DocumentCode
1775073
Title
Gibbs sampling based parameter estimation for RSC sub-codes of turbo codes
Author
Peidong Yu ; Jing Li ; Hua Peng
Author_Institution
Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou, China
fYear
2014
fDate
23-25 Oct. 2014
Firstpage
1
Lastpage
5
Abstract
This paper deals with the Bayesian parameter estimation for recursive convolutional sub-codes of turbo codes. A Monte Carlo method named Gibbs sampling is employed for this problem. The involved conditional probabilities of the encoder coefficients and the coded sequences are derived. Simulation results show that the proposed algorithm improves the estimation accuracy substantially.
Keywords
Bayes methods; Monte Carlo methods; recursive estimation; turbo codes; Bayesian parameter estimation; Gibbs sampling; Monte Carlo method; RSC subcodes; coded sequences; conditional probabilities; encoder coefficients; estimation accuracy; recursive convolutional subcodes; turbo codes; Bayes methods; Convolution; Convolutional codes; Estimation; Parameter estimation; Signal processing algorithms; Turbo codes; Gibbs sampling; error correcting coding; parameter estimation; recursive systematic convolutional (RSC) code; turbo code;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications and Signal Processing (WCSP), 2014 Sixth International Conference on
Conference_Location
Hefei
Type
conf
DOI
10.1109/WCSP.2014.6992195
Filename
6992195
Link To Document