Residual-Decaying-Based Informed Dynamic Scheduling for Belief-Propagation Decoding of LDPC Codes

Zhang, Huilian; Chen, Shaoping

doi:10.1109/access.2019.2899106

Cited by 15 publications

(16 citation statements)

References 24 publications

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“…The maximum iteration is set to 10 iterations. The NMSA [14] is used for check-node update. Normalization constant α = 0.75.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…A knowledgeaided IDS decoding algorithm [13] exploits the reliability of the messages to refine the exchange of information in the graph. To solve the problem of poor convergence BER performance of RBP decoding based on greediness, a residual message transfer algorithm based on residual attenuation is proposed [14]. It can prevent decoding resources from being unreasonably occupied by a small number of edges in Tanner graph.…”

Section: Introductionmentioning

confidence: 99%

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A Reliability Profile Based Low-Complexity Dynamic Schedule LDPC Decoding

2022

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In order to improve the error correction performance of Low-Density Parity-Check (LDPC) codes, In this paper, we propose a Reliability Profile (RP) Based Low-Complexity Dynamic Schedule, called RPD. In terms of dynamic scheduling, the new RPD method is distinct from the existing residual belief propagation (RBP) and its variations, since RPD is based on residual criterion. Reliability divides nodes message into two categories: reliable and unreliable. By using as many messages as possible from the latest available current iteration instead of the previous iteration to update unreliable messages multiple times to speed up the convergence speed and increase the total number of updates of effective nodes message, so as to improve the Bit Error Rate (BER) performance. By not updating the reliable message, the number of ineffective nodes message updates is reduced, thereby reducing the decoding complexity. Besides, the more iterations increase, the fewer calculations of these reliable nodes. Moreover, based on reliability profile, RPD has an advantage over RBP for dynamic scheduling in that the former only needs integer operations, while the latter requires float operations. Therefore, the RPD algorithm not only accelerates the convergence speed of LDPC decoding and but also improves the BER performance while reducing the complexity.The analysis and simulation results show that the RPD strategy not only retains the fast-convergence advantage of RBP, but also has a better convergence BER performance compared to that of node-wise residual belief propagation (NW RBP). Furthermore, the simulation results show that the RPD can significantly improve the convergence speed of protograph LDPC decoding.

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“…The maximum iteration is set to 10 iterations. The NMSA [14] is used for check-node update. Normalization constant α = 0.75.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Reliability Profile Based Low-Complexity Dynamic Schedule LDPC Decoding

2022

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“…Such greediness will prevent the RBP algorithm from converging to a low error rate. To solve this problem, different algorithms have recently been proposed, such as variable node-based dynamic scheduling [17], dynamic scheduling based on tabu search [18], and residual-decayingbased residual belief propagation [19].…”

Section: Introductionmentioning

confidence: 99%

“…Mobile Information Systems (16) ifD < μ, then (17) reset the processing subset, and put all check nodes into M (l) (18) end if (19) end if (20) ifHv T � 0 is not satisfied, then (21) go back to line 4 (22) else return estimated codeword (23) end if (24) end for (25) return estimated codeword ALGORITHM 2: RSNS-EMS. Mobile Information Systems algorithm has been developed based on this "abnormal" stability of the processing subset.…”

mentioning

confidence: 99%

Node-Subset Scheduling with a Subset-Reset Mechanism for the Decoding Algorithm of Nonbinary LDPC Codes

Luo

et al. 2021

Mobile Information Systems

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For the conventional extended min-sum (EMS) algorithm, all check nodes update their check-to-variable (C2V) messages in every iteration. Selected scheduling, which reduces the number of check nodes for message updating in one iteration, can effectively reduce the complexity of the decoding algorithm, but it also lead to some performance degradation. With the introduction of a metric based on node stability, we propose stability-based node-subset scheduling (SNS) for the EMS algorithm, which can improve the performance of node-subset scheduling (NS). Second, to further improve the decoding performance of SNS while maintaining low complexity, we propose the SNS-EMS algorithm with a subset-reset mechanism (RSNS-EMS) based on the abnormal stability found in the processing node subset, which will cause the estimated codeword to fail to converge. The RSNS-EMS algorithm enhances performance through a sliding window detection and reset mechanism, and it resets the elements in the processing node subset to force all check nodes to update new messages when abnormal stability is detected. The simulation results show that the proposed algorithm can reduce complexity by approximately 25% with negligible performance degradation.

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“…Gradually, the IDS aroused much attention for its excellent performance. Since then an increasing number of dynamic decoding algorithms based on different message selecting and updating strategies were presented [10]- [14], such as the variable-to-check RBP (VC RBP) [10], the silent-variablenode-free RBP (SVNF) [11], the dynamic-silent-variablenode-free scheduling(D-SVNFS) [12], the tabu search-based dynamic scheduling (TSDS) [13], and residual-decayingbased residual belief-propagation (RD RBP) [14]. In the VC RBP algorithm, the V2C message with the maximum V2C message residual is propagated preferentially, and the SVNF RBP algorithm aims at the issue of silent variable nodes, selects and updates each C2V message with the maximum C2V message residual generated by the check node connecting with each variable node in turn.…”

Section: Introductionmentioning

confidence: 99%

Improved Decoding Algorithms of LDPC Codes Based on Reliability Metrics of Variable Nodes

Liu

Yang

et al. 2019

IEEE Access

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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 updatingmessages 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.INDEX TERMS Low-density parity-check (LDPC) codes, dynamic selection strategies, dynamic updating strategies, residuals of variable nodes.

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Residual-Decaying-Based Informed Dynamic Scheduling for Belief-Propagation Decoding of LDPC Codes

Cited by 15 publications

References 24 publications

A Reliability Profile Based Low-Complexity Dynamic Schedule LDPC Decoding

A Reliability Profile Based Low-Complexity Dynamic Schedule LDPC Decoding

Node-Subset Scheduling with a Subset-Reset Mechanism for the Decoding Algorithm of Nonbinary LDPC Codes

Improved Decoding Algorithms of LDPC Codes Based on Reliability Metrics of Variable Nodes

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