A simple automatic classifier of PSK and FSK signals using characteristic cyclic spectrum

  • Authors:

  • Antonin Mazalek;Zuzana Vranova;Vojtech Ondryhal;Vaclav Platenka

  • Affiliations:

  • Communication and Information Systems Department, University of Defence, Brno, Czech Republic;Communication and Information Systems Department, University of Defence, Brno, Czech Republic;Communication and Information Systems Department, University of Defence, Brno, Czech Republic;Communication and Information Systems Department, University of Defence, Brno, Czech Republic

  • Venue:
  • MACMESE'11 Proceedings of the 13th WSEAS international conference on Mathematical and computational methods in science and engineering
  • Year:
  • 2011

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Abstract

This article deals with current issues of automatic modulation recognition. As a suitable method, classification investigating characteristic shape of the signal cyclic spectrum was chosen. First, a theoretical analysis of the issue of calculating of cyclic spectrum estimation is made using Strip Spectral Correlation Algorithm (SSCA). In another part, important findings learned during experiments are presented and conditions for obtaining the characteristic cyclic spectrum are determined. After that, a simple automatic classifier of modulations is designed and optimized by using a series of experiments. The classifier designed was tested by using a series of random modulated signal realizations with AWGN noise.