A Modulation Classification Using Joint Moments with Linear Transform

In this paper, a new modulation classification method based on joint moments and linear transform is proposed. In the method, the amplitude and phase of a received signal are linearly transformed, and then joint moments are used to classify modulations. The joint moments are derived in a form of the infinite series of elementary functions to analyze classification error probability. Numerical results of the classification error probability show that appropriate linear transform improves the classification performance significantly, and the method is robust to a carrier frequency offset