Table of Contents
Advances in Electrical Engineering
Volume 2015, Article ID 621306, 15 pages
http://dx.doi.org/10.1155/2015/621306
Research Article

Characterization and Modeling of Received Signal Strength and Charging Time for Wireless Energy Transfer

1Computer Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
2Systems Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia
3Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia

Received 30 April 2014; Revised 11 October 2014; Accepted 28 October 2014

Academic Editor: Abdulkareem Adinoyi

Copyright © 2015 Uthman Baroudi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Wireless sensor networks can provide effective means for monitoring and controlling a wide range of applications. Recently, tremendous effort was directed towards devising sensors powered from ambient sources such as heat, wind, and vibration. Wireless energy transfer is another source that has attractive features that make it a promising candidate for supplying power to wireless sensor nodes. This paper is concerned with characterizing and modeling the charging time and received signal strength indicator for wireless energy transfer system. These parameters play a vital role in deciding the geometry of sensor network and the routing protocols to be deployed. The development of communication protocols for wireless-powered wireless sensor networks is also improved with the knowledge of such models. These two quantities were computed from data acquired at various coordinates of the harvester relative to a fixed position of RF energy source. Data was acquired for indoor and outdoor scenarios using the commercially available PowerCast energy harvester and evaluation board. Mathematical models for both indoor and outdoor environments were developed and analyzed. A few guidelines on how to use these models were suggested. Finally, the possibility of harvesting the energy from the ambient RF power to energize wireless sensor nodes was also investigated.