TY - GEN
T1 - Efficient Multiple Charging Base Stations Assignment for Far-Field Wireless-Charging in Green IoT
AU - Sha, Qiuyu
AU - Liu, Xilong
AU - Ansari, Nirwan
AU - Jia, Yongxing
N1 - Funding Information:
This work has been supported in part by the NSFC under grant 62002312.
Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
KW - Energy Efficiency
KW - Green Base Station Assignment
KW - Green Energy
KW - Internet of Things Devices
KW - Wireless Charging
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U2 - 10.1109/GLOBECOM46510.2021.9685825
DO - 10.1109/GLOBECOM46510.2021.9685825
M3 - Conference contribution
AN - SCOPUS:85127275280
T3 - 2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
BT - 2021 IEEE Global Communications Conference, GLOBECOM 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE Global Communications Conference, GLOBECOM 2021
Y2 - 7 December 2021 through 11 December 2021
ER -