Map-Based Compressive Sensing Model for Wireless Sensor Network Architecture, A Starting Point

Mohammadreza Mahmudimanesh; Abdelmajid Khelil; Nasser Yazdani

Mobile Wireless Middleware, Operating Systems, and Applications - Workshops. Mobilware 2009 Workshops, Berlin, Germany, April 2009, Revised Selected Papers

Research Article

Map-Based Compressive Sensing Model for Wireless Sensor Network Architecture, A Starting Point

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@INPROCEEDINGS{10.1007/978-3-642-03569-2_8,
    author={Mohammadreza Mahmudimanesh and Abdelmajid Khelil and Nasser Yazdani},
    title={Map-Based Compressive Sensing Model for Wireless Sensor Network Architecture, A Starting Point},
    proceedings={Mobile Wireless Middleware, Operating Systems, and Applications - Workshops. Mobilware 2009 Workshops, Berlin, Germany, April 2009, Revised Selected Papers},
    proceedings_a={MOBILWARE WORKSHOPS},
    year={2012},
    month={11},
    keywords={Wireless Sensor Networks Compressive Sensing Map-based WSN WSN Architecture},
    doi={10.1007/978-3-642-03569-2_8}
}

Mohammadreza Mahmudimanesh
Abdelmajid Khelil
Nasser Yazdani
Year: 2012
Map-Based Compressive Sensing Model for Wireless Sensor Network Architecture, A Starting Point
MOBILWARE WORKSHOPS
Springer
DOI: 10.1007/978-3-642-03569-2_8

Mohammadreza Mahmudimanesh¹^,*, Abdelmajid Khelil¹^,*, Nasser Yazdani¹^,*

1: University of Tehran, Technical University of Darmstadt

*Contact email: m.mahmoudi@ece.ut.ac.ir, khelil@informatik.tu-darmstadt.de, yazdani@ut.ac.ir

Abstract

Sub-Nyquist sampling techniques for Wireless Sensor Networks (WSN) are gaining increasing attention as an alternative method to capture natural events with desired quality while minimizing the number of active sensor nodes. Among those techniques, Compressive Sensing (CS) approaches are of special interest, because of their mathematically concrete foundations and efficient implementations. We describe how the geometrical representation of the sampling problem can influence the effectiveness and efficiency of CS algorithms. In this paper we introduce a Map-based model which exploits redundancy attributes of signals recorded from natural events to achieve an optimal representation of the signal.

Keywords: Wireless Sensor Networks Compressive Sensing Map-based WSN WSN Architecture

Published: 2012-11-09

: http://dx.doi.org/10.1007/978-3-642-03569-2_8