Performance of per tone hammerstein and bilinear recurrent neural network equalizer for wireless OFDM systems

Intersymbol interference (ISI) of the radio propagation through multipath fading channels and nonlinear distortion are major factors that limit the performance of communication systems. In this paper we introduce a new blind adaptive per tone Hammerstein equalizer for OFDM systems. In this scheme, we compare the performance of the blind adaptive per tone Hammerstein equalizer with the blind adaptive per tone bilinear recurrent neural network for wiener system. The dynamic multipath wireless channel is followed by a statistic memoryless model; this forms a wiener system. The results of our simulation indicate that the per tone blind adaptive Hammerstein equalizer has a better BER in comparison with per tone blind adaptive bilinear recurrent neural network equalizer for wiener system in wireless communication.