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

Automatic modulation classification (AMC) is an essential task in intelligent receivers. AMC over multipath fading channels have two problems: The first problem is that the Higher-order moment (HOM)-based normalized channel coefficients estimator is not valid for some types of digital modulations. The second problem is about poor classification accuracy. This study addresses the aforementioned challenges through a multi-pronged approach. Firstly, it introduces a novel HOM-based normalized channel coefficient estimator applicable to a broad spectrum of digital modulation schemes. Secondly, it derives mathematical expressions for the estimated normalized HOMs and Higher-order Cumulants (HOCs) of the transmitted signal. Finally, the research employs feature selection algorithms to identify the most discriminatory estimated HOCs for Adaptive Modulation and Coding (AMC). Simulation results demonstrate that the classification accuracy using estimated Higher-order Cumulants (HOCs) for M-ary Phase Shift Keying (MPSK) and M-ary Quadrature Amplitude Modulation (MQAM) schemes shows significant improvement compared to previous studies. Perfect classification (100% accuracy) is achieved for the 3-tap multipath channel at Signal-to-Noise Ratio (SNR) values exceeding 6 dB, and for the 4-tap multipath channel at SNR values above 7 dB.