Mouapi Alex, Hakem Nadir
Underground Communication Research Laboratory, University of Québec in Abitibi-Témiscamingue, 675, 1e avenue, Val-d'Or, QC J9P1Y3, Canada.
Sensors (Basel). 2018 Jan 5;18(1):133. doi: 10.3390/s18010133.
Energy Harvesting techniques are increasingly seen as the solution for freeing the wireless sensor nodes from their battery dependency. However, it remains evident that network performance features, such as network size, packet length, and duty cycle, are influenced by the sum of recovered energy. This paper proposes a new approach to defining the specifications of a stand-alone wireless node based on a Radio-frequency Energy Harvesting System (REHS). To achieve adequate performance regarding the range of the Wireless Sensor Network (WSN), techniques for minimizing the energy consumed by the sensor node are combined with methods for optimizing the performance of the REHS. For more rigor in the design of the autonomous node, a comprehensive energy model of the node in a wireless network is established. For an equitable distribution of network charges between the different nodes that compose it, the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The model considers five energy-consumption sources, most of which are ignored in recently used models. By using the hardware parameters of commercial off-the-shelf components (Mica2 Motes and CC2520 of Texas Instruments), the energy requirement of a sensor node is quantified. A miniature REHS based on a judicious choice of rectifying diodes is then designed and developed to achieve optimal performance in the Industrial Scientific and Medical (ISM) band centralized at 2.45 GHz . Due to the mismatch between the REHS and the antenna, a band pass filter is designed to reduce reflection losses. A gradient method search is used to optimize the output characteristics of the adapted REHS. At 1 mW of input RF power, the REHS provides an output DC power of 0.57 mW and a comparison with the energy requirement of the node allows the Base Station (BS) to be located at 310 m from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m 2 and when each round lasts 10 min . The result shows that the range of the autonomous WSN increases when the controlled physical phenomenon varies very slowly. Having taken into account all the dissipation sources coexisting in a sensor node and using actual measurements of an REHS, this work provides the guidelines for the design of autonomous nodes based on REHS.
能量收集技术越来越被视为解决无线传感器节点电池依赖问题的方案。然而，网络性能特征，如网络规模、数据包长度和占空比，显然仍受回收能量总和的影响。本文提出了一种基于射频能量收集系统（REHS）来定义独立无线节点规格的新方法。为了在无线传感器网络（WSN）的覆盖范围内实现足够的性能，将使传感器节点能耗最小化的技术与优化REHS性能的方法相结合。为了使自主节点的设计更加严谨，建立了无线网络中该节点的综合能量模型。为了在组成网络的不同节点之间公平分配网络负载，为此使用了低能耗自适应聚类分层协议（LEACH）。该模型考虑了五个能量消耗源，其中大部分在最近使用的模型中被忽略。通过使用商用现货组件（德州仪器的Mica2 Motes和CC2520）的硬件参数，对传感器节点的能量需求进行了量化。然后，基于对整流二极管的明智选择，设计并开发了一个微型REHS，以在集中于2.45 GHz的工业科学医疗（ISM）频段实现最佳性能。由于REHS与天线之间不匹配，设计了一个带通滤波器以减少反射损耗。使用梯度法搜索来优化适配后的REHS的输出特性。在输入射频功率为1 mW时，REHS提供0.57 mW的输出直流功率，并且将其与节点的能量需求进行比较后可知，当无线传感器网络（WSN）有100个节点均匀分布在300×300 m²的区域且每轮持续10分钟时，基站（BS）可位于距离无线节点310 m处。结果表明，当受控物理现象变化非常缓慢时，自主WSN的覆盖范围会增加。考虑到传感器节点中共存的所有耗散源并使用REHS的实际测量结果，这项工作为基于REHS的自主节点设计提供了指导方针。
