Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size

<p>For a wireless sensor network (WSN) with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. We assume that the signal power attenuates as a function of the distance from the...

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Main Authors: Niu Ruixin, Varshney Pramod K.
Format: Article
Language:English
Published: SpringerOpen 2005-01-01
Series:EURASIP Journal on Wireless Communications and Networking
Subjects:
Online Access:http://dx.doi.org/10.1155/WCN.2005.462
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spelling doaj-b4d70dd031174f0480126fe2e1a699282020-11-24T23:56:31ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992005-01-0120054462472Distributed Detection and Fusion in a Large Wireless Sensor Network of Random SizeNiu RuixinVarshney Pramod K.<p>For a wireless sensor network (WSN) with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. We assume that the signal power attenuates as a function of the distance from the target, the number of sensors follows a Poisson distribution, and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for system-level detection performance are provided. This fusion rule can achieve a very good system-level detection performance even at very low signal-to-noise ratio (SNR), as long as the average number of sensors is sufficiently large. For all the different system parameters we have explored, the proposed fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. The problem of designing an optimum local sensor-level threshold is investigated. For various system parameters, the optimal thresholds are found numerically by maximizing the deflection coefficient. Guidelines on selecting the optimal local sensor-level threshold are also provided.</p> http://dx.doi.org/10.1155/WCN.2005.462wireless sensor networksdistributed detectiondecision fusiondeflection coefficient
collection DOAJ
language English
format Article
sources DOAJ
author Niu Ruixin
Varshney Pramod K.
spellingShingle Niu Ruixin
Varshney Pramod K.
Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
EURASIP Journal on Wireless Communications and Networking
wireless sensor networks
distributed detection
decision fusion
deflection coefficient
author_facet Niu Ruixin
Varshney Pramod K.
author_sort Niu Ruixin
title Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
title_short Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
title_full Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
title_fullStr Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
title_full_unstemmed Distributed Detection and Fusion in a Large Wireless Sensor Network of Random Size
title_sort distributed detection and fusion in a large wireless sensor network of random size
publisher SpringerOpen
series EURASIP Journal on Wireless Communications and Networking
issn 1687-1472
1687-1499
publishDate 2005-01-01
description <p>For a wireless sensor network (WSN) with a random number of sensors, we propose a decision fusion rule that uses the total number of detections reported by local sensors as a statistic for hypothesis testing. We assume that the signal power attenuates as a function of the distance from the target, the number of sensors follows a Poisson distribution, and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for system-level detection performance are provided. This fusion rule can achieve a very good system-level detection performance even at very low signal-to-noise ratio (SNR), as long as the average number of sensors is sufficiently large. For all the different system parameters we have explored, the proposed fusion rule is equivalent to the optimal fusion rule, which requires much more prior information. The problem of designing an optimum local sensor-level threshold is investigated. For various system parameters, the optimal thresholds are found numerically by maximizing the deflection coefficient. Guidelines on selecting the optimal local sensor-level threshold are also provided.</p>
topic wireless sensor networks
distributed detection
decision fusion
deflection coefficient
url http://dx.doi.org/10.1155/WCN.2005.462
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