DocumentCode :
291096
Title :
Hidden Markov models for the burst error statistics of Viterbi decoding
Author :
Chao, Chi-chao ; Yao, Yuh-Lin
Author_Institution :
Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Volume :
2
fYear :
1993
fDate :
23-26 May 1993
Firstpage :
751
Abstract :
The method of the hidden Markov model (HMM) is used to develop a Markov chain model for the burst error statistics of the Viterbi algorithm. Though only the case of Viterbi decoding is considered, the results presented can be applied to other applications of the Viterbi algorithm. Such a model can be used to generate the output sequence with little cost when compared with the real simulation of the Viterbi algorithm, and it provides a basis for studying other system parameters. The HMM developed generally performs better than the geometric model proposed by R. L. Miller et al. (1981) and in most cases better than the model by C.-C. Chao and R. J. McEliece (1990). It requires many fewer parameters than the model by Chao and McEliece for convolutional codes of large constraint length
Keywords :
Viterbi decoding; convolutional codes; error statistics; hidden Markov models; sequences; HMM; Viterbi decoding; burst error statistics; constraint length; convolutional codes; cost; hidden Markov model; output sequence; Algorithm design and analysis; Chaotic communication; Concatenated codes; Convolutional codes; Costs; Error analysis; Hidden Markov models; Maximum likelihood decoding; Solid modeling; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, 1993. ICC '93 Geneva. Technical Program, Conference Record, IEEE International Conference on
Conference_Location :
Geneva
Print_ISBN :
0-7803-0950-2
Type :
conf
DOI :
10.1109/ICC.1993.397374
Filename :
397374
Link To Document :
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