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International Symposium on Information Theory and its Applications

On the Decoding Radius Realized by Low-Complexity Decoded Non-Binary Irregular LDPC Codes

Pavel S. Rybin, Alexey Frolov

Published Oct 1, 2018• 1 citation
Publisher

Abstract

In this paper we consider the low complexity majority-logic decoding algorithm for irregular non-binary low-density parity-check (LDPC) codes. The decoding algorithm is a generalization of the bit-flipping algorithm for binary LDPC codes. The lower estimate on the decoding radius realized by this algorithm is derived for the first time for irregular non-binary LDPC codes. We present the numerical results for the derived lower bound.

DOI
10.23919/isita.2018.8664375

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In this paper we consider the low complexity majority-logic decoding algorithm for irregular non-binary low-density parity-check (LDPC) codes. The decoding algorithm is a generalization of the bit-flipping algorithm for binary LDPC codes. The lower estimate on the decoding radius realized by this algorithm is derived for the first time for irregular non-binary LDPC codes. We present the numerical results for the derived lower bound.
This paper deals with the irregular binary low-density parity-check (LDPC) codes and two iterative low-complexity decoding algorithms. The first one is the majority error-correcting decoding algorithm, and the second one is iterative erasure-correcting decoding algorithm. The lower bounds on correcting capabilities (the guaranteed corrected error and erasure fraction respectively) of irregular LDPC code under decoding (error and erasure correcting respectively) algorithms with low-complexity were represented. These lower bounds were obtained as a result of analysis of Tanner graph representation of irregular LDPC code. The numerical results, obtained at the end of the paper for proposed lower-bounds achieved similar results for the previously known best lower-bounds for regular LDPC codes and were represented for the first time for the irregular LDPC codes.
This paper deals with the irregular binary low-density parity-check (LDPC) codes with the constituent single parity check (SPC) codes and the error-correcting iterative low-complex decoding algorithm. The lower bound on the error fraction, guaranteed corrected by the considered iterative algorithm, was obtained for the irregular LDPC code for the first time in this paper. This lower bound was obtained as a result of analysis of Tanner graph representation of irregular LDPC code. The number of decoding iterations, required to correct the errors, is a logarithmic function of the code length. The numerical results, obtained at the end of the paper for proposed lower bound achieved similar results for the previously known best lower-bounds for regular LDPC codes and were represented for the first time for the irregular LDPC codes.
This paper deals with the Low-Density Parity-Check codes with the constituent Hamming codes (H-LDPC codes) and two different iterative hard-decision low-complexity decoding algorithms. Both algorithms are based on the same main idea: the decreasing of the syndrome weight on each step of the decoding algorithm. The first decoding algorithm uses the properties of the constituent Hamming code. The best known lower-bound on the guaranteed corrected errors fraction for the H-LDPC codes under the first decoding algorithm was obtained in 2011. The second decoding algorithm considers H-LDPC as the irregular LDPC code and uses the well-known majority decoding algorithm. The lower-bound on the guaranteed corrected errors fraction for H-LDPC code under the second decoding algorithm is introduced for the first time in this paper. Numerical results for the lower-bound, obtained in this paper for H-LDPC code under the second decoding algorithm, significantly exceed the numerical results for the best known lower-bounds, obtained previously for H-LDPC code under the first decoding algorithm.
We consider decoding of LDPC codes over GF(q) with a harddecision low-complexity majority algorithm, which is a generalization of the bit-flipping algorithm for binary LDPC codes. A modification of this algorithm with multiple thresholds is suggested. A lower estimate on the decoding radius realized by the new algorithm is derived. The estimate is shown to be better than the estimate for a single threshold majority decoder. At the same time, introducing multiple thresholds does not affect the order of decoding complexity.
Based on decoding performance, complexity and latency of finite-geometry low-density parity-check (LDPC) codes, an efficient decoding algorithm is proposed. The algorithm is a hybrid bit-flipping (BF)/majority-logic (MLG) algorithm. In the algorithm, there are two stages. At the first stage, a code is decoded with bit-flipping (BF) with a small fixed number of iterations. Then the output from bit-flipping (BF) decoder is decoded by majority-logic (MLG) decoding. And in bit-flipping (BF) decoding, a new method is used to find the least reliable position. In the hybrid algorithm, there aren't real operations. Simulation results show that the algorithm provides 0.3dB coding gain over weight bit-flipping (WBF) decoding, and within 1 dB away from sum-product algorithm (SPA) decoding.