Efficient Multiple Green Energy Base Stations Far-Field Wireless Charging for Mobile IoT Devices

Qiuyu Sha, Xilong Liu, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)8734-8743
Number of pages10
JournalIEEE Internet of Things Journal
Volume10
Issue number10
DOIs
StatePublished - May 15 2023

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

Keywords

  • Green energy
  • Internet of Things (IoT)
  • Internet of Things Devices (IoTD)-green base station (GBS) association
  • mobile IoTDs
  • multiple GBSs
  • wireless charging efficiency

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