Radiation Constrained Wireless Charger Placement

Haipeng Dai, Yunhuai Liu, Nan Yu, Chaofeng Wu, Guihai Chen, Tian He, Alex X. Liu

Research output: Contribution to journalArticlepeer-review

Abstract

Wireless Power Transfer has become a commercially viable technology to charge devices because of the convenience of no power wiring and the reliability of continuous power supply. This paper concerns the fundamental issue of wireless charger placement with electromagnetic radiation (EMR) safety. Although there are a few wireless charging schemes consider EMR safety, none of them addresses the charger placement issue. In this paper, we propose PESA, a wireless charger Placement scheme that guarantees EMR SAfety for every location on the plane. First, we discretize the whole charging area and formulate the problem into the Multidimensional 0/1 Knapsack (MDK) problem. Second, we propose a fast approximation algorithm to the MDK problem. Third, we propose a near optimal scheme to improve speed by double partitioning the area. We prove that the output of our algorithm is better than (1-epsilon) of the optimal solution to PESA with a smaller EMR threshold (1-epsilon /2)R{t} and a larger EMR coverage radius (1+epsilon /2)D. We conducted both simulations and field experiments to evaluate the performance of our scheme. Our experimental results show that in terms of charging utility, our algorithm outperforms the comparison algorithms.

Original languageEnglish (US)
Article number9234104
Pages (from-to)48-64
Number of pages17
JournalIEEE/ACM Transactions on Networking
Volume29
Issue number1
DOIs
StatePublished - Feb 2021

Bibliographical note

Funding Information:
Manuscript received July 3, 2018; revised April 8, 2019 and April 30, 2020; accepted September 1, 2020; approved by IEEE/ACM TRANSAC-TIONS ON NETWORKING Editor T. Hou. Date of publication October 20, 2020; date of current version February 17, 2021. This work was supported in part by the National Natural Science Foundation of China under Grant 61872178, Grant 61502229, Grant 61672353, Grant 61472252, Grant 61772046, Grant 61629302, Grant 61672276, Grant 61472184, and Grant 61872082; in part by the Natural Science Foundation of Jiangsu Province under Grant BK20181251; in part by the Fundamental Research Funds for the Central Universities under Grant 14380062; in part by the Fundamental Research Funds for the Central Universities under Grant 021014380079; in part by the Open Research Fund of Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education; in part by the Key Research and Development Project of Jiangsu Province under Grant BE2015154 and Grant BE2016120; in part by the Collaborative Innovation Center of Novel Software Technology and Industrialization, Nanjing University; in part by IIP under Grant 1632051; in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program; and in part by the Guangdong Leading Talent Program under Grant 2016LJ06D658. (Corresponding author: Haipeng Dai.) Haipeng Dai, Nan Yu, Chaofeng Wu, and Guihai Chen are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: haipengdai@nju.edu.cn; gchen@nju.edu.cn; mf1733067@smail.nju.edu.cn; nanyu@smail.nju.edu.cn).

Publisher Copyright:
© 1993-2012 IEEE.

Keywords

  • Inductive charging
  • electromagnetic radiation (EMR)
  • optimization

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