Efficient Multiple Charging Base Stations Assignment for Far-Field Wireless-Charging in Green IoT

Qiuyu Sha, Xilong Liu, Nirwan Ansari, Yongxing Jia

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Owing to the development of Internet of Things (IoT) and Artificial Intelligence (AI) technology, powering IoT devices has become a dire problem that mobile IoT devices need a more portable way to be charged. Based on our previous research on green IoT, the far-field Wireless Power Transfer (WPT) powered by green energy can alleviate this problem. Although many existing works on Multi-Base Station Joint Charging Schemes have gained remarkable results, the aggregation of multiple power waves cannot be explicitly described by the traditional 1-dimensional model suggested by Friis Formula. The 2-dimensional model called vector model can solve this problem by clearly indicating how the multiple power waves aggregate at an IoT device in the form of a 2-dimensional vector. In this work, an Adjusting Phase (AP) method based on the vector model is designed to enhance the value of aggregated power waves. In addition, we propose the Greedy chArging Grouping Algorithm (GAGA) to ensure that the charging mission will be completed on time and the risk of running out of power can be reduced. Finally, we validate the performance of the proposed algorithm in comparison with the state-of-the-art solutions through extensive simulations.

Original languageEnglish (US)
JournalProceedings - IEEE Global Communications Conference, GLOBECOM
StatePublished - 2021
Event2021 IEEE Global Communications Conference, GLOBECOM 2021 - Madrid, Spain
Duration: Dec 7 2021Dec 11 2021

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Signal Processing


  • Energy Efficiency
  • Green Base Station Assignment
  • Green Energy
  • Internet of Things Devices
  • Wireless Charging


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