Shuffled Belief Propagation Research Articles

GF(q) LDPC encoder and decoder FPGA implementation using group shuffled belief propagation algorithm

This paper presents field programmable gate array (FPGA) exercises of the GF(q) low-density parity-check (LDPC) encoder and interpreter utilizing the group shuffled belief propagation (GSBP) algorithm are presented in this study. For small blocks, non-dual LDPC codes have been shown to have a greater error correction rate than dual codes. The reduction behavior of non-binary LDPC codes over GF (16) (also known as GF(q)-LDPC codes) over the additive white Gaussian noise (AWGN) channel has been demonstrated to be close to the Shannon limit and employs a short block length (N=600 bits). At the same time, it also provides a non-binary LDPC (NB-LDPC) code set program. Furthermore, the simplified bubble check treasure event count is implemented through the use of first in first out (FIFO), which is based on an elegant design. The structure of the interpreter and the creation of the residential area he built were planned in very high speed integrated circuit (VHSIC) hardware description language (VHDL) and simulated in MODELSIM 6.5. The combined output of the Cyclone II FPGA is combined with the simulation output.

A weighted group shuffled decoding for low-density parity-check codes

In this paper, we have developed several concepts such as the tree concept, the short cycle concept and the group shuffling concept of a propagation cycle to decrypt low-density parity-check (LDPC) codes. Thus, we proposed an algorithm based on group shuffling propagation where the probability of occurrence takes exponential form exponential factor appearance probability belief propagation-group shuffled belief propagation (EFAP-GSBP). This algorithm is used for wireless communication applications by providing improved decryption performance with low latency. To demonstrate the effectiveness of our suggested technique EFAP-GSBP, we ran numerous simulations that demonstrated that our algorithm is superior to the traditional BP/GSBP algorithm for decrypting LPDC codes in both regular and non-regular forms

Corrections to “A Grouping Based on Local Girths for the Group Shuffled Belief Propagation Decoding”

In the above letter <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , the name of the author Ryuichi Tatsukawa was incorrectly provided as Ryuichi Tatasukawa. The author’s name should appear as Ryuichi Tatsukawa.

Reliability Ratio-Based Serial Algorithm of LDPC Decoder for Turbo Equalization Schemes

Serial decoding algorithms of low-density parity-check (LDPC) code converge efficiently with low errors. Previously, a serial decoding algorithm, named a shuffled belief-propagation (SBP), was applied in turbo equalization of bit-patterned magnetic recording (BPMR) systems. With the SBP algorithm, an LDPC decoder converged twice as fast as one using conventional BP algorithms. We further improved the convergence speed of SBP by updating the messages in an adaptive order, which played a flexible role throughout decoding. We proposed two adaptive-serial algorithms for LDPC codes in turbo equalization. One updated the messages using the extrinsic loglikelihood ratio (LLR) and the result of the parity-check equation checking. The second contained an additional rule that tracked the LLR sign changes in each iteration. Both algorithms converged faster and with lower bit error rates (BERs) than the SBP and previous adaptive-serial algorithms in a BPMR system with media noise.

Design and Optimization of Tail-Biting Spatially Coupled Protograph LDPC Codes Under Shuffled Belief-Propagation Decoding

In this letter, we conduct a comprehensive investigation on tail-biting (TB) spatially coupled protograph (SC-P) low-density parity-check (LDPC) codes under shuffled belief-propagation (BP) decoding. We first propose a shuffled extrinsic information transfer (S-EXIT) algorithm tailored for the shuffled decoding. Exploiting the proposed algorithm, we accurately predict the convergence performance (i.e., decoding thresholds) for TB-SC-P codes under such a schedule and demonstrate that their convergence performance can be further improved. Based on the S-EXIT analysis, we develop an optimization method to generate a new type of TB-SC-P codes, called improved TB-SC double-protograph (I-TB-SC-DP) codes, which can inherit the superiorities of two mother protograph codes and possess more desirable decoding thresholds. Theoretical analyses and simulated results illustrate that the proposed I-TB-SC-DP codes exhibit better error performance than the existing counterparts.

A Grouping Based on Local Girths for the Group Shuffled Belief Propagation Decoding

Low-density parity-check codes have been known to exhibit good error correcting performance by using with the belief propagation (BP) decoding. The group shuffled BP decoding, which is a modification of the BP decoding, can exhibit a better performance than BP decoding by suitably grouping variable nodes in a Tanner graph. In this letter, we propose a new grouping of variable nodes based on local girths and evaluate its performance.

Informed shuffled belief‐propagation decoding for low‐density parity‐check codes

Shuffled belief propagation (SBP), as a sequential belief propagation (BP) algorithm, speeds up the convergence of BP decoding, and maintains the least complexity of flooding BP. However, its performance is remarkably inferior to informed dynamic scheduling (IDS) BP algorithms. The authors design an informed dynamic location method, based on the residuals of variable node log-likelihood ratio values, to reorder variable nodes of SBP to be updated. The location method significantly accelerates the convergence of SBP algorithm from two aspects: the unstable variable node with the largest residual to be updated first, and selecting the largest residual locally. Simulation results show that the proposed algorithm performs nearly the same as the best performance of IDS BP algorithms, and behaves prominently at high signal-to-noise ratios.

A Group Shuffled BP decoding for punctured Low-Density Parity-Check codes

A group shuffled belief propagation (GSBP) decoding for punctured low-density parity-check (LDPC) codes is proposed in the paper. The proposed GSBP decoding schedules the updating order of each bit node according to its recovery order in the standard BP decoding. This enables the proposed decoding to recover all punctured nodes in the first iteration with the minimum required number of groups. Calculation of the number of effective updates, which indicates the number of nonzero check-to-bit messages, shows that the proposed decoding can achieve faster decoding convergence than the layered BP (LBP) decoding for rate-compatible punctured LDPC (RCP-LDPC) codes. In the simulation results, the maximum SNR gain of the proposed decoding over the LBP decoding is about 0.9dB at the FER of 10-4.

A Method for Grouping Symbol Nodes of Group Shuffled BP Decoding Algorithm

In this paper, we propose a method for enhancing performance of a sequential version of the belief-propagation (BP) decoding algorithm, the group shuffled BP decoding algorithm for low-density parity-check (LDPC) codes. An improved BP decoding algorithm, called the shuffled BP decoding algorithm, decodes each symbol node in serial at each iteration. To reduce the decoding delay of the shuffled BP decoding algorithm, the group shuffled BP decoding algorithm divides all symbol nodes into several groups. In contrast to the original group shuffled BP, which automatically generates groups according to symbol positions, in this paper we propose a method for grouping symbol nodes which generates groups according to the structure of a Tanner graph of the codes. The proposed method can accelerate the convergence of the group shuffled BP algorithm and obtain a lower error rate in a small number of iterations. We show by simulation results that the decoding performance of the proposed method is improved compared with those of the shuffled BP decoding algorithm and the group shuffled BP decoding algorithm.