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Merabet, B., Cirio, L., Takhedmit, H., Costa, F., Vollaire, C., Allard, B. and Picon, O. (2009) Low-Cost Converter for Harvesting of Microwave Electromagnetic Energy. IEEE Energy Conversion Congress and Exposition, San Jose, CA, 20-24 September 2009, 2592-2599.
https://doi.org/10.1109/ecce.2009.5316093

has been cited by the following article:

• TITLE: Enslavement of Wireless Sensor Network to an RF Energy Harvesting System

  AUTHORS: Alex Mouapi, Nadir Hakem

  KEYWORDS: WSN, Rectenna, HSMS 2850 Diode, RF/DC Efficiency, Leach Protocol

  JOURNAL NAME: Open Journal of Antennas and Propagation, Vol.5 No.2, June 28, 2017

  ABSTRACT: The abundance of telecommunications systems makes it possible to have somewhat significant quantity of radiofrequency energy in the environment. This energy can be recycled to power ultra-low-power devices such as Wireless Sensor Network (WSN). In this paper, the performance of a miniature RF/DC converter is evaluated in order to enslave a WSN’s per-formance to the amount of the recovered energy. More precisely, a highly sensitive and efficient rectifier is designed to achieve optimum performance in the GSM band. The design method relies on a judicious choice of the rectifying diode which is the basis of most losses in a rectifying antenna (rectenna). Optimum performance is achieved by using the gradient method search proposed in the Advanced Design System (ADS) software. A rectifier based on Schottky diodes HSMS 2850 used in a voltage doubler topology is thus obtained. A maximum RF/DC conversion efficiency of 36% is reached for an RF input power level of 10 dBm. An energy budget of a sensor node in a WSN having an equitable distribution of network loads is then defined and used to evaluate the performance of the WSN regarding the distance at which the Base Station (BS) can be located. The Low Energy Adaptive Clustering Hierarchy (LEACH) protocol is used for this purpose. The distance separating the WSN from the BS is used as the enslavement parameter. Our analysis shows that increasing the duration of each round results in an increase in the range of the WSN. As an example, a network with 100 nodes distributed over an area of may be located at 1.3 km from the base station when each node of the WSN must perform measurements every 1 min.