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Noise Uncertainty Study of the Low SNR Energy Detector in Cognitive Radio

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6319))

Abstract

It’s well known that a signal-noise-ratio(SNR) threshold named ”SNR wall” [5] appears in the energy detection due to the noise uncertainty. It makes energy detector(ED) highly non-robust in low SNR environment. In this paper, a log-normal distribution model of the noise power uncertainty is proposed. The detection performances of the energy detector are analyzed based on the proposed noise model. The numerical results illustrate that not only local but also cooperative low SNR Eds are reduced to invalid for a biggish noise power uncertainty.

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References

  1. Haykin, S.: Cognitive radio: Brain-empowered wireless communications. IEEE Journal on Selected Areas in Communications 23(2), 201–220 (2005)

    Article  Google Scholar 

  2. Federal Communications Commission, .Notice of Proposed Rulemaking, in the matter of unlicensed operation in the TV broadcast bands (ET Docket No. 04-186) and additional spectrum for unlicensed devices below 900 MHz and in the 3 GHz band (ET Docket No. 02-380), FCC 04-113 (May 2004)

    Google Scholar 

  3. http://www.ieee802.org/22/

  4. Urkowitz, H.: Energy detection of unkown deterministic signals. Proceedings of the IEEE 55(4), 523–531 (1967)

    Article  Google Scholar 

  5. Tandra, R., Sahai, A.: Fundamental limits on detection in low SNR under noise uncertainty. In: 2005 International Conference on Wireless Networks, Communications and Mobile Computing, pp. 464–469 (2005)

    Google Scholar 

  6. Tandra, R., Sahai, A.: SNR walls for signal detection. IEEE Journal of Selected Topics in Signal Processing 2, 4–17 (2008)

    Article  Google Scholar 

  7. Sonnenschein, A., Fishman, P.M.: Radiometric detection of spreadspectrum signals in noise of uncertain power. IEEE Trans. Aerosp. Electron. Syst. 28, 654–660 (1992)

    Article  Google Scholar 

  8. Zeng, Y., Liang, Y.-C., Hoang, A.T., Peh, E.C.Y.: Reliability of Spectrum Sensing Under Noise and Interference Uncertainty. In: Proc. - IEEE Int. Conf. Commun. Workshops, ICC 2009 (2009)

    Google Scholar 

  9. Lin, W., Zhang, Q.: A design of energy detector in cognitive radio under noise uncertainty. In: ICCS 2008, pp. 213–217 (November 2008)

    Google Scholar 

  10. Letaief, K.B., Zhang, W.: Cooperative Communications for Cognitive Radio Networks. Proceedings of the IEEE 97(5) (May 2009)

    Google Scholar 

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© 2010 Springer-Verlag Berlin Heidelberg

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Ji, G., Zhu, H. (2010). Noise Uncertainty Study of the Low SNR Energy Detector in Cognitive Radio. In: Wang, F.L., Deng, H., Gao, Y., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2010. Lecture Notes in Computer Science(), vol 6319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16530-6_30

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  • DOI: https://doi.org/10.1007/978-3-642-16530-6_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16529-0

  • Online ISBN: 978-3-642-16530-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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