Title :
Application of recurrent neural networks to communication channel equalization
Author :
Bradley, M.J. ; Mars, P.
Author_Institution :
Sch. of Eng., Durham Univ., UK
Abstract :
The paper examines the mechanism by which recurrent neural networks (RNNs) achieve equalization whilst operating on simple digital communication channels. The mode of operation is seen to be essentially similar to the conventional decision feedback equalizer (DFE) and the RNN node nonlinearity is identified as a limiting factor. Two versions of an alternative RNN structure are formulated for channels with longer impulse responses based on soft-decision feedback. Simulations demonstrate the improved BER performance compared with the DFE
Keywords :
digital communication; equalisers; error statistics; recurrent neural nets; telecommunication channels; transient response; BER performance; RNN node nonlinearity; communication channel equalization; decision feedback equalizer; digital communication channels; impulse responses; recurrent neural networks; soft-decision feedback; Bit error rate; Communication channels; Decision feedback equalizers; Delay lines; Digital communication; Intersymbol interference; Neural networks; Neurofeedback; Pattern classification; Recurrent neural networks;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479715
