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A Statistical Moment Deviation Approach to Identify Outliers in Collaborative Spectrum Sensing for Cognitive Radio

Javied, Asad, Rajasegarar, Sutharshan, Arshad, Kamran and Moessner, Klaus (2012) A Statistical Moment Deviation Approach to Identify Outliers in Collaborative Spectrum Sensing for Cognitive Radio [Working Paper]

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Abstract

Cognitive radio is an enabling technology that allows opportunistic users to reuse licensed spectrum in order to overcome the artificial spectrum scarcity. In cognitive radio networks, opportunistic users collaboratively perform spectrum sensing to detect the presence of incumbent users. Collaborative Spectrum Sensing (CSS) performance suffers due to the presence of malicious users. We propose a robust malicious user detection algorithm which exploits inherent statistical moments of the sensing observations from collaborating users to identify malicious users among them. In this way, CSS performance is improved by detecting and marginalizing the effects of malicious users.

Item Type: Working Paper
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Communication Systems Research
Authors :
NameEmailORCID
Javied, Asada.javied@surrey.ac.uk
Rajasegarar, Sutharshan
Arshad, Kamran
Moessner, Klausk.MOESSNER@surrey.ac.uk
Date : July 2012
Contributors :
ContributionNameEmailORCID
http://www.loc.gov/loc.terms/relators/AUTJavied, Asada.javied@surrey.ac.uk
Depositing User : Asad Javied
Date Deposited : 09 Nov 2017 14:24
Last Modified : 09 Nov 2017 14:24
URI: http://epubs.surrey.ac.uk/id/eprint/844720

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