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Automatic modulation classification using statistical moments and a fuzzy classifier

This paper presents a new digital modulation recognition algorithm for classifying baseband signals in the presence of additive white Gaussian noise. An 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. Benefits of this technique are that it is simple to implement, has a generalization property, and requires no a priori knowledge of the SNR, carrier phase, or baud rate of the signal for classification.