Low-complexity one-dimensional edge detection in wireless sensor networks

Authors:
Marco Martalò;Gianluigi Ferrari
Affiliations:
WASN Laboratory, Department of Information Engineering, University of Parma, Parma, Italy;WASN Laboratory, Department of Information Engineering, University of Parma, Parma, Italy
Venue:
EURASIP Journal on Wireless Communications and Networking - Special issue on signal processing-assisted protocols and algorithms for cooperating objects and wireless sensor networks
Year:
2010

Citing 10
Cited 1

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Elements of information theory

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Fundamentals of statistical signal processing: estimation theory

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Boundary estimation in sensor networks: theory and methods

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Distributed environmental monitoring using random sensor networks

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A survey on sensor networks

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Estimating inhomogeneous fields using wireless sensor networks

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An isotropic universal decentralized estimation scheme for a bandwidth constrained ad hoc sensor network

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Adaptive edge detection with distributed behaviour-based agents in WSNs

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Abstract

In various wireless sensor network applications, it is of interest to monitor the perimeter of an area of interest. For example, one may need to check if there is a leakage of a dangerous substance. In this paper, we model this as a problem of one-dimensional edge detection, that is, detection of a spatially nonconstant one-dimensional phenomenon, observed by sensors which communicate to an access point (AP) through (possibly noisy) communication links. Two possible quantization strategies are considered at the sensors: (i) binary quantization and (ii) absence of quantization. We first derive the minimum mean square error (MMSE) detection algorithm at the AP. Then, we propose a simplified (suboptimum) detection algorithm, with reduced computational complexity. Noisy communication links are modeled either as (i) binary symmetric channels (BSCs) or (ii) channels with additive white Gaussian noise (AWGN).