An Improved soft decision method in Viterbi decoder using artificial neural networks

In this paper, the application of artificial neural networks to improve the efficiency of soft decision in Viterbi decoder is proposed. By adding neural network to the decision block of Viterbi decoders and training in supervisor manner, neural networks will be able to anticipate and handle a wide range of distortion. Using the neural networks soft decision in Viterbi decoder block would reduce the bit error rate (BER) in data transmission for AWGN channels. This method can provide low bit BER for data transmission on channels with low signal to noise ratio (SNR). The results show that the proposed technique can improve the efficiency of decision making in comparison with other methods of decision making (soft, hard and slow), in term of BER.

[1]  ADIL GURSEL KARACOR,et al.  Aircraft Classification Using Image Processing Techniques and Artificial Neural Networks , 2011, Int. J. Pattern Recognit. Artif. Intell..

[2]  Mohamed Ibnkahla,et al.  Applications of neural networks to digital communications - a survey , 2000, Signal Process..

[3]  Martin Fodslette Møller,et al.  A scaled conjugate gradient algorithm for fast supervised learning , 1993, Neural Networks.

[4]  Stevan M. Berber,et al.  Soft output decision convolutional (SONNA) decoders based on the application of neural networks , 2008, Eng. Appl. Artif. Intell..

[5]  Stevan M. Berber,et al.  A generalised framework for convolutional decoding using a recurrent neural network , 2003, Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint.

[6]  S.M. Berber.  Soft decision output decoding (SONNA) algorithm for convolutional codes based on artificial neural networks , 2004, 2004 2nd International IEEE Conference on 'Intelligent Systems'. Proceedings (IEEE Cat. No.04EX791).

[7]  Martin Bossert,et al.  Channel Coding for Telecommunications , 1999 .

[8]  Zoran A. Salcic,et al.  Theory and application of neural networks for 1/n rate convolutional decoders , 2005, Eng. Appl. Artif. Intell..

[9]  Jukka Henriksson,et al.  Novel use of channel information in a neural convolutional decoder , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[10]  Rolf Johannesson,et al.  Fundamentals of Convolutional Coding , 1999 .

[11]  Yunghsiang Sam Han,et al.  A maximum-likelihood soft-decision sequential decoding algorithm for binary convolutional codes , 2002, IEEE Trans. Commun..