Study on Effective Placement Algorithm for Energy Transmitter in RF Energy Harvesting Wireless Sensor Networks

WANG Hai-dong; LIU Yun-jing; KANG Lin; WU ying-chun

doi:10.3969/j.issn.0372-2112.2020.12.012

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Study on Effective Placement Algorithm for Energy Transmitter in RF Energy Harvesting Wireless Sensor Networks

更新时间：2025-12-08

- Study on Effective Placement Algorithm for Energy Transmitter in RF Energy Harvesting Wireless Sensor Networks
- Acta Electronica Sinica Vol. 48, Issue 12, Pages: 2367-2375(2020)
- 作者机构：
  
  太原科技大学电子信息工程学院,山西,太原,030024
- 作者简介：
- 基金信息：
  
  Program of Key Research and Development Plan of Shanxi Province (No.201903D121139);Youth Fund of National Natural Science Foundation of China (No.61601318);Applied Basic Research Program of Shanxi Province (No.201801D121130);Science and Technology Innovation Team Project of Shanxi Province (No.201705D131025);1331 Key Innovation Team Project of Shanxi Province (No.2017015);The Collaborative Innovation Center of Internet+3D Printing in Shanxi Province
- DOI：10.3969/j.issn.0372-2112.2020.12.012
  CLC： TP311
- Published Online：25 December 2020，
  
  Published：2020
- 稿件说明：
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WANG Hai-dong, LIU Yun-jing, KANG Lin, et al. Study on Effective Placement Algorithm for Energy Transmitter in RF Energy Harvesting Wireless Sensor Networks[J]. Acta Electronica Sinica, 2020, 48(12): 2367-2375.
DOI：

WANG Hai-dong, LIU Yun-jing, KANG Lin, et al. Study on Effective Placement Algorithm for Energy Transmitter in RF Energy Harvesting Wireless Sensor Networks[J]. Acta Electronica Sinica, 2020, 48(12): 2367-2375. DOI： 10.3969/j.issn.0372-2112.2020.12.012.

摘要

射频能量捕获传感网（RF Energy Harvesting Wireless Sensor Network，RFEH-WSN）由专用射频能量源设备（Energy Transmitter，ET）和具有射频能量捕获功能的传感器节点（Energy Harvesting Recevier，简称EHR）组成.该网络解决了传感器网络中电池不易更换与节点能量容易耗尽的问题，使得RFEH-WSN应用前景更加广阔.RFEH-WSN应用中一个值得研究的问题是如何布置ET的充电位置，降低ET能耗且提高覆盖率.已有的工作主要考虑ET布置中单目标优化问题，如最小充电时间、最小功耗、最大覆盖率等.本文以时间最小和覆盖率最大为目标建立多目标优化模型，并提出利用粒子群算法（Particle Swarm Optimization，PSO）求解多目标函数（Multiple Object Program，MOP）的低复杂度近似算法，获得了最优Pareto解集.仿真结果表明，多目标优化可以满足不同情况的需求，提高充电效用.

Abstract

RF energy harvesting wireless sensor network (RFEH-WSN) consists of dedicated energy transmitter (ET) and sensor nodes with RF energy harvesting technology. The RFEH-WSN solves the problems of the battery replacement and node energy depletion

which makes it has more advantages in the future application. How to place ET effectively with minimum energy consumption and maximize overall charging utility is one fundamental issue in RFEH-WSN. In this paper

a new multiple object model is proposed

and the optimization aims of the model are to minimize the charging time and to maximize the coverage. An approximate with low complex algorithm is proposed to solve this multi-object function by PSO optimizer

and from it an optimum pareto solution set is obtained. The simulation results show that the new methods can improve the charging efficiency obviously and satisfy the different demands for lots of application environments.

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