, in terms of the cost of labor, time, and so on. Far-field green energy wireless charging is a promising technique to remotely power IoTDs in a large-scale network. In order to improve the end-to-end energy efficiency, for the scenario with multiple green base stations (GBSs) wirelessly charging multiple IoTDs, our previous research work proposed a wireless charging scheme to aggregate the wireless power received by a static IoTD from multiple GBSs. In reality, in various emerging IoT applications, a large proportion of IoTDs are mobile. Hence, in this work, we focus on intelligently assigning multiple GBSs to wirelessly charge mobile IoTDs such that the IoTDs can be efficiently powered. We first propose the moving model and the charging model of IoTDs. Based on the nonlinear wireless charging model and nonlinear wireless energy conversion model, we then propose the Greedy dynamic joint charging (GAIN) algorithm to efficiently power the mobile IoTDs. Through extensive simulations, we validate the performance of the proposed algorithm." @default.
• W4312597511 created "2023-01-05" @default.
• W4312597511 creator A5008864376 @default.
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• W4312597511 date "2023-05-15" @default.
• W4312597511 modified "2023-09-28" @default.
• W4312597511 title "Efficient Multiple Green Energy Base Stations Far-Field Wireless Charging for Mobile IoT Devices" @default.
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• W4312597511 doi "https://doi.org/10.1109/jiot.2022.3232091" @default.
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