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http://dx.doi.org/10.7472/jksii.2012.13.1.1

A Kullback-Leiber Divergence-based Spectrum Sensing for Cognitive Radio Systems  

Thuc, Kieu-Xuan (울산대학교 전기공학부)
Koo, In-Soo (울산대학교 전기공학부)
Publication Information
Journal of Internet Computing and Services / v.13, no.1, 2012 , pp. 1-6 More about this Journal
Abstract
In the paper, an information divergence called Kullback-Leiber divergence, which measures the average of the logarithmic difference between two probability density functions, is utilized to derive a novel method for spectrum sensing in cognitive radio systems. In the proposed sensing method, we test whether the observed samples are drawn from the noise distribution by using Kullback-Leiber divergence. It is shown by numerical results that under the same conditions, the proposed Kullback-Leiber divergence-based spectrum sensing always outperforms the energy detection based spectrum sensing significantly, especially in low SNR regime and in fading circumstance.
Keywords
Cognitive radio; spectrum sensing; Kullback-Leiber divergence;
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1 S. Haykin, "Cognitive radio: brain-empowered wireless communications," IEEE Journal on Selected Areas in Communications, vol. 23, no. 2, pp. 201-220, 2005.   DOI   ScienceOn
2 D. Cabric, A. Tkachenko, and R. W. Brodersen, "Spectrum sensing measurement of pilot, energy, and collaborative detection," Proc. IEEE Military Communications Conf., pp. 1-7, Washington, DC, Oct. 2006.
3 H. S. Chen, W. Gao, and D. G. Daut, "Signature based spectrum sensing algorithm for IEEE 802.22 WRAN," Proc. IEEE Int. Conf. on Communications (ICC), pp. 6487-6492, Glasgow, Scotland, June 2007.
4 M. Oner and F. Jondral, "Cyclostationarity based air interface recognition for software radio systems," Proc. IEEE Radio and Wireless Conf., pp. 263-266, Atlanta, GA, Sept. 2004.
5 M. Oner and F. Jondral, "A cyclostationarity feature detection," Proc. Asilomar Conference on Signals, Systems, and Computer, pp. 806-810, CA, 1994.
6 H. Urkowitz, "Energy detection of unknown deterministic signals," Proceedings of the IEEE, vol.55, no.4, pp. 523-531, April 1967.   DOI   ScienceOn
7 V. I. Kostylev, "Energy detection of a signal with random amplitude," Proceedings of the IEEE Conference on Communications, Newyork, pp. 1606-1610, May 2002.
8 F. Digham, M.-S. Alouini, and M. K. Simon, "On the energy detection of unknown signals over fading channels," IEEE Trans. Commun., vol. 55, no. 1, pp. 21-24, 2007.   DOI   ScienceOn
9 Z. Ye, G. Memik and J. Grosspietsch, "Energy detection using estimated noise variance for spectrum sensing in cognitive radio networks," Proc. IEEE wireless communications and networking Conf. (WCNC), pp. 711-716, Nevada, USA, April 2008.
10 S. Kullback, Information theory and statistics, Dover Publications Inc., Mineola, New York, 1968.
11 T. M. Cover and J. A. Thomas, Elements of information theory, Wiley series in telecommunications, Jonh Wiley & Son, 1991.
12 J. R. Hershey and P. A. Olsen, "Approximating the Kullback-Leiber divergence between Gaussian mixture models," Proc. IEEE Int. Conf. on Acoustics, Speech, and Signal Processing, Vol. 04, pp. 317-320, Hawaii, USA, May 2007.