Modulation Type Recognition of OFDM Signals Based on EMD

Article Preview

Abstract:

This paper used the Empirical Mode Decomposition (EMD) ,solving the problem of the modulation type recognition of Orthogonal Frequency Division Multiplexing (OFDM) on blind signal Processing of communication .This method uses the characteristics of the OFDM' envelope nearly Gaussian .Using the EMD decomposition algorithm of signal decomposition, extract the intrinsic mode function (IMF) after signal decomposition and computes the correlation co-efficient of IMF and the original signal as the recognition feature .So as to achieve that identification the OFDM signals and single carrier linearly digitally modulated (SCLD) signals (MFSK(2FSK, 4FSK), MPSK(BPSK, QPSK)) without prior knowledge. Experiments show that this method has a good performance with less computation, and this method also has well Real-time and robustness compare with the methods of the wavelet transform and the higher order cumulants.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

670-673

Citation:

Online since:

December 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] C.X. Fan: Communication Principle. (National Defenses Industry Press, 2012), p.252.

Google Scholar

[2] Y.S. Li, L. M, L. xia: Electronic Information Warfare Technology, 2012. No. 27 (4), pp.1-4.

Google Scholar

[3] H. Liang, HOKC: IEEE MIL-COM, 1999, No. 1, pp.437-431.

Google Scholar

[4] PUNCHIHEWA A, ZHANG Q, DOBRE O A, et al: IEEE Transactions on Wireless Communications, Vol. 9 (2010) No. 8, pp.2588-2599.

Google Scholar

[5] Y.R. Zhu, B. Tian, J.K. Jin, Y.J. Sun, K.C. Yi. Journal of XidianUniversity(Natural Sciences), 2012, No. 39(1), pp.17-21.

Google Scholar

[6] Q.P. Jiang, S.Z. Yang, T.Q. Zhang. Journal of Huazhong University, 2010, No. 38 (2), pp.118-121.

Google Scholar

[7] H. N E, S. Z, Long, S R. The empirical mode decomposition and the hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of Royal Society, 1998, 44: 903~995.

Google Scholar

[8] Karel ULOVEC. Radio Engineering Vol. 17(2008), No. 1, pp.50-52.

Google Scholar