Robust recognition of linear and nonlinear digital modulations of RRC pulse trains

TLDR: Simple and robust features to distinguish continuous-phase frequency shift keying from quadrature amplitude and phase shift modulations are proposed and performance is compared to the wavelet based feature that uses support vector machines for classification.

Abstract: In this paper we propose simple and robust features to distinguish continuous-phase frequency shift keying from quadrature amplitude and phase shift keying modulations. Robustness is tested in the presence of SNR estimation offset, block and correlated fast fading, lack of symbol and sampling synchronization, and carrier offset. The features are based on sample mean and sample variance of the imaginary part of the product of two consecutive complex signal values. Root raised cosine pulses are used to generate the linearly modulated signals. Root raised cosine as well as rectangular shaped instantaneous frequency pulses are used in designing the continuous-phase frequency shift keying signals. Support vector machines are employed to distinguish the signals. One benefit of using support vector machines is that it requires very few realizations for training. Moreover, no a priori information is required about carrier amplitude, carrier phase, carrier offset, symbol rate, pulse shape and initial symbol phase. Performance of the proposed feature is compared to the wavelet based feature that uses support vector machines for classification.