A Fault-Tolerant Cooperative Spectrum Sensing Algorithm over Cognitive Radio Network Based on Wireless Sensor Network

DOI: 10.4236/wsn.2011.33009   PDF   HTML     5,224 Downloads   10,473 Views   Citations


A serious threat to cognitive radio networks that sense the spectrum in a cooperative manner is the transmission of false spectrum sensing data by malicious sensor nodes. SNR fluctuations due to wireless channel effects complicate handling such attackers even further. This enforces the system to acquire authentication. Actually, the decision maker needs to determine the reliability or trustworthiness of the shared data. In this paper, the evaluation process is considered as an estimation dilemma on a set of evidences obtained through sensor nodes that are coordinated in an underlying wireless sensor network. Then, a likelihood-based computational trust evaluation algorithm is proposed to determine the trustworthiness of each sensor node's data. The proposed procedure just uses the information which is obtained from the sensor nodes without any presumptions about node’s reliability. Numerical results confirm the effectiveness of the algorithm in eliminating malicious nodes or faulty nodes which are not necessarily conscious attackers.

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M. Akbari and A. Falahati, "A Fault-Tolerant Cooperative Spectrum Sensing Algorithm over Cognitive Radio Network Based on Wireless Sensor Network," Wireless Sensor Network, Vol. 3 No. 3, 2011, pp. 83-91. doi: 10.4236/wsn.2011.33009.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Federal Communications Commission (FCC), “Spectrum Policy Task Force,” Report ET Docket, No. 02-135, November 2002.
[2] J. Mitola, “Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio,” Ph.D. Thesis, KTH- Royal Institute of Technology, Stockholm, 2000.
[3] Y. C. Liang, Y. Zeng, E. C. Y. Peh and A. T. Hoang, “Sens-ing-Throughput Tradeoff for Cognitive Radio Networks,” IEEE Transactions on Wireless Communication, Vol. 7, No. 4, April 2008, pp. 1326-1337. doi:10.1109/TWC.2008.060869
[4] T. Yucek and H. Arslan, “A Survey of Spectrum Sensing Algorithm for Cognitive Radio Applications,” IEEE Com- munication Survey & Tutorials, Vol. 11, No. 1, Spring 2009, pp. 116-130.
[5] A. Taherpour, Y. Norouzi, M. Nasiri-Kenari, A. Jamshidi and Z. Zeinal-pour-Yazdi, “Asymptotically Optimum Detection of Primary User in Cognitive Radio Networks,” IET Communications, Vol. 1, No. 6, December 2007, pp. 1138-1145. doi:10.1049/iet-com:20060645
[6] S. Tseng, H. Chiang and J. Lehnert, “Parametric density estimation using EM algorithm for collaborative spectrum sensing,” 3rd International Conference on Cognitive Radio Oriented Wireless Network and Communications (CrownCom), Singapore, 15-17 May 2008, pp. 1-6.
[7] S. Shankar, C. Cordeiro and K. Challapali, “Spectrum Agile Radios: Utilization and Sensing Architectures,” Pro- ceedings of IEEE DySPAN, 8-11 November 2005, pp. 160-169.
[8] A. W. Min, K. G. Shin and X. Hu, “At-tack-Tolerant Distributed Sensing for Dynamic Spectrum Access Networks,” 17th IEEE International Conference on Network Protocols, Princeton, 13-16 October 2009, pp. 294-303. doi:10.1109/ICNP.2009.5339675
[9] H. Chen, H. Wu, X. Zhou and C. Gao, “Agent-Based Trust Model in Wireless Sen-sor Networks,” 8th IEEE International Conference on Software Engineering, Artificial Intelligence, Networking, and Paral-lel/Distributed Computing, Qingdao, July-August 2007, pp. 119-124. doi:10.1109/SNPD.2007.122
[10] G. Vijay, E. Bdira and M. Ibnkahla, “Cognitive Approaches in Wireless Sensor Networks: A Survey,” 25th Biennial Symposium on Communications, Kingston, 12- 14 May 2010, pp. 177-180. doi:10.1109/BSC.2010.5472978
[11] A. Ghasemi and E. S. Sousa, “Asymptotic Performance of Collaborative Spectrum Sensing under Correlated Log- Normal Shadowing,” IEEE Communication Letters, Vol. 11, No. 1, January 2007, pp. 34-36.
[12] T. Shu and M. Krunz, “Throughput-Efficient Se-quential Channel Sensing and Probing in Cognitive Radio Networks under Sensing Errors,” Proceedings of ACM Mobi-Com’09, September 2009.
[13] R. Chen, J. M. Park, Y. T. Hou and J. H. Reed, “Toward Secure Distributed Spectrum Sensing in Cognitive Radio Networks,” IEEE Communication Magazine, Vol. 46, No. 4, April 2008, pp. 50-55.
[14] P. Kaligineedi, M. Khabbazian and V. K. Bhargava, “Secure Cooperative Sensing Techniques for Cognitive Radio Systems,” IEEE International Conference on Communications (ICC), Beijing, 19-23 May 2008, pp. 3406- 3410.
[15] S. Xu, Y. Shang and H. Wang, “Double Thresholds based Cooperative Spectrum Sensing against Untrusted Secondary Users in Cognitive Radio Networks,” 69th IEEE conference on Vehicular Technology, Barcelona, 26-29 April 2009, pp. 1-5. doi:10.1109/VETECS.2009.5073511
[16] M. Akbari and A. Falahati, “SSDF Protection in Cooperative Spectrum Sensing Employing a Computational Trust Evaluation Algorithm,” 5th International Symposium on Telecommunication, December 2010.
[17] A. GoldSmith, “Wireless Communication,” Cam-bridge University Press, Cambridge, 2005.
[18] Q. Wang, D. W. Yue and Y. Wang, “Performance Analysis of Spectrum Sensing Using Diversity Technique,” 5th International Confe-rence on Wireless Communication, Networking and Mobile Computing, Beijing, 24-26 September 2009, pp. 1-5. doi:10.1109/WICOM.2009.5301177
[19] W. Zhang, J. Yang, Q. Yan and L. Xiao, “Performance Analysis of Cooperative Sensing with Equal Gain Combining over Nakagami Channels in Cognitive Radio Net- works,” 6th International Conference on Wireless Communication and Mobile Computing, September 2010.
[20] H. G. Kang, I. Song, Y. H. Kim, T. An and D. Kim, “Spectrum Sensing Based on Nonlinear Combining for Cognitive Radio with Receive Diversity,” 44th Annual Confe-rence on Information Sciences and Systems (CISS), Princeton, 17-19 March 2010, pp. 1-6. doi:10.1109/CISS.2010.5464977
[21] C. Yu and K. Chen, “Multiple Systems Sensing for Cognitive Radio Networks over Rayleigh Fading Channel,” Vehicular Technology Conference (VTC), Singapore, 11- 14 May 2008, pp. 1574-1578.
[22] E. D. Kaplan and C. J. Hegarty, “Understanding GPS: Principles and Applications,” 2nd Edition, Artech House Inc., London, 2006.
[23] R. K. Pearson, “Outliers in Process Modeling and Identification,” IEEE Transactions on Control System Tech-nology, Vol. 10, No. 1, January 2002, pp. 55-63. doi:10.1109/PROC.1967.5573
[24] H. Urkowitz, “Energy Detection of Unknown Deterministic Signals,” Proceedings of IEEE, Vol. 55, No. 4, 1967, pp. 523-531. doi:10.1109/PROC.1967.5573
[25] A. Papoulis and S. U. Pillai, “Probability, Random Variables and Stochastic Processes,” 4th Edition, McGraw- Hill, New York, 2002.
[26] R. F. Mills and G. E. Prescon, “A Comparison of Various Radiometer Detection models,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 32, No. 1, January 1996, pp. 467-473. doi:10.1109/7.481289
[27] C. Cordeiro, K. Challapali, D. Birru and S. Shankar, “IEEE 802.22: An Introduction to the First Wireless Standard based on Cognitive Radio,” Journal of Communications, Vol. 1, No. 1, April 2006, pp. 38-47.
[28] H. Kim and K. G. Shin, “Efficient Discovery of Spectrum Oppor-tunities with MAC-Layer Sensing in Cognitive Radio Net-works,” IEEE Transactions on Mobile Computing, Vol. 7, No. 5, May 2008, pp. 533-545.

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