Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Transactions on Communications

New insights into weighted bit-flipping decoding

Xiaofu Wu, Cong Ling, Ming Jiang, Enyang Xu, Chunming Zhao, Xiaohu You

Published Aug 1, 2009• 29 citations
Publisher

Abstract

A natural relationship between weighted bit-flipping (WBF) decoding and belief-propagation-like (BP-like) decoding is explored. This understanding can help us develop WBF algorithms from BP-like algorithms. For min-sum decoding, one can find that its WBF algorithm is the algorithm proposed by Jiang et al. For BP decoding, we propose a new WBF algorithm and show its performance advantage. The proposed WBF algorithms are parallelized to achieve rapid convergence. Two efficient simulation-based procedures are proposed for the optimization of the associated thresholds.

DOI
10.1109/tcomm.2009.08.070257

Related papers

Towards Understanding Weighted Bit-Flipping Decoding

Xiaofu Wu, Cong Ling, Ming Jiang +3 more

A natural relationship between weighted bit-flipping (WBF) decoding and message-passing decoding is explored. This understanding can help us develop a dual WBF decoding algorithm from one type of message-passing decoding algorithm and vice versa. For min-sum decoding, one can find that its dual WBF algorithm is the algorithm proposed by Jiang et al. For belief-propagation (BP) decoding, we propose a new WBF algorithm and show its performance advantage. For some high-rate low-density parity-check (LDPC) codes of large row weight, it is shown that the WBF algorithm proposed by Liu and Pados performs extraordinarily well. However, its dual message- passing decoding does not work well. Furthermore, we propose a parallel implementation framework for various WBF algorithms. Compared to serial implementations, various WBF algorithms in their parallel form converge significantly faster and often perform better.

IEEE International Symposium on Information Theory (ISIT)•Jun 1, 2007•6 citations

Theoretic approach to BP-based WBF decoding algorithm of LDPC codes

Erl‐Huei Lu, Tso-Cho Chen, Pen‐Yao Lu

A theoretic approach to the belief-propagation - based weighted bit-flipping (BP-based WBF) algorithm is proposed for decoding low-density parity-check codes. The decoding algorithm can be easily simplified to IMWBF, MWBF, WBF or BF decoding algorithms by setting different parameters; hence it could offer a high flexible performance/complexity trade-off for hybrid decoding.

International Symposium on Wireless Pervasive Computing•Nov 1, 2013•8 citations

Weighted bit-flipping decoding for product LDPC codes

Sirawit Khittiwitchayakul, Watid Phakphisut, Pornchai Supnithi

In this work, we propose a weighted bit-flipping (WBF) decoding for product LDPC codes of which decoding complexity is lower than the belief-propagation (BP) decoding. Two distinct types based on page computations and row/column computations are proposed. In addition, we address an issue of hard decision algorithm for product LDPC codes suffering a performance degradation at high iteration numbers. We introduce a threshold of flipped bits to adjust the performance at high iterations. Although the performances of both proposed decoding are worse than that of the BP algorithm, it greatly reduces the decoding complexity.

International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)•Jun 1, 2016•3 citations

Fast Weighted Bit-Flipping Decoding of Finite-Geometry LDPC Codes

Xiaofu Wu, Ming Jiang, Chunming Zhao +1 more

In this letter, we establish a natural relationship between the improved modified-weighted-bit-flipping (IMWBF) decoding and min-sum decoding. This insight helps us to develop a fast weighted bit-flipping (FWBF) decoding algorithm. For decoding of finite-geometry low-density parity-check codes, we demonstrate through examples that the FWBF decoding can provide a further improvement to the IMWBF decoding on both convergence and performance

IEEE Information Theory Workshop (ITW)•Oct 1, 2006•7 citations

An Enhanced Belief Propagation Decoding Algorithm With Bit-Flipping for Polar Codes

Zhongjun Yang, Li Chen

For polar codes, bit-flipping strategy can significantly improve the error-correction performance of the belief propagation (BP) decoding. However, the existing BP flipping (BPF) decoding algorithms require many attempts, due to their inefficiency in locating the erroneous positions. This leads to high decoding complexity, limiting their practical applications, especially for long polar codes. In this letter, an enhanced BPF (EBPF) decoding algorithm is proposed. It requires fewer flipping attempts, but yields an advanced decoding performance. By better utilizing the reliability and divergence of bit estimations, a novel weighted metric (WM) is introduced to identify the possible erroneous positions. During each new decoding attempt, the EBPF decoding takes turns to flip these positions. Our simulation results show that, with the same number of flipping attempts, the proposed decoding outperforms the generalized BPF (GBPF) decoding and the state-of-the-art BP correction (BPC) decoding.

IEEE Communications Letters•Dec 16, 2024•6 citations

Parallel Weighted Bit-Flipping Decoding

Xiaofu Wu, Chunming Zhao, Xiaohu You

A parallel weighted bit-flipping (PWBF) decoding algorithm for low-density parity-check (LDPC) codes is proposed. Compared to the best known serial weighted bit-flipping decoding, the PWBF decoding converges significantly faster but with little performance penalty. For decoding of finite-geometry LDPC codes, we demonstrate through examples that the proposed PWBF decoding converges in about 5 iterations with performance very close to that of the standard belief-propagation decoding.

IEEE Communications Letters•Aug 1, 2007•53 citations
A natural relationship between weighted bit-flipping (WBF) decoding and belief-propagation-like (BP-like) decoding is explored. This understanding can help us develop WBF algorithms from BP-like algorithms. For min-sum decoding, one can find that its WBF algorithm is the algorithm proposed by Jiang et al. For BP decoding, we propose a new WBF algorithm and show its performance advantage. The proposed WBF algorithms are parallelized to achieve rapid convergence. Two efficient simulation-based procedures are proposed for the optimization of the associated thresholds.
A natural relationship between weighted bit-flipping (WBF) decoding and message-passing decoding is explored. This understanding can help us develop a dual WBF decoding algorithm from one type of message-passing decoding algorithm and vice versa. For min-sum decoding, one can find that its dual WBF algorithm is the algorithm proposed by Jiang et al. For belief-propagation (BP) decoding, we propose a new WBF algorithm and show its performance advantage. For some high-rate low-density parity-check (LDPC) codes of large row weight, it is shown that the WBF algorithm proposed by Liu and Pados performs extraordinarily well. However, its dual message- passing decoding does not work well. Furthermore, we propose a parallel implementation framework for various WBF algorithms. Compared to serial implementations, various WBF algorithms in their parallel form converge significantly faster and often perform better.
In this work, we propose a weighted bit-flipping (WBF) decoding for product LDPC codes of which decoding complexity is lower than the belief-propagation (BP) decoding. Two distinct types based on page computations and row/column computations are proposed. In addition, we address an issue of hard decision algorithm for product LDPC codes suffering a performance degradation at high iteration numbers. We introduce a threshold of flipped bits to adjust the performance at high iterations. Although the performances of both proposed decoding are worse than that of the BP algorithm, it greatly reduces the decoding complexity.
For polar codes, bit-flipping strategy can significantly improve the error-correction performance of the belief propagation (BP) decoding. However, the existing BP flipping (BPF) decoding algorithms require many attempts, due to their inefficiency in locating the erroneous positions. This leads to high decoding complexity, limiting their practical applications, especially for long polar codes. In this letter, an enhanced BPF (EBPF) decoding algorithm is proposed. It requires fewer flipping attempts, but yields an advanced decoding performance. By better utilizing the reliability and divergence of bit estimations, a novel weighted metric (WM) is introduced to identify the possible erroneous positions. During each new decoding attempt, the EBPF decoding takes turns to flip these positions. Our simulation results show that, with the same number of flipping attempts, the proposed decoding outperforms the generalized BPF (GBPF) decoding and the state-of-the-art BP correction (BPC) decoding.