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23891 A distributed compressive sensing technique for data gathering in Wireless Sensor Networks
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Masoum, A. and Meratnia, N. and Havinga, P.J.M. (2013) A distributed compressive sensing technique for data gathering in Wireless Sensor Networks. In: The 4th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2013, 21-24 Oct 2013, Niagara Falls, Ontario, Canada. pp. 207-216. Procedia Computer Science 21. Elsevier. ISSN 1877-0509

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Official URL: http://dx.doi.org/10.1016/j.procs.2013.09.028

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Abstract

Compressive sensing is a new technique utilized for energy efficient data gathering in wireless sensor networks. It is characterized by its simple encoding and complex decoding. The strength of compressive sensing is its ability to reconstruct sparse or compressible signals from small number of measurements without requiring any a priori knowledge about the signal structure. Considering the fact that wireless sensor nodes are often deployed densely, the correlation among them can be utilized for further compression. By utilizing this spatial correlation, we propose a joint sparsity-based compressive sensing technique in this paper. Our approach employs Bayesian inference to build probabilistic model of the signals and thereafter applies belief propagation algorithm as a decoding method to recover the common sparse signal. The simulation results show significant gain in terms of signal reconstruction accuracy and energy consumption of our approach compared with existing approaches.

Item Type:Conference or Workshop Paper (Full Paper, Talk)
Research Group:EWI-PS: Pervasive Systems
Research Program:CTIT-WiSe: Wireless and Sensor Systems
Research Project:GENESIS: Green sEnsor NEtworks for Structural monItoring, FREE: True-wireless mesh networks for transport and logistics
ID Code:23891
Status:Published
Deposited On:23 December 2013
Refereed:Yes
International:Yes
More Information:statisticsmetis

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