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Chinese Journal of Radio Science

Shuffled belief propagation decoding based on variable nodes reliability

Wang Haiqua

Published Jan 1, 2015• 0 citations
OpenAlex

Abstract

This paper proposes a new group shuffled belief propagation(BP)decoding of low-density parity-check(LDPC)codes,which divides check nodes or variable nodes into groups based on the reliability of the initial channel message.The bit error rate and the average number of iterations are analyzed with additive white Gaussian noise(AWGN)channel.Simulations verify that the proposed decoding strategy greatly improves the decoding performance.

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This paper proposes a new group shuffled belief propagation(BP)decoding of low-density parity-check(LDPC)codes,which divides check nodes or variable nodes into groups based on the reliability of the initial channel message.The bit error rate and the average number of iterations are analyzed with additive white Gaussian noise(AWGN)channel.Simulations verify that the proposed decoding strategy greatly improves the decoding performance.
Shuffled decoding is known to provide efficient and high-throughput implementation of LDPC decoders. In this paper, a new grouping technique of variable nodes to accelerate the message-passing rate is presented. In this algorithm, unlike other group-shuffled decoding methods, we consider for the first sub-group a set of variable nodes that has a low value of the intrinsic information, where the variable nodes of the code graph are divided into sub-groups called layers to perform group-by-group message-passing decoding and each iteration is broken into multiple sub-iterations. This paper proposes a simplification of the Variable Node group-shuffled Belief Propagation (Optimized VN group-shuffled BP) to lower the complexity of the check node update rule. Simulation results, verify that the Optimized VN group-shuffled BP does yield a faster convergence rate than both Belief Propagation (BP) and Check Node group-shuffled Belief Propagation (CN group-shuffled BP) decoder.
To reduce the implementation complexity of a belief propagation (BP) based low-density parity-check (LDPC) decoder, shuffled BP decoding schedules, which serialize the decoding process by dividing a complete parallel message-passing iteration into a sequence of sub-iterations, have been proposed. The so-called group horizontal shuffled BP algorithm partitions the check nodes of the code graph into groups to perform group-by-group message-passing decoding. This paper proposes a new grouping technique to accelerate the message-passing rate. Performance of the proposed algorithm is analyzed by a Gaussian approximation approach. Both analysis and numerical experiments verify that the new algorithm does yield a convergence rate faster than that of existing conventional or group shuffled BP decoder with the same computing complexity constraint.
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.
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.
With the rapid development of the channel coding technology, low density parity check(LDPC) code has been widely concerned by researchers all of the world as an approaching code to Shannon limit. Error floor is an important issue in the theory of LDPC codes and the research of iterative decoding algorithms. Based on the decoding of LDPC codes, a new improved decoding algorithm, Group Belief Propagation (GBP) based on variable nodes is proposed for the different scheduling strategies of the LDPC codes. According to the difference between the messages and the hard decision values, the variable nodes are divided into reliable nodes and unreliable nodes. And the unreliable nodes are priority to update. Further, the effect of threshold for judging the group on GBP strategy is analyzed. Simulation results show that the proposed algorithm can achieve better convergence and decoding performances compared to three classical scheduling algorithms. Meanwhile, it can overcome the error floor phenomenon caused by the trapping set effectively.
The Layered Belief Propagation L-BP algorithm is is a modified Belief Propagation BP algorithm, where the check nodes are divided in subgroups called layers and each iteration is broken into multiple sub-iterations. In this paper, we consider layered belief propagation decoding and propose an efficient variable node layering for decoding LDPC codes that performs well. We compare the performance of the first introduced LDPC decoding algorithm BP and Layered BP using check node layering with Layered BP using variable node layering in terms of bit error rate (BER). We show that the convergence for decoding LDPC codes is increasing by using a simple and efficient layering strategy.