总能量捕获功率最大化的射频能量源布置方案

RF Energy Source Deployment Schemes Maximizing Total Energy Harvesting Power

射频能量捕获是应对无线网络节点能量受限的有效方法之一。射频能量源(Energy Source,ES)的布置位置决定了各个节点的能量捕获功率。然而,目前几乎没有相关工作研究如何在ESs的候选布置位置中选择合适的布置位置。已知节点位置、ESs的个数以及ESs的候选布置位置,文中研究并设计了最大化节点总能量捕获功率的ES布置方案。首先将该问题建模为0-1整数规划问题,然后分别提出了一种具有较低复杂度的近似比为1-1/e的近似算法和一种能达到更大总能量捕获功率的基于遗传算法的布置算法。仿真结果表明,相比于布置位置随机挑选法,提出的两种算法的总能量捕获功率能提高约50%,而遗传算法可达到比近似算法高约15%的总能量捕获功率。因此,基于遗传算法的布置算法可用于中小规模的ES布置场景,而近似算法可用于大规模的ES布置场景。

Radio frequency (RF) energy harvesting is one of the effective methods to deal with the energy limitation of wireless network nodes.The placement of RF energy sources (ESs) determines the energy harvesting power of each node.However,so far,almost no work has been done to study how to select appropriate deployment locations among the candidate deployment locations of ESs.Given the node locations,the number of ESs and candidate deployment locations of ESs,this paper studied and designed the ES deployment schemes which maximize the total energy harvesting power of nodes.Firstly,the problem is modeled as a 0-1 integer programming problem.Then a low-complexity approximation scheme with approximation ratio (1-1/e) and a genetic algorithm based deployment scheme with higher total energy harvesting power are proposed,respectively.Simulation results show that the proposed schemes improve the total energy harvesting power by about 50% compared to the scheme of randomly selecting the deployment locations,and the total energy harvesting power of genetic scheme can be 15% higher than that of approximation scheme.Therefore,the deployment scheme based on genetic scheme can be used for small and medium-sized ES deployment scenarios,while the approximation scheme can be used for large-scale ES deployment scenarios.