A NEW ADAPTIVE EQUALIZER STRUCTURE FOR NONLINEAR CHANNELS

Based on the analysis of nonlinear channel models,a new connectionist model ofadaptive equalizer is constructed.Comparing with the connectionist model using the Volterraseries to extend the input vector space,the number of weights with the new structure is reducedsignificantly.It is shown by simulations that the weight values of the new scheme converge to theoptimal values closely for non-minimum phase channels as well minimum phase channels,if thechannel noise is small enough.Testing results of the BER(Bit Error Rate)tell us that the newadaptive equalizer for nonlinear channels is superior to the conventional linear equalizers in theequalization performances.

A new adaptive equalizer structure for nonlinear channels

Based on the analysis of nonlinear channel models,a new connectionist model of adaptive equalizer is constructed.Comparing with the connectionist model using the Volterra series to extend the input vector space,the number of weights with the new structure is reduced significantly.It is shown by simulations that the weight values of the new scheme converge to the optimal values closely for non-minimum phase channels as well minimum phase channels,if the channel noise is small enough.Testing results of the BER(Bit Error Rate)tell us that the new adaptive equalizer for nonlinear channels is superior to the conventional linear equalizers in the equalization performances.