Modulation classifier of digitally modulated signals based on method of artificial neural networks

  • Authors:

  • Marie Richterova;Antonin Mazalek;Karel Pelikan

  • Affiliations:

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

  • Venue:
  • AEE'05 Proceedings of the 4th WSEAS international conference on Applications of electrical engineering
  • Year:
  • 2005

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Abstract

In this paper is described a new original configuration of subsystems for the automatic modulation recognition of digital signals. The signal recognizer being developed consists of five subsystems: (1) adaptive antenna arrays, (2) pre-processing of signals, (3) key features extraction, (4) modulation recognizer and (5) output stage. The choice of maximum value of spectral power density of the normalized-centred amplitude, standard deviation of the absolute value of the centred non-linear component of the instantaneous phase, standard deviation of the absolute value of the normalized-centred instantaneous amplitude, standard deviation of the absolute value of the normalized-centred instantaneous frequency, as key features for the digital modulation recognizer based on the artificial neural networks (ANNs). The new original structure of the recognizer of digital signals is described. The modulation recognizer using the ANNs with two hidden layers. The results are summarized for real signals.