Title: Events localisation and estimation in wireless sensor networks using compressed sensing

Authors: Yu Liu; Guanhong Lai; Qing Li; Xuqi Zhu; Lin Zhang

Addresses: Key Laboratory of Universal Wireless Communications, Ministry of Education of PRC, Beijing University of Posts and Telecommunications, Beijing 100876, China ' Key Laboratory of Universal Wireless Communications, Ministry of Education of PRC, Beijing University of Posts and Telecommunications, Beijing 100876, China ' Key Laboratory of Universal Wireless Communications, Ministry of Education of PRC, Beijing University of Posts and Telecommunications, Beijing 100876, China ' Key Laboratory of Universal Wireless Communications, Ministry of Education of PRC, Beijing University of Posts and Telecommunications, Beijing 100876, China ' Key Laboratory of Universal Wireless Communications, Ministry of Education of PRC, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract: Events localisation and estimation are two major applications of wireless sensor networks (WSNs). However, owing to the noise of wireless sensing and transmission, it is difficult to guarantee the detection accuracy, especially in multiple events scenarios. This paper proposed a multiple events detection method based on compressive sensing (CS) to efficiently achieve the positions and the values of events simultaneously. Moreover, the high redundancy between the sparse signals of adjacent time slots is taken into account by distributed compressive sensing (DCS) to improve the detection accuracy. We also proposed an adaptive CS reconstruction algorithm to deal with the variable sparsity level in practical WSN scenarios. The simulation results show that the proposed method not only outperforms the traditional decentralised detection methods using Bayesian, but also perfectly handles the unknown sparsity level situations.

Keywords: multiple events; events localisation; events estimation; WSNs; wireless sensor networks; DCS; distributed compressive sensing; variable sparsity level; wireless networks; simulation.

DOI: 10.1504/IJAHUC.2014.059915

International Journal of Ad Hoc and Ubiquitous Computing, 2014 Vol.15 No.1/2/3, pp.12 - 22

Received: 21 Dec 2012
Accepted: 22 Aug 2013
Published online: 19 Mar 2014 *

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