Research on modulation classification using empirical mode decomposition method

Automatic modulation classification (AMC) is a scheme to identify the data samples automatically. Empirical mode decomposition (EMD) is a self-adaptive signal processing method that can be applied to non-linear and non-stationary process perfectly. This paper presents a new method for AMC, using empirical mode decomposition (EMD) method. By utilizing the proposed feature extraction method, the disadvantages of conventional AMC algorithms, such as the feature value is sensitive to outliers in the data, the sample sequence is long and so on could be overcome. The advantage of our new algorithm is we don't need the channel information as a priori. Simulation results show that the performance of the proposed algorithm is comparable with other existing AMC algorithm.