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IEEE Communications Letters

Parallel Weighted Bit-Flipping Decoding

Xiaofu Wu, Chunming Zhao, Xiaohu You

Published Aug 1, 2007• 53 citations
Publisher

Abstract

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.

DOI
10.1109/lcomm.2007.070269

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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.
A novel self-normalized weighted bit-flipping (SNWBF) decoding algorithm for low-density parity-check (LDPC) codes is proposed. Compared to the best known weighted bit-flipping decoding, the SNWBF algorithm converges significantly faster but with little performance penalty. For decoding of LDPC codes, the proposed SNWBF algorithm considers not only the reliability of the neighboring check nodes, but also the reliability of each variable node. Compared to the IMWBF algorithm, the proposed algorithm does not require multiplicative normalization and performs even better.
In this paper a fast version of the parallel weighted bit flipping LDPC decoding algorithm (PWBF) is presented. The idea, which allowed decreasing the computational complexity of the PWBF method, is based on the observation that in dependency on signal to noise ratio, many of the received bits in the codeword of LDPC code could be without error. The augmented algorithm makes tests based on syndromes and symbol involvement in parity checks, which are given by the factor graph corresponding to the chosen LDPC code in order to define so called guaranteed bits. These guaranteed bits do not participate in the decoding calculations further. Simulation results are presented, which show that there is not visible any significant performance deterioration by application of this method and that the approximate speed up of the decoding for the tested codes is about 25% on the selected hardware in comparison with the known PWBF.
An improved parallel weighted bit-flipping (PWBF) algorithm is presented. To accelerate the information exchanges between check nodes and variable nodes the bit-flipping step and the check node updating step of the original algorithm are parallelized. The simulation experiments demonstrate that the improved PWBF algorithm provides about 0.1 to 0.3 dB coding gain over the original PWBF algorithm. And the improved algorithm achieves a higher convergence rate. The choice of the threshold is also discussed, which is used to determine whether a bit should be flipped during each iteration. The appropriate threshold can ensure that most error bits be flipped, and keep the right ones untouched at the same time. The improvement is particularly effective for decoding quasi-cyclic low-density parity-check (QC-LDPC) codes.
To seek a decoding scheme with good performance, low complexity and fast convergence, we present an improved parallel weighted bit flipping (IPWBF) algorithm for finite geometry low-density parity-check codes whose parity check matrix is of heavy row and column weights. In the IPWBF, a bit flipping (BF) function and two parallel BF criteria, all of which scatter in the literature, are exploited jointly to serve our purpose. Meanwhile, differential evolution is used to optimize the involved parameters. Simulation results show that the proposed algorithm achieves an observable performance gain over its counterparts without any complexity penalty. Furthermore, with respect to other known low complexity decodings such as normalized BP-based, the IPWBF yields a new performance versus complexity tradeoff, that is, higher throughput at the expense of moderate performance loss.
In this paper, a weighted multiple bit flipping (WMBF) algorithman for decoding low-density parity-check (LDPC) codes is proposed first. Then the improved WMBF algorithm which we call the efficient weighted bit-flipping (EWBF) algorithm is developed. The EWBF algorithm can dynamically choose either multiple bit-flipping or single bit-flipping in each iteration according to the log-likelihood ratio of the error probability of the received bits. Thus, it can efficiently increase the convergence speed of decoding and prevent the decoding process from falling into loop traps. Compared with the parallel weighted bit-flipping (PWBF) algorithm, the EWBF algorithm can achieve significantly lower computational complexity without performance degradation when the Euclidean geometry (EG)-LDPC codes are decoded. Furthermore, the flipping criterion does not require any parameter adjustment.
Aiming at seeking a low-complexity decoder with fast decoding convergence speed for short or medium low-density parity-check (LDPC) codes, an improved parallel weighted bit-flipping (IPWBF) algorithm, which is applied flexibly for two classes of codes is presented here. For LDPC codes with low column weight in their parity check matrix, both bootstrapping and loop detection procedures, described in the existing literature, are included in IPWBF. Furthermore, a novel delay-handling procedure is introduced to prevent the codeword bits of high reliability from being flipped too hastily. For large column weight finite geometry LDPC codes, only the delay-handling procedure is included in IPWBF to show its effectiveness. Extensive simulation results demonstrate that the proposed algorithm achieves a good tradeoff between performance and complexity.