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The symbol flipping decoding algorithms based on prediction (SFDP) for non-binary LDPC codes perform well in terms of error performances but converge slowly when compared to other symbol flipping decoding algorithms. In order to improve the convergence rate, we design new flipping rules with two phases for the SFDP algorithms. In the first phase, two or more symbols are flipped at each iteration to allow a quick increase of the objective function. While in the second phase, only one symbol is flipped to avoid the oscillation of the decoder when the objective function is close to its maximum. Simulation results show that the SFDP algorithms with the proposed flipping rules can reduce the average number of iterations significantly, whereas having similar performances when compared to the original SFDP algorithms.

- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E102-A No.7 pp.930-933

- Publication Date
- 2019/07/01

- Publicized

- Online ISSN
- 1745-1337

- DOI
- 10.1587/transfun.E102.A.930

- Type of Manuscript
- LETTER

- Category
- Coding Theory

Zhanzhan ZHAO

Xidian University

Xiaopeng JIAO

Xidian University

Jianjun MU

Xidian University

Yu-Cheng HE

Huaqiao University

Junjun GUO

Xi'an Technological University

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Zhanzhan ZHAO, Xiaopeng JIAO, Jianjun MU, Yu-Cheng HE, Junjun GUO, "Fast-Converging Flipping Rules for Symbol Flipping Decoding of Non-Binary LDPC Codes" in IEICE TRANSACTIONS on Fundamentals,
vol. E102-A, no. 7, pp. 930-933, July 2019, doi: 10.1587/transfun.E102.A.930.

Abstract: The symbol flipping decoding algorithms based on prediction (SFDP) for non-binary LDPC codes perform well in terms of error performances but converge slowly when compared to other symbol flipping decoding algorithms. In order to improve the convergence rate, we design new flipping rules with two phases for the SFDP algorithms. In the first phase, two or more symbols are flipped at each iteration to allow a quick increase of the objective function. While in the second phase, only one symbol is flipped to avoid the oscillation of the decoder when the objective function is close to its maximum. Simulation results show that the SFDP algorithms with the proposed flipping rules can reduce the average number of iterations significantly, whereas having similar performances when compared to the original SFDP algorithms.

URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E102.A.930/_p

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@ARTICLE{e102-a_7_930,

author={Zhanzhan ZHAO, Xiaopeng JIAO, Jianjun MU, Yu-Cheng HE, Junjun GUO, },

journal={IEICE TRANSACTIONS on Fundamentals},

title={Fast-Converging Flipping Rules for Symbol Flipping Decoding of Non-Binary LDPC Codes},

year={2019},

volume={E102-A},

number={7},

pages={930-933},

abstract={The symbol flipping decoding algorithms based on prediction (SFDP) for non-binary LDPC codes perform well in terms of error performances but converge slowly when compared to other symbol flipping decoding algorithms. In order to improve the convergence rate, we design new flipping rules with two phases for the SFDP algorithms. In the first phase, two or more symbols are flipped at each iteration to allow a quick increase of the objective function. While in the second phase, only one symbol is flipped to avoid the oscillation of the decoder when the objective function is close to its maximum. Simulation results show that the SFDP algorithms with the proposed flipping rules can reduce the average number of iterations significantly, whereas having similar performances when compared to the original SFDP algorithms.},

keywords={},

doi={10.1587/transfun.E102.A.930},

ISSN={1745-1337},

month={July},}

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TY - JOUR

TI - Fast-Converging Flipping Rules for Symbol Flipping Decoding of Non-Binary LDPC Codes

T2 - IEICE TRANSACTIONS on Fundamentals

SP - 930

EP - 933

AU - Zhanzhan ZHAO

AU - Xiaopeng JIAO

AU - Jianjun MU

AU - Yu-Cheng HE

AU - Junjun GUO

PY - 2019

DO - 10.1587/transfun.E102.A.930

JO - IEICE TRANSACTIONS on Fundamentals

SN - 1745-1337

VL - E102-A

IS - 7

JA - IEICE TRANSACTIONS on Fundamentals

Y1 - July 2019

AB - The symbol flipping decoding algorithms based on prediction (SFDP) for non-binary LDPC codes perform well in terms of error performances but converge slowly when compared to other symbol flipping decoding algorithms. In order to improve the convergence rate, we design new flipping rules with two phases for the SFDP algorithms. In the first phase, two or more symbols are flipped at each iteration to allow a quick increase of the objective function. While in the second phase, only one symbol is flipped to avoid the oscillation of the decoder when the objective function is close to its maximum. Simulation results show that the SFDP algorithms with the proposed flipping rules can reduce the average number of iterations significantly, whereas having similar performances when compared to the original SFDP algorithms.

ER -