Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.
%0 Journal Article
%1 IJACSA.2011.021225
%A Mohammad Rakibul Islam Dewan Siam Shafiullah, Muhammad Mostafa Amir Faisal Imran Rahman
%D 2011
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Min-sum Normalized Optimization \&\#160;LDPC algorithm; codes; factor. min-sum
%N 12
%T Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes
%U http://ijacsa.thesai.org/
%V 2
%X Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.
@article{IJACSA.2011.021225,
abstract = {Low Density Parity Check (LDPC) code approaches Shannon–limit performance for binary field and long code lengths. However, performance of binary LDPC code is degraded when the code word length is small. An optimized min-sum algorithm for LDPC code is proposed in this paper. In this algorithm unlike other decoding methods, an optimization factor has been introduced in both check node and bit node of the Min-sum algorithm. The optimization factor is obtained before decoding program, and the same factor is multiplied twice in one cycle. So the increased complexity is fairly low. Simulation results show that the proposed Optimized Min-Sum decoding algorithm performs very close to the Sum-Product decoding while preserving the main features of the Min-Sum decoding, that is low complexity and independence with respect to noise variance estimation errors.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Mohammad Rakibul Islam Dewan Siam Shafiullah}, Muhammad Mostafa Amir Faisal Imran Rahman},
biburl = {https://www.bibsonomy.org/bibtex/27d0008e402c80ee18ccc55fe1fc91362/thesaiorg},
interhash = {8f9a421d325ca6cf3461399356901c24},
intrahash = {7d0008e402c80ee18ccc55fe1fc91362},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Min-sum Normalized Optimization \&\#160;LDPC algorithm; codes; factor. min-sum},
number = 12,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Optimized Min-Sum Decoding Algorithm for Low Density Parity Check Codes}},
url = {http://ijacsa.thesai.org/},
volume = 2,
year = 2011
}