Hierarchical classification of modulation signals

This paper addresses the problem of classifying both analog and digital modulation signals. A total of 31 features were used to classify 11 modulation signals plus white noise in a hierarchical fashion. The modulation signals included carrier wave (CW), AM, FM, SSB, FSK2, FSK4, PSK2, PSK4, OOK, QAM16, and QAM32. Genetic algorithm was used to obtain the most effective set of features at each level of the hierarchy. Based on the selected features at each level, a Bayes classifier was then designed to separate the most distinct subclasses at that level. The obtained classification results indicate the effectiveness of the introduced hierarchical classification.