Title :
Improved Check Node Decomposition for Linear Programming Decoding
Author :
Xiaopeng Jiao ; Jianjun Mu
Author_Institution :
Sch. of Comput. Sci. & Technol., Xidian Univ., Xi´an, China
Abstract :
For the linear programming decoding (LPD) proposed by Feldman et al., the number of constraints increases exponentially with check degrees. By decomposing a high-degree check node into a number of degree-3 check nodes, the number of constraints grows linearly with check degrees. In this letter, we show that the size of the LPD can be reduced by decomposing a high-degree check node into a number of degree-4 check nodes. The LPD using the degree-4 decomposition leads to almost the same number of constraints as using the degree-3 decomposition, while the number of auxiliary variable nodes is less than half of the one using the degree-3 decomposition. Moreover, when decomposing a high degree check node into a number of check nodes with degree d, d>4, the number of constraints increases rapidly and the size of the LPD becomes larger than the degree-4 decomposition. It is demonstrated on an LDPC code and a BCH code that the decoding time of the degree-4 decomposition is the smallest among the different decomposition methods.
Keywords :
BCH codes; decoding; linear codes; linear programming; parity check codes; BCH code; LDPC code; LPD; auxiliary variable nodes; check degrees; check node decomposition; linear programming decoding; Block codes; Complexity theory; Iterative decoding; Linear programming; Maximum likelihood decoding; Check node decomposition; high-degree check node; linear block code; linear programming decoding (LPD);
Journal_Title :
Communications Letters, IEEE
DOI :
10.1109/LCOMM.2012.122012.122396