Institutional Repository
Technical University of Crete
EN  |  EL

Search

Browse

My Space

Multistatic scatter radio sensor networks for extended coverage

Alevizos Panagiotis, Tountas Konstantinos, Bletsas Aggelos

Full record


URI: http://purl.tuc.gr/dl/dias/F705F16F-595B-4A98-8239-CD5C0B1734B4
Year 2018
Type of Item Peer-Reviewed Journal Publication
License
Details
Bibliographic Citation P.N. Alevizos, K. Tountas and A. Bletsas, "Multistatic scatter radio sensor networks for extended coverage," IEEE Trans. Wirel. Commun., vol. 17, no. 7, pp. 4522-4535, Jul. 2018. doi: 10.1109/TWC.2018.2827034 https://doi.org/10.1109/TWC.2018.2827034
Appears in Collections

Summary

Scatter radio, i.e., communication by means of reflection, has been recently proposed as a viable ultra-low power solution for wireless sensor networks (WSNs). This paper offers a detailed comparison between monostatic and multistatic scatter radio architectures. In monostatic architecture, the reader consists of both the illuminating transmitter and the receiver of signals scattered back from the sensors. The multistatic architecture includes several ultra-low cost illuminating carrier emitters and a single reader. Maximum-likelihood coherent and noncoherent bit error rate (BER), diversity order, average information, and energy outage probability comparison is performed, under dyadic Nakagami fading and filling a gap in the literature. It is found that: 1) diversity order, BER, and tag location-independent performance bounds of multistatic architecture outperform monostatic; 2) energy outage due to radio frequency (RF) harvesting for passive tags, is less frequent in multistatic than monostatic architecture; and 3) multistatic coverage is higher than monostatic. Furthermore, a proof-of-concept digital multistatic scatter radio WSN with a single receiver, four low-cost emitters, and multiple ambiently-powered low-bitrate tags, perhaps the first of its kind, is experimentally demonstrated (at 13 dBm transmission power), covering an area of 3500 m2. Research findings are applicable in the industries of WSNs, RF identification, and emerging Internet-of-Things.

Services

Statistics