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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Online Access: | http://dx.doi.org/10.1155/WCN.2005.462 |
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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 |
work_keys_str_mv |
AT niuruixin distributeddetectionandfusioninalargewirelesssensornetworkofrandomsize AT varshneypramodk distributeddetectionandfusioninalargewirelesssensornetworkofrandomsize |
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1725458001622466560 |