A decision feedback recurrent neural equalizer for digital communication

An important problem in high density digital magnetic recording system is that of channel equalization, that is, removal of distortions introduced by linear or nonlinear message corrupting mechanisms in the reconstruction of the original symbols. Severe nonlinear distortions in high density digital magnetic recording systems can make it difficult for conventional equalizers to reconstruct the originally recorded symbols. In this paper, we propose a Decision Feedback Recurrent Neural Equalizer (DFRNE) with a simple structure, which can recover the original symbols correctly under severe nonlinear distortion.