Title :
An Improved soft decision method in Viterbi decoder using artificial neural networks
Author :
Charei, Qolamreza Nadalinia ; Aghamalek, H.F. ; Razavi, Seyed Mohsen ; Golestanian, M.
Author_Institution :
Fac. of Comput. Sci. & Electr. Eng., Semnan Univ., Semnan, Iran
Abstract :
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.
Keywords :
AWGN channels; Viterbi decoding; error statistics; neural nets; AWGN channels; BER; Viterbi decoder; artificial neural networks; bit error rate; data transmission; decision making; improved soft decision method; signal to noise ratio; Biological neural networks; Bit error rate; Decoding; Signal to noise ratio; Training; Viterbi algorithm; AWGN channel; Bit Error Rate (BER); Soft decision; Viterbi decoder; neural networks;
Conference_Titel :
Pattern Recognition and Image Analysis (PRIA), 2013 First Iranian Conference on
Conference_Location :
Birjand
Print_ISBN :
978-1-4673-6204-7
DOI :
10.1109/PRIA.2013.6528456