Automatic modulation classification using hierarchical polynomial classifier and stepwise regression

This paper presents a simplified automatic modulation classification system based on stepwise regression and Hierarchical Polynomial Classifier. The proposed system applies High Order Cumulants of the received signal to a polynomial network in order to calculate their second order polynomial expansion. Then, stepwise regression model is used as a feature selection system; whereas important features are identified and used for the classification problem and the insignificant features are discarded. With this optimization step, the complexity of the classifier is reduced significantly while maintaining the same classification accuracy as the original Hierarchical Polynomial Classifier with all the expanded features.