Commenced in January 2007
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An Energy Detection-Based Algorithm for Cooperative Spectrum Sensing in Rayleigh Fading Channel

Authors: H. Bakhshi, E. Khayyamian

Abstract:

Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: Cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, Rayleigh fading channel.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1339406

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References:


[1] Federal Communications Commission, “Spectrum policy task force,” Rep. ET Docket no. 02-135, Nov. 2002.
[2] Federal Communications Commission, “Notice of proposed rulemaking and order, Facilitating opportunities for flexible, efficient and reliable spectrum use employing cognitive radio technologies”, FCC 03-322, Dec. 2003.
[3] J. Mitola and G. Q. Maguire, “Cognitive Radio: Making software radios more personal,” IEEE PersCommun., vol. 6, no.4, pp 13-18, Aug. 1999.
[4] J. Mitola, “Cognitive radio: An integrated architecture for software defined radio,” PhD. Diss., Royal Institute of Technology, Stockholm, Sewden, 2000.
[5] D. Cabric, S. Mishra, R. Brodersen, “Implementation issues in spectrum sensing for cognitive radio”. Asilomar Conf. on Signals, Systems and Computers, November 2004, vol. 1, pp. 772–776.
[6] T. Yucek, H. Arslan, “A survey of spectrum sensing algorithms for cognitive radio applications”, IEEE Commun. Surv. Tutor, 2009, 11, pp. 116–130.
[7] Z. Chair and P. K. Varshney, “Optimal data fusion in multiple sensor detection systems,” IEEE Trans. Aerosp. Electron. Syst., vol. 22, no. 1, pp. 98–101, Jan. 1986.
[8] Z. Quan, S. Cui, and A. H. Sayed, “Optimal linear cooperation for spectrum sensing in cognitive radio networks,” IEEE J. Sel. Topics Signal Process. vol. 2, no. 1, pp. 28–40, Feb. 2008.
[9] H. Sun, A. Nallanathan, C. X. Wang and Y. Chen, “Widband Spectrum Sensing for Cognitive Radio Networks: A Survey,” Wireless Communications, IEEE, vol. 20, no. 2, pp. 74–81, 2013.
[10] Y.-C. Liang, Y. Zeng, E. C. Y. Peh, and A. T. Hoang, “Sensing throughput tradeoff for cognitive radio networks,” IEEE Trans. Wireless Commun., vol. 7, no. 4, pp. 1326–1337, Apr. 2008.
[11] H. Urkowitz, “Energy detection of unknown deterministic signals,” Proc. IEEE, vol. 55, no. 4, pp. 523–531, Apr. 1967.
[12] S. Atapattu, C. Tellambura, and H. Jiang, Energy Detection for Spectrum Sensing in Cognitive Radio. Springer, 2014.
[13] F. F. Digham, M. S. Alouini, and M. K. Simon, “On the energy detection of unknown signals over fading channels,” IEEE Trans on Communication., vol. 55, no. 1, pp. 21–24, Jan. 2007.
[14] T. Salman, A. Badawy, T.M. Elfouly, T. Khattab, A. Mohamed, "Non-data-aided SNR estimation for QPSK modulation in AWGN channel." Wireless and Mobile Computing, Networking and Communications (WiMob), IEEE 10th International Conference on. Oct. 2014 pp. 611-616.
[15] A. Wiesel, J. Goldberg, and H. Messer, “Non-data-aided signal to noise- ratio estimation,” in Communications, ICC 2002. IEEE International Conference on,vol. 1, pp. 197–201.
[16] R. Lopez-Valcarce and C. Mosquera, “Sixth-order statistics-based nondata aided SNR estimation,” IEEE Communications Letters, vol. 11, no. 4, pp. 351–353, April 2007.
[17] W. Zhang, R. K. Mallik, and K. B. Letaief, “Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks,” IEEE Trans. on Wireless Comm., vol. 8, no. 8, pp. 5761-5766, December 2009.
[18] Su-wen, W.J. kang, Z. Ling, Q. Ming, “SNR-based weighted cooperative spectrum sensing in cognitive radio networks,” ELSEVIER, The Journal of China Universities of Posts and Telecommunications, Vol. 17, Issue 2, pp. 1-7, April 2010.