A Least Square Method for Parameter Estimation of RSC Sub-Codes of Turbo Codes

Author

Peidong Yu ; Jing Li ; Hua Peng

Author_Institution

Zhengzhou Inst. of Inf. Sci. & Technol., Zhengzhou, China

Volume

18

Issue

4

fYear

2014

fDate

Apr-14

Firstpage

644

Lastpage

647

Abstract

A new algorithm is developed for parameter estimation of the recursive systematic convolutional sub-codes of turbo codes. It is based on a least square cost function of the encoder coefficients. A simple iterative process assisted by a try-again scheme is designed for the optimization of the cost function. Simulation results show that, compared with the existing method, the new algorithm significantly improves the performance while the complexity is quite reasonable.

Keywords

convolutional codes; iterative methods; least squares approximations; recursive estimation; turbo codes; RSC sub-codes; cost function optimization; encoder coefficients; iterative process; least square cost function; least square method; parameter estimation; recursive systematic convolutional sub-codes; try-again scheme; turbo codes; Convolutional codes; Cost function; Equations; Estimation; Parameter estimation; Turbo codes; Error correcting coding; least square; parameter estimation; recursive systematic convolutional (RSC) codes; turbo codes;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/LCOMM.2014.022514.140086

Filename

6763130