Digital Modulation Classification Using the Bees Algorithm and Probabilistic Neural Network Based on Higher Order Statistics

Abstract

There has been an increasing demand for automatic classification of digital signal formats during the past decades, which seems to be a continouning trend in future too. Most of the previously proposed classifiers can only classify a few kinds of digital signals and/or a low order of digital signals. In addition, They usually require a high level of Signal to Noise Ratio (SNR). This paper presents a hybrid intelligent system for recognition of digital signal types, including three main modules: a feature extraction module, a classifier module, i.e., a Probabilistic Neural Networks (PNN), and an optimization module. Simulation results validate the high recognition accuracy of the proposed system even at low SNRs.