Editorial
International Journal of Distributed Sensor Networks
2017, Vol. 13(6) Ó The Author(s) 2017 DOI: 10.1177/1550147717712838 journals.sagepub.com/home/ijdsn
Radio frequency energy harvesting for
wireless sensor networks
The need for the battery-free devices is increasing dra-matically in many applications including medical and environmental monitoring, electric car charging, and wireless sensor networks.1–4 For wireless sensor net-works, energy harvesting (EH) techniques based on various types of energy resources such as solar energy, thermal energy, radio frequency (RF) energy, and piezoelectric energy have been developed. Of these techniques, we particularly focus on the ambient RF EH. The systems harvesting ambient RF energy exploit energy sources already present in the surrounding environments, namely, TV, radio, cellular, satellite, and Wi-Fi systems.5,6
Ambient wireless EH technologies are generally used for low-power standalone electronics. EH from the sur-rounding RF environments can be an option to recharge wireless sensor networks. The amount of energy harvested from ambience primarily depends on the type of the harvesting device and the type of energy source. The harvested energy from ambience and the density of incident power according to the type of energy source are summarized in Georgiou et al.7 In the case of wireless LAN, for instance, the peak power density ranges from 30 pW/cm2to 13.36 mW/cm2with typical transmit power, channel status, and the distance between transmitter and receiver.
If ambient energy sources are not available, wireless power transfer (WPT) can be a powerful technique to recharge devices for their sustainable operation.8 The WPT can be classified into near-field (NF) WPT, and far-field (FF) WPT, depending on the distance between the transmitter and the receiver.9–11Most of NF-WPT techniques are induction-based: magnetic induction (or inductive power transfer (IPT)) and electrostatic induc-tion (or capacitive power transfer (CPT)).12The IPT is able to recharge the sensor devices with charging power ranging from low level (\1 W) to high level (.1 kW).13 Particularly, the high-power IPT has recently emerged as an attractive means of electric car charging. The CPT is suitable for low-power biomedi-cal devices and mobile devices.14The FF-WPT is based on magnetic resonance with RF. In RF-based WPT, a dedicated power beacon can be used for recharging
while data are transmitted simultaneously. Wireless sys-tems in support of simultaneous power and data trans-fer at diftrans-ferent frequency bands are known as out-band system, whereas those working in the same frequency band are known as in-band systems.10
In the paper ‘‘Wireless-powered cooperative energy aware anycast routing in wireless sensor networks,’’ authors present a wireless-powered cooperative energy aware anycast routing protocol. Selection of relays with optional capability of EH and routing to destination are investigated with wireless sensor networks. They found from their study that maximization of lifetime and reduction in energy consumption of cooperative wireless sensor networks can be obtained by relays capable of EH. In another paper ‘‘Performance analysis of the clustering-based multi-hop wireless EH sensor networks over symmetric and asymmetric fading chan-nels,’’ authors investigated clustering-based multi-hop relaying sensor network. They also considered relays capable of EH and proposed a relay selection scheme. It is found from their work that gain obtained from path loss reduction and relay diversity can mitigate potential performance degradation incurred by poor RF-to-DC conversion efficiency. They also showed comparative performance of their scheme with conven-tional multi-hop relaying scheme without clustering. Acknowledgements
Editorial team of the Special Issue thanks all the researchers who contributed to the special issue and reviewers who made remarkable effort during reviewing process. Without their help, it would not have been possible to publish the special issue.
Dongsoo Har1, Seungwook Min2, Todor Mladenov3and Pham Ngoc Son4
1
Cho Chun Shik Graduate School for Green Transportation, KAIST, Daejeon, Republic of Korea
2
Department of Computer Science, Sangmyung University, Seoul, Republic of Korea
3
Intel Mobile Communications, Neubiberg, Germany
4
Faculty of Electrical & Electronics Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam
Creative Commons CC-BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (http://www.creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (http://www.uk.sagepub.com/aboutus/ openaccess.htm).
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