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International Conference on Wireless Communications and Signal Processing (WCSP)

Grouping dynamic scheduling for LDPC codes in symmetric alpha-stable impulsive noise

Bin Dai, Rongke Liu, Zhen Mei, Yi Hou, Ling Zhao

Published Oct 1, 2016• 0 citations
Publisher

Abstract

In some practical applications, impulsive noise can severely degrade the performance of a communication system. As a class of powerful error correction codes, Low-density parity-check (LDPC) codes ha,ve been shown superior performance on AWGN channels. In addition, belief propagation (BP) decoding algorithm of LDPC codes based on scheduling strategy has better performance and faster convergence rate than conventional BP decoding algorithm. In this paper, a dynamic scheduling of LDPC codes is first used on impulsive noise channels. Moreover, we propose a new scheduling strategy which named grouping dynamic scheduling (GDS) for impulsive noise channels to further improve the performance. Simulation results show that the dynamic scheduling on impulsive noise channels provides more performance gain than AWGN channels and the gain becomes significant when the channel is more impulsive. In addition, compared with conventional dynamic scheduling strategy, our proposed algorithm not only provides better performance, but also lowers the actual decoding computational complexity.

DOI
10.1109/wcsp.2016.7752594

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In some practical applications, impulsive noise can severely degrade the performance of a communication system. As a class of powerful error correction codes, Low-density parity-check (LDPC) codes ha,ve been shown superior performance on AWGN channels. In addition, belief propagation (BP) decoding algorithm of LDPC codes based on scheduling strategy has better performance and faster convergence rate than conventional BP decoding algorithm. In this paper, a dynamic scheduling of LDPC codes is first used on impulsive noise channels. Moreover, we propose a new scheduling strategy which named grouping dynamic scheduling (GDS) for impulsive noise channels to further improve the performance. Simulation results show that the dynamic scheduling on impulsive noise channels provides more performance gain than AWGN channels and the gain becomes significant when the channel is more impulsive. In addition, compared with conventional dynamic scheduling strategy, our proposed algorithm not only provides better performance, but also lowers the actual decoding computational complexity.
Modern navigation satellite communication has the characteristic of high transmitting rate. To avoid bit errors in data transmission, low density parity check (LDPC) codes are widely recognized as efficient ways for navigation communication. Conventionally, the LDPC decoding is applied for additive white Gaussian noise (AWGN) channel and degrades severely while facing the impulsive noise. However, navigation communication often suffers from impulsive interference due to the occurrence of high amplitude "spikes". At this time, the conventional Gaussian noise assumption is inadequate. The impulsive component of interference has been found to be significant which influences the reliability of transmitted information. Therefore the LDPC decoding algorithms for AWGN channel are not suitable for impulsive noise environments. Consider that LDPC codes over GF(q) perform better than binary LDPC in resisting burst errors for current navigation system, it is necessary to conduct research on LDPC codes over GF(q). In this paper, an optimized initialization by calculating posterior probabilities of received symbols is proposed for non-binary LDPC decoding on additive white Class A noise (AWAN) channel. To verify the performance of the proposed initialization, extensive experiments are performed in terms of convergence, validity, and robustness. Preliminary results demonstrate that the decoding algorithm with the optimized initialization for non-binary LDPC codes performs better than the competing methods and that of binary LDPC codes on AWAN channel.
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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.
In this letter, a novel scheduling scheme for decoding irregular low-density parity-check (LDPC) code, based on the column weight of variable nodes in the code graph, is introduced. In this scheme, the irregular LDPC code is decoded using the shuffled belief-propagation (BP) algorithm by selecting the variable nodes in descending order of their column weight. Via numerical simulation, it is shown that the proposed high-to-low column-weight based decoding schedule can noticeably increase the convergence speed at medium to high signal-to-noise ratio (SNR) over AWGN and Rayleigh fading channels without introducing additional complexity or error rate degradation. Furthermore, it is found that the improvement in decoding convergence is proportional to the maximum column-weight in the code graph.
Low-Density Parity-Check (LDPC) codes have been widely used in modern communication standards due to their strong error correction capabilities. This paper presents an experimental evaluation of a (1200, 600) irregular LDPC code over an additive white Gaussian noise (AWGN) channel, systematically comparing three decoding algorithms (Sum-Product, Normalized Min-Sum, and Offset Min-Sum) with three scheduling methods (Flooding, Layered Belief Propagation, and Residual Belief Propagation). Parameter sweeps are performed to determine the optimal normalization factor (α\alphaα) for the Normalized Min-Sum and the offset factor (β\betaβ) for the Offset Min-Sum. A comparative analysis is then performed on the frame error rate (FER) and convergence behavior of each algorithm and scheduling configuration, considering the maximum number of iterations set at 10 and 25. The results show that the Offset Min-Sum algorithm withβ=0.5\beta=0.5β=0.5and Layered Belief Propagation scheduling provides an acceptable trade-off between complexity and error-correction performance, closely matching the Sum-Product algorithm but at a lower computational cost. Although Residual Belief Propagation converges quickly at lower signal-to-noise ratios, it exhibits a high error floor. These findings provide practical guidelines for selecting optimal decoding configurations in resource-constrained applications.
Low-density parity-check (LDPC) codes have proved to be very powerful channel coding schemes with a broad range of applications. However, as maximum-likelihood decoding is utterly complex, suboptimal decoders have to be employed. One of the most popular decoding algorithms of LDPC codes is belief propagation (BP) decoding. In this paper, we present a novel scheduling for belief propagation decoding of LDPC codes. The new approach combines probabilistic scheduling with the known shuffled and check-shuffled serial scheduling algorithms. The resulting probabilistic shuffled and probabilistic check-shuffled decoders show a superior performance in terms of residual bit error rate. The drawback is that the convergence speed is slightly decreased. However, the convergence is still faster than for the standard and probabilistic flooding algorithms. Furthermore, we have adapted the probabilistic flooding schedule and the proposed probabilistic shuffled schedule to the non-binary case. We show that the aforementioned effects on the binary decoder can similarly be observed when applying the different schedules to the decoding of LDPC codes over higher order Galois fields.