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Chinese Control and Decision Conference (CCDC)

Research on LDPC code decoding algorithm based on scheduling strategy

Feng Xiao

Published May 1, 2016• 0 citations
Publisher

Abstract

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.

DOI
10.1109/ccdc.2016.7531650

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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.
Among the belief-propagation (BP) decoding algorithms of low-density parity-check (LDPC) codes, the algorithms based on dynamic scheduling strategy show excellent performance. In this letter, we propose a variable-node-based dynamic scheduling decoding algorithm. For the proposed algorithm, the reliability of variable nodes is evaluated based on the log-likelihood ratio (LLR) values and the parity-check equations; then, a more accurate dynamic selection strategy is presented. Simultaneously, the oscillating variable nodes are processed so that the influence of the spread of error messages caused by oscillation are suppressed. In addition, the proposed algorithm updates the same number of messages in one iteration as the original BP decoding algorithm does, which is different from some other dynamic decoding algorithms. Simulation results demonstrate that the proposed algorithm outperforms other algorithms.
Recently low-density parity check (LDPC) codes have been applied in more areas, and the research of non-binary LDPC codes has become more significant. In this paper, we establish a dynamic scheduling strategy to reduce complexity of non-binary LDPC codes decoding, and choose extended min-sum algorithm as the model. The dynamic scheduling strategy is based on the idea of nodes reliability. When decoding, we select a part of check nodes to update messages in real time according to the reliability rules, and only the variable nodes getting new messages can participate in the message propagation. Compared with usual standard flooding scheduling, this dynamic scheduling strategy can reduce decoding complexity effectively. We also optimize the message of variable nodes according to reliability, which ensure that the error correction performance of decoding algorithm is not affected. Our simulations over a BPSK-AWGN channel show that this dynamic scheduling strategy can reduce complexity in non-binary LDPC codes belief propagation decoding without affecting error correction performance.
Scheduling strategy is considered an important aspect of belief-propagation (BP) decoding of low-density parity-check (LDPC) codes because it affects the decoder's convergence rate, decoding complexity and error-correction performance. In this paper, we propose two new scheduling strategies for the BP decoding of non-binary LDPC (NB-LDPC) codes. Both the strategies are devised based on the concept of check node reliability and employ a heuristically defined threshold which can adapt to the communication channel variations. As the scheduling strategies only update a subset of the check nodes in each iteration, they result in reduced iteration cost. Furthermore, since the BP performs suboptimally for finite-length LDPC codes, especially for short-length LDPC codes, by enhancing the message propagation over the Tanner Graphs of short-length NB-LDPC codes, the new scheduling strategies can even improve the error-correction performances of BP decoding. Simulation results demonstrate that the new scheduling strategies provide good performance/complexity tradeoffs.
The informed dynamic scheduling (IDS) strategies for decoding of low-density parity-check codes obtained superior performance in error correction performance and convergence speed. However, there are still two problems existing in the current IDS algorithms. The first is that the current IDS algorithms only preferentially update the selected unreliable messages, but they do not guarantee the updating is performed with reliable information. In this paper, a two-step message selecting strategy is introduced. On the basis of the two reliability metrics and two types of variable node residuals, the residual belief propagation (BP) decoding algorithm, short for TRM-TVRBP, is proposed. With the algorithm, the reliability of the updating-messages can be improved. The second is the greediness problem, prevalently existed in the IDS-like algorithms. The problem arises mainly from the fact that the major computing resources are allocated to or concentrated on some nodes and edges. To overcome the problem, the reliability metric-based RBP algorithm (RM-RBP) is proposed, which can force every variable node to contribute its intrinsic information to the iterative decoding. At the same time, the algorithm can force the related variable nodes to be updated, and make every edge have an equal opportunity of being updated. The simulation results show that both the TRM-TVRBP and the RM-RBP have appealing convergence rate and error-correcting performance compared with the previous IDS decoders over the white Gaussian noise (AWGN) channel.
Schedule plays an important role in layered belief propagation (BP) decoding of low-density parity-check (LDPC) codes. It affects the error-rate performance as well as convergence rate of the decoder. In this paper, an efficient scheduling scheme is proposed to arrange the updating order of check nodes for layered BP decoder of regular LDPC codes. This scheme selects check node one at a time based on the reliability of the variable nodes. Specifically each time the check node with maximum number of low-reliability neighbors is selected. For simplicity, we introduce the updating state instead of the real-time messages to represent variable-node reliability. Simulation results on regular LDPC codes prove that the proposed scheduling scheme can obtain efficient schedules with fast convergence and good error-rate performance.