Title :
Viterbi algorithm motives in turbo decoding
Author :
Kerner, Michael ; Amrani, Ofer
Author_Institution :
Dept. of Electr. Eng.-Syst., Tel Aviv Univ., Israel
fDate :
29 Aug.-1 Sept. 2005
Abstract :
This work addresses the problem of decoding turbo convolutional codes. In particular, it is concerned with the question of how maximum likelihood sequence estimation (MLSE), in the shape of the Viterbi algorithm (VA), can be utilized in the framework of turbo decoding. It is shown that the conventional VA, which is a soft-input hard-output decoder, can be used for iterative decoding of turbo codes. Moreover, it is demonstrated how the VA can be used for obtaining accurate BER estimation as well as an effective stopping criterion.
Keywords :
convolutional codes; error statistics; iterative decoding; maximum likelihood sequence estimation; turbo codes; BER estimation; Viterbi algorithm; convolutional codes; iterative decoding; maximum likelihood sequence estimation; turbo codes; AWGN; Additive white noise; Bit error rate; Convolutional codes; Iterative algorithms; Iterative decoding; Maximum likelihood decoding; Maximum likelihood estimation; Shape; Viterbi algorithm;
Conference_Titel :
Information Theory Workshop, 2005 IEEE
Print_ISBN :
0-7803-9480-1
DOI :
10.1109/ITW.2005.1531865