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Communication System Recognition by Modulation Recognition

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3124))

Abstract

Communication system recognition is major part of some civilian and military applications. The recognition of the system is done by inspecting the received signal properties like modulation type, carrier frequency, baud rate and so on. Therefore we need Automatic Modulation Recognition (AMR) methods plus carrier and baud rate estimation methods. In this paper we introduce a new AMR method based on time-domain and spectral features of the received signal. We have used neural network as the classifier. Some analog and digital modulations including AM, LSSB, USSB, FM, ASK2, ASK4, ASK8, PSK2, PSK4, PSK8, FSK2, FSK4, FSK8 and MSK are considered. Then using information from the received signal like baud rate, carrier frequency and modulating scheme the protocol used for signal transmission is detected.

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References

  1. Hsue, S.Z., Soliman, S.S.: Automatic modulation recognition of digitally modulated signals. In: Lecture Notes in MILCOM 1989, vol. 3, pp. 645–649 (1989)

    Google Scholar 

  2. Ghani, N., Lamontagne, R.: Neural networks applied to the classification of spectral features for automatic modulation recognition. In: Lecture Notes in MILCOM 1993, vol. 1, pp. 111–115 (1993)

    Google Scholar 

  3. Mobasseri, B.: Digital modulation classification using constellation shape. Signal Processing, 251–277 (2000)

    Google Scholar 

  4. Taira, S.: Automatic classification of QAM signals by neural networks. In: Lecture Notes in ICASSP 2001, vol. 2, pp. 1309–1312 (2001)

    Google Scholar 

  5. Wong, M.L.D., Nandi, A.K.: Automatic modulation recognition using spectral and statistical features with multi layer perceptrons. In: Lecture Notes in Sixth international symposium on Signal processing and its application, vol. 2, pp. 390–393 (2001)

    Google Scholar 

  6. Hung, C.Y., Polydoros, A.: Likelihood methods for MPSK modulation classification. IEEE Trans. On Communication, 1493–1503 (1995)

    Google Scholar 

  7. Polydoros, A., Kim, K.: On detection and classification of quadrature digital modulations in broad-band noise. IEEE Trans. On Communication, 1199–1211 (1990)

    Google Scholar 

  8. Boudreau, D., Dubuc, C., Patenaude, F.: A fast automatic modulation recognition algorithm and its implementation in a spectrum monitoring application. In: Lecture Notes in MILCOM 2000, vol. 2, pp. 732–736 (2000)

    Google Scholar 

  9. Hong, L., Ho, K.C.: BPSK and QPSK modulation classification with unknown signal levels. In: Lecture Notes in MILCOM 2000, vol. 2, pp. 976–980 (2000)

    Google Scholar 

  10. Lichun, L.: Comments on signal classification using statistical moments. IEEE Trans. On Communication, 1199–1211 (2002)

    Google Scholar 

  11. Louis, C., Sehier, P.: Automatic modulation recognition with hierarchical neural networks. In: Lecture Notes in MILCOM 1994, vol. 3, pp. 713–717 (1994)

    Google Scholar 

  12. Delgosh, F.: Digital modulation recognition, Master’s Thesis, Sharif Industrial university (1998)

    Google Scholar 

  13. Carlson, A.B., Crilly, P.B., Rutledge, J.C.: Communication systems, 4th edn. McGraw-Hill, New York (2001)

    Google Scholar 

  14. Proakis, J.G.: Digital communication, 2nd edn. McGraw Hill international edition, New York (1989)

    Google Scholar 

  15. Azzouz, E.G., Nandi, A.K.: Automatic modulation recognition of communication signals. Kluwer Academic Publishers, Boston (1996)

    Google Scholar 

  16. Wegener, A.W.: Practical techniques for baud rate estimation. In: Lecture Notes in ICASSP 1992, vol. 4, pp. 681–684 (1992)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Attar, A.R., Sheikhi, A., Zamani, A. (2004). Communication System Recognition by Modulation Recognition. In: de Souza, J.N., Dini, P., Lorenz, P. (eds) Telecommunications and Networking - ICT 2004. ICT 2004. Lecture Notes in Computer Science, vol 3124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27824-5_16

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  • DOI: https://doi.org/10.1007/978-3-540-27824-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22571-3

  • Online ISBN: 978-3-540-27824-5

  • eBook Packages: Springer Book Archive

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