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IEEE International Conference on Communication Technology (ICCT)

Improved Informed Dynamic Scheduling Strategies for 5G LDPC Codes

Kunyang Li, Huai-Yi Li, Li Juan DENG, Xiaohan Sun, Yueh Wang, Zhiping Shi

Published Oct 20, 2023• 1 citation
Publisher

Abstract

In this paper, we propose two new scheduling algorithms to address the issues of existing informed dynamic scheduling (IDS) decoding algorithms of short low-density parity-check (LDPC) codes for the fifth-generation (5G) new radio (NR). The first issue is the complexity problem, where the high complexity of IDS makes hardware implementation difficult. By considering the impact of puncturing for the first two columns of base matrices, the proposed least-punctured and sum-residual-based (LPSRB) algorithm can reduce decoding complexity. The second issue is the significant degradation of decoding performance when the code length is short. By fully utilizing residuals, the proposed novel residual belief propagation (NRBP) algorithm allocates a significant amount of decoding resources to the less convergent edges. Simulation results demonstrate that NRBP achieves better frame error rate (FER) performance for short LDPC codes.

DOI
10.1109/icct59356.2023.10419771

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In this paper, we propose two new scheduling algorithms to address the issues of existing informed dynamic scheduling (IDS) decoding algorithms of short low-density parity-check (LDPC) codes for the fifth-generation (5G) new radio (NR). The first issue is the complexity problem, where the high complexity of IDS makes hardware implementation difficult. By considering the impact of puncturing for the first two columns of base matrices, the proposed least-punctured and sum-residual-based (LPSRB) algorithm can reduce decoding complexity. The second issue is the significant degradation of decoding performance when the code length is short. By fully utilizing residuals, the proposed novel residual belief propagation (NRBP) algorithm allocates a significant amount of decoding resources to the less convergent edges. Simulation results demonstrate that NRBP achieves better frame error rate (FER) performance for short LDPC codes.
Low-density parity-check (LDPC) codes have been chosen for the fifth-generation (5G) new radio (NR) enhanced Mobile Broad Band (eMBB) data channel. Since NR LDPC codes puncture the first two block columns of the parity-check matrix, the decoding complexity is reduced, but it slows down the convergence rate. In this letter, we propose a fixed schedule that decodes the layers with the least-punctured edges and those with the highest-degree (LPHD), which has much faster convergence speed than conventional schemes. The fixed scheduling schemes cannot take full advantage of the dynamic changes of decoding messages. As a result, the residual-based layered belief propagation (RB-LBP) is proposed to rearrange the layers dynamically among different iterations. Compared with some informed dynamic scheduling (IDS) strategies, RB-LBP reduces the decoding complexity with slight performance loss.
We present an enhanced informed dynamic scheduling (IDS) strategy to avoid propagations of unreliable messages in the residual belief-propagation (RBP) algorithm for decoding low-density parity-check (LDPC) codes. To reduce the resource needed for updating the degree-one variable nodes (VNs) in an RBP-based algorithm for decoding 5G New Radio (NR) LDPC codes, we further introduce a process consisting of several simple procedures for managing the resource consumption. Simulation results demonstrate that our RBP algorithm based on the proposed IDS strategy outperforms existing RBP-based algorithms at the early decoding iterations. By using our degree-one VN resource managing approach, the performance of both the proposed and the existing decoders is significantly improved in decoding the 5G NR codes.
Quasi-cyclic low-density parity-check codes (QC-LDPC) are selected as the channel coding scheme for the data channel of the new radio (NR) enhanced mobile broadband (eMBB) in fifth-generation (5G) mobile communication technology. Traditional layered scheduling strategies used in 5G LDPC codes improve decoding convergence speed, but fixed scheduling schemes cannot fully utilize dynamic changes in decoded messages. To address this issue, this paper proposes a layered scheduling scheme for 5G LDPC codes based on edge information. By prioritizing updates to layers with minimal changes in edge information, this method reduces decoding complexity and accelerates convergence with minimal performance loss. Simulation results demonstrate that this approach enhances decoding performance by approximately 0.05dB compared to other improved hierarchical scheduling strategies.
Low‐density parity‐check (LDPC) codes have excellent performance for a wide range of applications at reasonable complexity. LDPC codes with short blocks avoid the high latency of codes with large block lengths, making them potential candidates for ultra reliable low‐latency applications of future wireless standards. In this work, a novel informed dynamic scheduling (IDS) strategy for decoding LDPC codes, denoted reliability‐based residual belief propagation (Rel‐RBP), is developed by exploiting the reliability of the message and the residuals of the possible updates to choose the messages to be used by the decoding algorithm. A different measure for each iteration of the IDS schemes is also presented, which underlies the high cost of those algorithms in terms of computational complexity and motivates the development of the proposed strategy. Simulations show that Rel‐RBP speeds up the decoding at reduced complexity and results in error rate performance gains over prior work.
When residual belief-propagation (RBP), which is a kind of informed dynamic scheduling (IDS), is applied to low-density parity-check (LDPC) codes, the convergence speed in error-rate performance can be significantly improved. However, the RBP decoders presented in previous literature suffer from poor convergence error-rate performance due to the two phenomena explored in this paper. The first is the greedy-group phenomenon, which results in a small part of the decoding graph occupying most of the decoding resources. By limiting the number of updates for each edge message in the decoding graph, the proposed Quota-based RBP (Q-RBP) schedule can reduce the probability of greedy groups forming. The other phenomenon is the silent-variable-nodes issue, which is a condition where some variable nodes have no chance of contributing their intrinsic messages to the decoding process. As a result, we propose the Silent-Variable-Node-Free RBP (SVNF-RBP) schedule, which can force all variable nodes to contribute their intrinsic messages to the decoding process equally. Both the Q-RBP and the SVNF-RBP provide appealing convergence speed and convergence error-rate performance compared to previous IDS decoders for both dedicated and punctured LDPC codes.
Low-density parity-check (LDPC) codes offer excellent performance at competitive levels of complexity. Short block length LDPC codes avoid the large processing latency incurred by the large block lengths classically considered for this class of codes, making them a potential candidate for next generation wireless communications systems. In this paper, a novel informed dynamic scheduling (IDS) approach for decoding LDPC codes is developed based on the use of the current message reliabilities and the residuals of the potential updates to select the messages passed in the graph during iterative Sum Product decoding. An alternative measure of the iteration of the IDS schemes is also proposed which highlights the high cost of those algorithms in terms of processing complexity and motivates the development of the proposed approach. The proposed Rel.-RBP decoding algorithm offers very fast convergence at reduced complexity and gains in error rate performance when compared to the previous schemes.