Equalization of 8PSK Signals with a Recurrent Neural Network

Authors:
Dong-Chul Park;Young-Soo Song;Dong-Min Woo
Affiliations:
ICRL and Myongji IT Engineering Research Institute, Myong Ji University, Korea;ICRL and Myongji IT Engineering Research Institute, Myong Ji University, Korea;ICRL and Myongji IT Engineering Research Institute, Myong Ji University, Korea
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks, Part III
Year:
2007

Citing 2
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Equalisation of a wireless ATM channel using a pruned recurrent neural network

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Abstract

A novel equalization scheme for a wireless ATM communication channel using a recurrent neural network is proposed in this paper. The recurrent neural network used in this scheme is the Complex Bilinear Recurrent Neural Network (CBLRNN). A reduced version of the CBLRNN for faster and stable convergence is first proposed in this paper. The R-CBLRNN is then applied to equalization of a wireless ATM channel for 8PSK, which has severe nonlinearity and intersymbol interference due to multiple propagation paths. The experiments and results show that the proposed R-CBLRNN gives very favorable results in the Mean Square Error (MSE) criterion over conventional equalizers.