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Wireless Communications and Mobile Computing
Volume 2017, Article ID 4316029, 8 pages
https://doi.org/10.1155/2017/4316029
Research Article

Performance of -Norm Detector in Cognitive Radio Networks with Cooperative Spectrum Sensing in Presence of Malicious Users

1Department of ECE, SSN College of Engineering, Chennai, India
2EE Department, Indian Institute of Technology, Madras, India

Correspondence should be addressed to Nandita Lavanis; moc.liamtoh@latidnan

Received 26 July 2016; Revised 5 October 2016; Accepted 18 October 2016; Published 12 January 2017

Academic Editor: Gonzalo Vazquez-Vilar

Copyright © 2017 Nandita Lavanis and Devendra Jalihal. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A cognitive radio network (CRN) with a cooperative spectrum sensing scheme is considered. This CRN has a primary user and multiple secondary users, some of which are malicious secondary users (MSUs). Energy detection at each SU is performed using a -norm detector with , where corresponds to the standard energy detector. The MSUs are capable of perpetrating spectrum sensing data falsification (SSDF) attacks. At the fusion center (FC), an algorithm is used to suppress these MSUs which could be either an adaptive weighing algorithm or one of the following: Tietjen-Moore (TM) test or Peirce’s criterion. This is followed by computation of a test statistic (TS) which is a random variable. In this paper, we assume TS to have either a Gamma or a Gaussian distribution and calculate the threshold accordingly. We provide closed-form expressions of probability of false alarm and probability of miss-detection under both assumptions. We show that Gaussian assumption of TS is more suited in presence of an SSDF attack when compared with the Gamma assumption. We also compare the detection performance for various values of and show that along with the Gaussian assumption is the best amongst all the cases considered.