Modulation Classification of MFSK Modulated Signals Using Spectral Centroid

Abstract

This study utilizes higher order spectrum in order to achieve satisfactory probability of correct classification of M-ary Frequency Shift Keying (MFSK) modulated signals even at low signal to noise ratios. MFSK modulated signals are characterized by a single feature, spectral centroid, which is defined as the centroid value of the diagonal vector of bispectrum matrix. It is observed that conventional K-means clustering is sufficient to achieve satisfactory modulation classification performance using this single feature. The parameters such as bandwidth and chosen FFT size which affect the correct classification ratio at a certain signal to noise ratio are analysed in order to optimize the performance of the proposed method.