Abstract
Spectrum sensing is the key problem for cognitive radio systems. A fast blind sensing method on Multi-Stage Wiener Filter (MSWF) of the received signals is proposed to sense the available spectrum for the cognitive users with the help of the multiple antennas at the receiver of the cognitive users. The greatest advantage of the new method is that it requires no information of the noise power and without any eign-decomposition (or SVD). Both the simulation and the analytical results demonstrate that the proposed method is effective, and almost the same performance compare with the eigen-value based methods.
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References
Haykin, S.: Cognitive radio: brain-empowered wireless communications. IEEE J. Select. Areas Commun. 23, 201–220 (2005)
Zeng, Y.H., Liang, Y.C.: Eigenvalue based spectrum sensing algorithms for cognitive radio. IEEE Trans. Commun. 57, 1784–1793 (2009)
Zeng, Y.H., Liang, Y.C., Zhang, R.: Blindly combined energy detection for spectrum sensing in cognitive radio. IEEE Signal Process. Lett. 15, 649–652 (2008)
Wang, R., Tao, M.X.: Blind Spectrum Sensing by Information Theoretic Criteria for Cognitive Radios. IEEE Transactions on Vehicular Technology 59, 3806–3817 (2010)
Zayen, B., Hayar, A., Nussbaum, D.: Blind spectrum sensing for cognitive radio based on model selection. In: 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom 2008, Singapore, pp. 15–17 (2008)
Wang, Y.X., Lu, G.Y.: DMM Based Spectrum Sensing Method for Cognitive Radio Systems. Journal of Electronics and Information Technology 32, 2571–2575 (2010)
Goldstein, J.S., Reed, I.S., Scharf, L.L.: A multistage representation of the Wiener filter based on orthogonal projections. IEEE Trans. Inf. Theory 44, 2943–2959 (1998)
Duan, F.J.: Bounds for the greatest eigenvalue of the three cornerwise matrix. Journal of Guilin Institute of Electronic Technology 21, 59–61 (2001)
Johnstone, I.: On the distribution of the largest eigenvalue in principal components analysis. Ann. Statist 29, 295–327 (2001)
Bejan, A.: Largest eigenvalues and sample covariance matrices, Tracy-Widom and Painleve II: computational aspects and realization in SPlus with applications (2005), http://www.vitrum.md/andrew/MScWrwck/TWinSplus.pdf
Bao, Z.Q., Wu, S.J., Zhang, L.R.: A Novel Algorithm for Joint Source-Number Detection and DOA Estimation. ACTA ELECTRONICA SINICA 34, 2170–2174 (2006)
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Bao, Z., Lu, G., Yang, G., Qingdong, H. (2012). Fast Blind Spectrum Sensing Method Based on Multi-stage Wiener Filter. In: Ren, P., Zhang, C., Liu, X., Liu, P., Ci, S. (eds) Wireless Internet. WICON 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 98. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30493-4_25
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DOI: https://doi.org/10.1007/978-3-642-30493-4_25
Publisher Name: Springer, Berlin, Heidelberg
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