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http://dx.doi.org/10.5573/ieie.2014.51.6.003

Spectrum Sensing Scheme Using the Ratio of the Maximum and the Minimum of Power Spectrum  

Lim, Chang Heon (Department of Electronic Engineering, Pukyong National University)
Publication Information
Journal of the Institute of Electronics and Information Engineers / v.51, no.6, 2014 , pp. 3-8 More about this Journal
Abstract
Recently, a spectrum sensing technique employing the maximum value of a received power spectrum as a test statistic has been presented in the literature for the purpose of detecting a wireless microphone signal in TV bands This detects the presence of a primary user by comparing the test statistic with some threshold, which depends on the background noise power level as well as a target false alarm rate. Therefore its performance may deteriorate when the noise power uncertainty occurs. As a means to mitigate this difficulty, we present a spectrum sensing strategy adopting the ratio of the maximum and the minimum value of the power spectrum as a test statistic and analyze its performance of spectrum sensing.
Keywords
cognitive radio; feature detection; noise power uncertainty; power spectrum; order statistics;
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1 W. Zhang, H. V. Poor, "Frequency-Domain Correlation: An Asymptotically Optimum Approximation of Quadratic Likelihood Ratio Detectors," IEEE Trans. on Signal Processing, vol. 58, no. 3, pp. 969-979, Mar. 2010.   DOI   ScienceOn
2 C. Hanwen and J. Peissig, "Practical spectrum sensing with frequency-domain processing in cognitive radio," Proceedings of the 20th European Signal Processing Conference (EUSIPCO), pp. 435-439, Aug. 2012
3 H. S. Chen, W. Gao, and D. G. Daut, "Spectrum Sensing for Wireless Microphone Signals," IEEE Annual Communications Society Conference on SECON Workshops, pp. 1-5, June 2008.
4 Y. Zeng, Y. C. Liang, "Eigenvalue-based spectrum sensing algorithms for cognitive radio," IEEE Transactions on Communications, vol. 57, no. 6, pp.1784-1793, June 2009   DOI   ScienceOn
5 X. Y. Hou, N. Morinage, T. Namegawa, "Direct evaluation of radar detection probabilities," IEEE Trans. Aerosp. Electron. Syst., vol. 23, no. 4, pp. 418-424, 1987.
6 V. K. Rohatgi, An Introduction to Probability Theory and Mathematical Statistics, John Wiley & Sons, 1976.
7 G. Staple and K. Werbach, "The End of Spectrum Scarcity", IEEE Spectrum, vol. 41, no. 3, pp. 48-52, 2004.
8 J. Mitola and G. Q. Maguire, "Cognitive radio: making software radios more personal," IEEE Pers. Commun., vol. 6, no. 4, pp. 13-18, Aug. 1999.   DOI   ScienceOn
9 T. Yucek and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," IEEE Comms. Surveys, vol. 11, no. 1, pp. 116-130. 2009.   DOI   ScienceOn
10 Z. Quan, W. Zhang, S. J. Shellhammer, and A. H. Sayed, "Optimal Spectral Feature Detection for Spectrum Sensing at Very Low SNR," IEEE trans. on Commun., vol. 59, no. 1, pp. 210-212, Jan. 2011.