Sensing Confidence Level-Based Cooperative Spectrum Sensing Algorithm

Abstract:

Cooperative spectrum sensing is a key technology to tackle the challenges such as fading or hidden terminal problem in local spectrum sensing of cognitive radio system. Conventional cooperative method can improve the detection performance in some sense, but increase overhead of control channel. In order to reduce the overhead, a new cooperative spectrum sensing algorithm based on confidence level is proposed. In this algorithm, the maximum-eigenvalue-based detection scheme is carried out to obtain the local spectrum detection and the detection probability and false alarm probability of each secondary user are used to estimate the reliability of the sensing decision. The test statistic of the secondary users with high reliability are chosen and sent to fusion center. Then weighted factors of chosen secondary users are derived from creditability values, and the global decision is made by weighted fusion at fusion center. The simulation results show that the proposed algorithm improves the detection probability in the guarantee of the false-alarm probability close to 0 and saves half of the overhead in the control channel.

• Periodical: Applied Mechanics and Materials (Volumes 380-384)
• Pages: 1499-1504
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.380-384.1499
• Online since: August 2013
• Authors: Shi Ding Zhang, Hai Lian Wang, Jing Ping Mei
• Keywords: Cognitive Radio (CR), Maximum Eigenvalue Detection, Reliability, Spectrum Sensing

References

[1] J. Mitola and G. Q. Maguire, Cognitive radio: making software radios more personal, IEEE Personal Communications, vol. 6, no. 4, p.13–18, (1999).

DOI: 10.1109/98.788210

[2] F. E. Visser, G. J. M Janssen and P. Pawelczak, Multinode spectrum sensing based on energy detection for dynamic spectrum access, IEEE Radio Communication Magazine, vol. 42, no. 3, p.20–25, (2007).

DOI: 10.1109/vetecs.2008.293

[3] Y. H. Zeng, C. L. Koh and Y. C. Liang, Maximum eigenvalue detection: theory and application, IEEE International Conference, p.4160–4164, May (2008).

[4] Y. H. Zeng and Y. C. Liang, Eigenvalue based spectrum sensing algorithms for cognitive radio, IEEE Transaction on Communications, vol. 57, no. 6, pp.1784-1793, Jun (2009).

DOI: 10.1109/tcomm.2009.06.070402

[5] A. Ghasemi and E. S. Sousa, Collaborative spectrum sensing for opportunistic access in fading environments, " in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN , 05), Baltimore, MD, USA, pp.131-136, Nov. (2005).

DOI: 10.1109/dyspan.2005.1542627

[6] G. Ganesan and Y. G. Li, Cooperative spectrum sensing in cognitive radio networks, in Proc. IEEE Symp. New Frontiers in Dynamic Spectrum Access Networks (DySPAN05), Baltimore, USA, pp.137-143, (2005).

DOI: 10.1109/dyspan.2005.1542628

[7] Z. Chair and P. K. Varshney, Optimal data fusion in multiple sensor detection systems, IEEE Trans. Aerospace Electron. Syst., pp.98-101, (1986).

DOI: 10.1109/taes.1986.310699

[8] W. Zhang, R. Mallik, and K. Ben Letaief, Cooperative spectrum sensing optimization in cognitive radio networks, " in IEEE International Conference on Communications, ICC, 08, May 2008, p.3411–3415.

DOI: 10.1109/icc.2008.641

[9] F. Visser, G. Janssen, and P. Pawelczak, Multinode spectrum sensing based on energy detection for dynamic spectrum access, " in IEEE Vehicular Technology Conference, VTC Spring, 08, p.1394–1398, May (2008).

DOI: 10.1109/vetecs.2008.293

[10] N. NguyenThanh and I. Koo, An enhanced cooperative spectrum sensing scheme based on evidence theory and reliability source evaluation in cognitive radio context, IEEE Communications Letters, vol. 13, p.492–494, July (2009).

DOI: 10.1109/lcomm.2009.090043

[11] Hiep Vu-Van , Insoo Koo. Cooperative spectrum sensing with collaborative users using individual sensing credibility for cognitive radio network[C]. IEEE Transactions on Consumer Electronics, vol. 57, no. 2, pp.320-326, (2011).

DOI: 10.1109/tce.2011.5955162

[12] Chin Liang Wang, Han Wei Chen and Yu Ren Chou, A credibility-based cooperative spectrum sensing technique for cognitive radio systems VTC spring, 2011 IEEE 73rd, vol. 15-18, pp.1-5, (2011).

DOI: 10.1109/vetecs.2011.5956690

[13] Zhenghao Zhang, Zhu Han, Husheng Li and Depeng Yang, Changxing Pei, Belief propagation based cooperative compressed spectrum sensing wideband cognitive radio networks, IEEE Transactions on Wireless Communications, vol. 10, no. 9, pp.3020-3031, (2011).

DOI: 10.1109/twc.2011.071411.101929

[14] A. M. Tulino and S. Verdú. Random matrix theory and wireless communications, Hanover, USA: now Publishers Inc, (2004).