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International Conference on Communications

An Improved Split-Row Threshold Decoding Algorithm for LDPC Codes

Tinoosh Mohsenin, Dean N. Truong, Bevan M. Baas

Published Jun 1, 2009• 13 citations
Publisher

Abstract

We present an improved thresholding LDPC decoding algorithm which outperforms the split-row and original split-row threshold decoders with a small increase in hardware. Simulation results show that the algorithm provides 0.27- 0.50 dB coding gain over split-row, 0.10-0.20 dB over split-row threshold, and is within 0.08-0.13 dB of SPA. Compared with the original threshold algorithm the check node processor's gate count is increased by 3% while total chip area is kept the same.

DOI
10.1109/icc.2009.5198733

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We present an improved thresholding LDPC decoding algorithm which outperforms the split-row and original split-row threshold decoders with a small increase in hardware. Simulation results show that the algorithm provides 0.27- 0.50 dB coding gain over split-row, 0.10-0.20 dB over split-row threshold, and is within 0.08-0.13 dB of SPA. Compared with the original threshold algorithm the check node processor's gate count is increased by 3% while total chip area is kept the same.
The recently proposed split-row decoding algorithm provides significant improvements in the throughput, hardware efficiency and energy efficiency when compared to existing soft decision decoding algorithms at the cost of some error performance loss. In this paper we propose split-row threshold which outperforms the split-row algorithm while maintaining the same level of complexity. Simulation results show that the algorithm provides 0.15-0.2 dB coding gain over split-row decoding and is within 0.15-0.2 dB of SPA and MinSum normalized.
In this paper, we propose a thresholding algorithm to improve Split-Row decoding method of irregular LDPC codes, with maintaining the same level of complexity. We present in this paper a full description of this method and its benefits for various row weight and length code word. In this context, we have performed an implementation on MATLAB of an irregular LDPC codes with different code word and code rate. Simulation results over an additive white Gaussian channel show that the error performance of high row-weight codes with thresholding algorithm is within 0.1–0.2 dB of the normalized Min-Sum algorithm. The study result shows that the thresholding algorithm outperforms original Split Row of irregular codes.
A reduced complexity LDPC decoding method for regular LDPC code is extended to irregular LDPC codes; we present in this paper a full description of this method and its benefits for various row weight and length code word. The Split-Row method makes column processing parallelism easier to exploit and significantly simplifies row processors. Simulation results over an additive white Gaussian channel show that the error performance of high row-weight codes with Split-Row decoding is within 0.3-0.5 dB of the Min-Sum algorithm.
In this paper, we have proposed a novel method of decoding algorithm of irregular LDPC codes. A reduced complexity LDPC decoding method for regular LDPC code is extended to irregular LDPC codes. We present in this paper a full description of this method and its benefits for various row weight and length code word. The Split-Row method makes column processing parallelism easier to exploit and significantly simplifies row processors. Recently, irregular LDPC codes have received a lot of attention by many advanced standard, such as WiFi, WiMAX Mobile and digital video broadcasting (DVB-S2). Hence the idea to develop the “Split-Row Method” for irregular LDPC codes. In this context, we have performed an implementation on MATLAB of an irregular LDPC codes with different code word and code rate; simulation results over an additive white Gaussian channel show that the error performance of high row-weight codes with Split-Row decoding is within 0.3–0.5 dB of the Min-Sum algorithm. The study result shows that the “Split Row Method” is better for irregular code than regular LDPC codes.
The paper presents an improvement of the weighted bit-flipping (WBF) decoding algorithm for LDPC codes proposed by Liu and Pados (2003). Simulation results show that the improved WBF algorithm provides about 0.25 dB coding gain over the Liu–Pados WBF algorithm. Also included in the paper is a simplified loop-detection algorithm, which is much easier to implement than the one proposed by Liu and Pados. The proposed WBF algorithm is particularly effective for decoding LDPC codes whose parity check matrices have large row/column weights such as finite geometry LDPC codes.