A Blind Modulation Classification Method Based on Decision Tree and High Order Cumulants

The classification of modulation schemes will be widely used in future communication systems, among which the classification accuracy and speed of modulation classification methods have always been the focus of the research. Our goal is to simplify the complexity of the classification model and improve the modulation recognition accuracy. In this paper, we propose the blind modulation classification method based on the decision tree and high order cumulants. During the experiments, the results are visualized to observe the effect. By comparing the probability of accurate classification at different signal-to-noise ratios at each stage, it is used as an overall measure of the performance of the entire classifier. Moreover, experiments show that the performance of the independent block level and the whole system has excellent accuracy and stability under the optimal threshold, signal-to-noise ratio, and the number of samples.