Fuzzy logic classifier for radio signals recognition

Authors

DOI:

https://doi.org/10.26636/jtit.2001.2.57

Keywords:

modulation recognition, fuzzy logic

Abstract

This paper presents a new digital modulation recognition algorithm for classifying baseband signals in the presence of additive white Gaussian noise. Elaborated classification technique uses various statistical moments of the signal amplitude, phase and frequency applied to the fuzzy classifier. Classification results are given and it is found that the technique performs well at low SNR. The benefits of this technique are that it is simple to implement, has generalization property and requires no apriori knowledge of the SNR, carrier phase or baud rate of the signal for classification.

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References

[1] J. Aisbett, "Automatic modulation recognition using time domain parameters", Sig. Proc., vol. 13, no. 3, pp. 323-328, 1987.
View in Google Scholar

[2] E. E. Azzouz and A. K. Nandi, "Automatic identification of digital modulation types", Sig. Proc., vol. 47, pp. 55-69, 1995.
View in Google Scholar

[3] S. L. Marple, Digital Spectral Analysis. Englewood Cliffs, NJ: Prentice Hall, 1987, (Chapter 7).
View in Google Scholar

[4] T. H. Nguyen, M. Sugeno, R. Tong, and R. R. Yager, Theoretical Aspects of Fuzzy Control. New York: Wiley, 1995.
View in Google Scholar

[5] A. Papouli, Probability, Random Variables, and Stochastic Processes. New York: McGraw Hill, 1991.
View in Google Scholar

[6] S. S. Soliman and S. Z. Hsue, "Signal classification using statistical moments", Trans. Commun., vol. 40, no. 5, pp. 908-916, 1992.
View in Google Scholar

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Submitted

2023-04-06

Published

2001-06-30

Issue

Section

RESEARCH ARTICLES

How to Cite

[1]
J. Łopatka and M. Pędzisz, “Fuzzy logic classifier for radio signals recognition”, JTIT, vol. 4, no. 2, pp. 31–34, Jun. 2001, doi: 10.26636/jtit.2001.2.57.

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