Analysis on Communication Performance for Secondary Users Classified in Cognitive Radio Networks

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Cognitive Radio Networks is an effective technology and a hot research direction which can solve the problem of deficient resource and revolutionize utilization. In order to enhance the communication efficiency, secondary users are classified by some strategy. We exploit the queuing theory model to research on the communication performance of secondary users, considering primary user as the first grade user and secondary users as other grades users. The research results indicate that the users which have lower priority level are more sensitive than those have higher priority level when primary user appears. Under Primary User Emulation Attack (PUEA), if the number of secondary users reaches 300, the waiting time would larger than 15 minutes. And if the appearance rate of PUEA reaches 4, the break-out rate would be 80%, which is much harmful for CRN.

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668-673

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December 2012

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Claudia Cormio, Kaushik. Adaptive Multiple Rendezvous Control Channel for CR Wireless Ad Hoc Networks. Int. Conference on Pervasive Computing and Communications, 2010, 346-351.

DOI: 10.1109/percomw.2010.5470645

Google Scholar

[2] J. Mitola, G. Maguire, Cognitive Radio: Making Software Radios More Personal. IEEE Personal Commun. Mag., Vol. 6, No. 4, Aug. 1999, 13–18.

DOI: 10.1109/98.788210

Google Scholar

[3] Tevfik Yucek, Huseyin Arslan. A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications. IEEE Communications Surveys & Tutorials, Vol. 11, No. 1, 2009, 116-130.

DOI: 10.1109/surv.2009.090109

Google Scholar

[4] Yao Liu, Peng Ning. Authenticating Primary Users' Signals in CRN via Integrated Cryptographic and Wireless Link Signatures, Symposium on Security and Privacy, 2010, 286-301.

DOI: 10.1109/sp.2010.24

Google Scholar

[5] Nicola Baldo, Alfred Asterjadhi. A Scalable Dynamic Spectrum Access Solution for Large Wireless Networks. International Symposium on Wireless Pervasive Computing, 2010, 430-435.

DOI: 10.1109/iswpc.2010.5483761

Google Scholar

[6] Z. Jin, S. Anand, K. P. Subbalakshmi. Detecting Primary User Emulation Attacks in Dynamic Spectrum Access Networks. ICC IEEE International Conference on Communications, 2009, 1-5.

DOI: 10.1109/icc.2009.5198911

Google Scholar

[7] Baldini G., Sturman T.. Security Aspects in Software Defined Radio and Cognitive Radio Networks: A Survey and A Way Ahead. IEEE Communications Surveys & Tutorials, 2011, 1-25.

DOI: 10.1109/surv.2011.032511.00097

Google Scholar

[8] Wenkai Wang, Husheng Li. Research Article Securing Collaborative Spectrum Sensing against Untrustworthy Secondary Users in Cognitive Radio Networks. EURASIP, 2010, 1-15.

DOI: 10.1155/2010/695750

Google Scholar

[9] Y. H. Tang, X. W. Tang. Queuing Theory[M] (in Chinese). Beijing Science and Technology Press, 2006, 87-139.

Google Scholar