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Optimal Threshold of Welch’s Periodogram for Spectrum Sensing Under Noise Uncertainty

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 322))

Abstract

In this paper, spectrum sensing is investigated when the decision statistic is computed using energy detection (ED) with Welch’s method in the frequency domain. First, we assume an estimated noise variance is used to calculate the threshold, instead of the priori exact noise. We present an analytical model to evaluate the performance of the conventional Welch’s ED. The characteristics of this model are also analyzed to show the effect for the performance of spectrum sensing. Then an optimal threshold is proposed to achieve high detection probability and low false alarm probability at low SNR levels. The analytical results and simulations demonstrate the effectiveness of the proposed optimal threshold.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (61379016、61271180), Major National Science and Technology Projects (2013zx03001015).

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Correspondence to Tingyu Lu .

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© 2015 Springer International Publishing Switzerland

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Lu, T., Zhao, C., Zhang, Y., Peng, X. (2015). Optimal Threshold of Welch’s Periodogram for Spectrum Sensing Under Noise Uncertainty. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_43

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  • DOI: https://doi.org/10.1007/978-3-319-08991-1_43

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08990-4

  • Online ISBN: 978-3-319-08991-1

  • eBook Packages: EngineeringEngineering (R0)

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