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Y. Zeng and Y.-C. Liang, “Covariance Based Signal Detections for Cognitive Radio,” 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, Dublin, 17-20 April 2007, pp. 202-207.

has been cited by the following article:

• TITLE: A New Method for Sensing Cognitive Radio Network under Malicious Attacker

  AUTHORS: Shaahin Tabatabaee, Vahid Tabataba Vakili

  KEYWORDS: Cognitive Radio; LMS Algorithm; Fusion Center; Malicious User; SSDF Attack

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.6 No.1, January 29, 2013

  ABSTRACT: Cognitive radio has been designed for solving the problem of spectrum scarcity by using the spectrum of primary users who don’t use their spectrum on that time. For sensing the spectrum, collaborative spectrum sensing has been utilized because of robustness. In this paper, a new collaborative spectrum method is proposed based on Least Mean Square (LMS) algorithm. In this scheme, the weights of secondary users were updated in time and finally the sensing results were combined in the fusion center based on their trusted weights. Simulation results show that the proposed scheme can significantly reduce the effects of Spectrum Sensing Data Falsification (SSDF) attackers, when they are smart malicious, and even percentage of malicious users are more than trusted users.