Widely Linear Prediction for Blind Equalization

This paper proposes a new blind equalization scheme based on widely linear (WL) prediction. It permits to compensate non-minimum phase channels with or without spectral nulls, since the received signal can be interpreted as a convolution of a real-valued data sequence and a complex baseband channel. Such a transmission model applies, for instance, to the ASK, OQAM and binary MSK-type modulations. The WL prediction technique uses a linear combination of the complex delayed samples of the received signal and its complex conjugate to predict the current sample. The proposed WL blind equalizer presents a low computational complexity and a higher convergence rate as compared to others blind equalization techniques.