Automatic modulation classification using polynomial classifiers

Abstract

In this paper, a new automatic modulation classification system using a polynomial classifier is proposed. The feature set used in the proposed system is comprised of second, fourth and sixth higher order cumulants of the received signal. The polynomial classifier expands the feature vector into a higher dimensional space in which the different modulation types are linearly separable. The performance of the proposed system is tested against BPSK, QPSK, 8-PSK, 16-QAM and 64-QAM constellations. Results showed a relatively higher classification rate for all types of modulations compared to previously published results using fourth and sixth order cumulants with other classification schemes. Moreover, the proposed classification scheme has low computational complexity and is more suited for real time applications.