Discriminative estimated cumulants-based automatic modulation classification over multipath fading channels

Abstract Automatic modulation classification (AMC) is an essential task in intelligent receivers. AMC research papers over multipath fading channels have two problems. The first problem is the Higher-order moment (HOM)based normalized channel coefficients estimator is not valid for some types of digital modulations. The second problem is poor classification accuracy. This paper solves these problems through significant steps, first, by finding a new HOM-based normalized channel coefficients estimator for all cases of digital modulation types, and second, by finding the mathematical forms of the transmitted signal's estimated normalized HOMs and Higherorder cumulants (HOCs), and third, by selecting the most discriminative estimated HOCs for AMC using features selection algorithms. The simulation results show that the classification accuracy of the selected estimated HOCs, for M-array Phase Shift Keying (MPSK) and M-array quadrature amplitude shift modulation (MQAM) classification is highly improved compared with reference papers. It's 100% for the three-tap multipath channel case, and Signal-to-noise ratio (SNR) values greater than 6 dB.