A New Approach to Design Autonomous Wireless Sensor Node Based on RF Energy Harvesting System

Abstract

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 normalm from the wireless nodes when the Wireless Sensor Network (WSN) has 100 nodes evenly spread over an area of 300 × 300 m2 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.

Cantilevered Piezoelectric Micro Generator Design Issues and Application to the Mining Locomotive

“…The wireless communications domain also interests the operability of a WS powered by a PMG. This is because it is necessary to propose energy consumption models of WSs that are quite complete [33][34][35] to be able to predict the reliability of the autonomous WS. Intending to an optimal solution, we must also consider the solutions proposed in recent years, aiming to minimize the energy budget of the WSs [36][37][38][39].…”

“…Energy for the transmission of bits-data, E tx depends on the distance d between the WS and the sink and the path loss exponent [66]. Assuming that the transmission distances are greater than 88 m as in [34], this energy is expressed as follows:…”

“…To accomplish this, some research uses the duty cycle strategy, which is to leave the WS in standby mode until the harvested energy is sufficient [69,108]. In other recent work, the used enslavement parameter is the transmission distance, which is the distance d between the WS and the BS [34,64].…”

Performance Analysis of a User Selection Protocol in Cooperative Networks with Power Splitting Protocol-Based Energy Harvesting Over Nakagami-m/Rayleigh Channels

“…Like in previous studies [33][34][35][36], we conducted Monte Carlo simulations to verify analytical expressions of the OP and EC of the proposed system in the above section. In addition, we investigated the effect of the primary system parameter on the system performance in terms of OP and EC.…”

A Robust Energy Saving Data Dissemination Protocol for IoT-WSNs

“…WSN routing protocols, generally categorized as cluster-based [12] and flat types, could take energy into consideration as an important measure in the path-construction step to prolong WSN lifetime [13]. Cluster-based routing protocols divide the given topology into clusters, and a chosen node (called a cluster head) could manage and control its cluster.…”