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An Efficient Two-Stage Decoding Scheme for LDPC-CRC Concatenated Codes

Lingjun Kong, Haiyang Liu, Yuezhuang Shi, Jiacheng Miao

Published Aug 25, 2025• 2 citations
Publisher

Abstract

In modern communication systems, the concatenation of a low-density parity-check (LDPC) code with a cyclic redundancy check (CRC) code is commonly used for error correction. In this paper, we propose a low-complexity two-stage scheme for decoding these codes using their concatenation structures. In the first stage, the traditional belief propagation (BP)-based iterative algorithm with a relative small maximum number of iterations is performed for decoding the LDPC code. If an LDPC codeword is obtained in this stage, the decoding process terminates. Otherwise, the second stage of the decoding process is performed, in which the guessing random additive noise decoding (GRAND) algorithm is applied to the CRC code. A list of information sequences satisfying the CRC check is obtained, each of which is then encoded to an LDPC codeword. The most likely codeword among them is the output of the decoding approach. The simulation results indicate that the proposed two-stage decoding approach can outperform the traditional BP-based iterative algorithm with a large maximum number of iterations. Moreover, the average complexity of the proposed approach is relatively low.

DOI
10.3390/e27090899

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This dissertation contains the following contributions on the low-complexity decoding schemes of LDPC codes.• Two-stage decoding scheme for LDPC codes -A new stopping criterion for LDPC codes -A new decoding scheme for LDPC codes with unreliable path search • Parallel unreliable path search algorithm • Analysis of two-stage decoding schemes -Validity and complexity analysis First, a new two-stage decoding scheme for low-density parity check (LDPC) codes to lower the error-floor is proposed.The proposed decoding scheme consists of the conventional belief propagation (BP) decoding algorithm as the first-stage decoding and the re-decodings with manipulated log-likelihood ratios (LLRs) of variable nodes as the second-stage decoding.In the first-stage decoding, an early stopping criterion is proposed for early detection of decoding failure and the candidate set of the variable nodes is determined, which can be partly included in the small trapping sets.In the second-stage decoding, the scores of the variable nodes in the candidate set are computed by the proposed unreliable path search algorithm and the variable nodes are sorted in ascending order by their scores for the re-decoding trials.Each re-decoding i trial is performed by BP decoding algorithm with manipulated LLR of a selected variable node in the candidate set one at a time with the second early stopping criterion.Secondly, the parallel unreliable path search algorithm is proposed for practical application to the proposed unreliable path search algorithm.In order to reduce the decoding delay and computational complexity, an efficient method for the search algorithm based on the parallel message-passing algorithm in the LDPC decoding is proposed.The parallel unreliable path search algorithm significantly reduces the additional complexity without extra hardware requirements.Finally, the validity and the complexity analysis of the proposed unreliable path search algorithm is presented.The proposed algorithm effectively finds the variable nodes in small trapping sets much more faster than the previous random selection method.Also, it is verified that the additional complexity of the parallel unreliable path search algorithm is less than that of one iteration of iterative decoders.

•Jan 1, 2017•0 citations
In modern communication systems, the concatenation of a low-density parity-check (LDPC) code with a cyclic redundancy check (CRC) code is commonly used for error correction. In this paper, we propose a low-complexity two-stage scheme for decoding these codes using their concatenation structures. In the first stage, the traditional belief propagation (BP)-based iterative algorithm with a relative small maximum number of iterations is performed for decoding the LDPC code. If an LDPC codeword is obtained in this stage, the decoding process terminates. Otherwise, the second stage of the decoding process is performed, in which the guessing random additive noise decoding (GRAND) algorithm is applied to the CRC code. A list of information sequences satisfying the CRC check is obtained, each of which is then encoded to an LDPC codeword. The most likely codeword among them is the output of the decoding approach. The simulation results indicate that the proposed two-stage decoding approach can outperform the traditional BP-based iterative algorithm with a large maximum number of iterations. Moreover, the average complexity of the proposed approach is relatively low.
Low-density parity-check (LDPC) codes have been widely used in practice due to their excellent error correction capabilities. However, the error correction performance of traditional decoding algorithms for LDPC codes is limited under short block lengths. To address this problem, this paper proposes an effective scheme that contains two stages for decoding short LDPC codes. In the first stage, the traditional belief propagation (BP) iterative algorithm is used to decode an LDPC code. The decoding process terminates if a codeword is obtained in this stage. Otherwise, the second stage decoding is invoked, in which the ordered reliability bits guessing random additive noise decoding (ORBGRAND) algorithm is applied. The accumulated log-likelihood ratios in the first stage are used to order the test error patterns in the ORBGRAND algorithm. Simulation results indicate that the proposed BP-ORBGRAND scheme can outperform the traditional BP iterative algorithm with relatively low additional complexity. Compared with the decoding scheme that concatenates the BP algorithm and the order statistics decoding (OSD) algorithm, the proposed decoding scheme has similar performance and the operations involved can be efficiently implemented in the hardware platform. All these indicate that the proposed scheme is desirable for practical purposes.
In this paper, a fresh belief propagation (BP) decoding algorithm is proposed. The proposed decoding algorithm with improved perturbation method is designed for short length low density parity-check (LDPC) codes aided by cyclic redundancy check (CRC). In the proposed algorithm corresponding to path size L, L decoding paths are considered concurrently. Then, a single codeword is selected according to the checking results of CRC. Simulation results show that the modified CRC-aided decoding scheme can enhance the error-correcting performance of short LDPC codes effectively.
In this paper, we focus on how to further improve the performance of short block-length low-density parity-check (LDPC) codes, especially the short LDPC codes in 5th generation (5G) New Radio (NR) systems. We propose an enhanced adaptive belief propagation (ABP) decoding algorithm with the assistance of partial cyclic redundancy check (CRC) bits. Meanwhile, the error detection ability can still be guaranteed by the remaining CRC bits and adaptive decoder parameters. Moreover, the proposed partial CRC-aided ABP (CA-ABP) decoding can be combined with the conventional BP decoding to further improve the performance. Simulation results show that compared with the BP decoding our proposed decoding method achieves an improvement in the error-correction performance.
In order to avoid unnecessary computation and increase system throughput, various early termination schemes are adopted in quasi-cyclic low-density parity-check (QC-LDPC) decoders. Cyclic redundancy check (CRC) based early termination scheme can be used when the information bits are concatenated with the CRC. The CRC is usually checked at the end of an iteration to verify the integrity of information bits. The latency of the CRC calculation results in an unnecessary decoding process. In this paper, we propose a distributed CRC early termination scheme for high throughput QC-LDPC codes. The proposed scheme distributes the CRC calculation in each layer of the iteration to minimize unnecessary computation and increase system throughput.
In this paper, we propose a modified adaptive belief propagation (ABP) algorithm, which is referred to as the random ABP (R-ABP) algorithm, for decoding short channel codes adopted in the fifth generation (5G) New Radio (NR) wireless systems. Based on the cyclic redundancy check (CRC) concatenation structure of 5G channel codes, we can take partial or even all CRC bits into iterative R-ABP decoding to improve the error correction performance, while the error detection capability can still be guaranteed by the remaining CRC bits and a proposed threshold-based acceptance criterion. We call this improved R-ABP decoding the threshold-and-CRC-aided R-ABP (TCA-R-ABP) decoding. The simulation results show that our proposed TCA-R-ABP algorithm outperforms the state-of-the-art decoding algorithms for many 5G low-density parity-check (LDPC) and polar codes. Moreover, the proposed TCA-R-ABP algorithm leads to a unified decoder for LDPC and polar codes, which has the potential to be a lower-complexity decoder over the combination of the belief propagation (BP) and CRC-aided successive cancellation list (CA-SCL) decoders.
This dissertation contains the following contributions on the low-complexity decoding schemes of LDPC codes.• Two-stage decoding scheme for LDPC codes -A new stopping criterion for LDPC codes -A new decoding scheme for LDPC codes with unreliable path search • Parallel unreliable path search algorithm • Analysis of two-stage decoding schemes -Validity and complexity analysis First, a new two-stage decoding scheme for low-density parity check (LDPC) codes to lower the error-floor is proposed.The proposed decoding scheme consists of the conventional belief propagation (BP) decoding algorithm as the first-stage decoding and the re-decodings with manipulated log-likelihood ratios (LLRs) of variable nodes as the second-stage decoding.In the first-stage decoding, an early stopping criterion is proposed for early detection of decoding failure and the candidate set of the variable nodes is determined, which can be partly included in the small trapping sets.In the second-stage decoding, the scores of the variable nodes in the candidate set are computed by the proposed unreliable path search algorithm and the variable nodes are sorted in ascending order by their scores for the re-decoding trials.Each re-decoding i trial is performed by BP decoding algorithm with manipulated LLR of a selected variable node in the candidate set one at a time with the second early stopping criterion.Secondly, the parallel unreliable path search algorithm is proposed for practical application to the proposed unreliable path search algorithm.In order to reduce the decoding delay and computational complexity, an efficient method for the search algorithm based on the parallel message-passing algorithm in the LDPC decoding is proposed.The parallel unreliable path search algorithm significantly reduces the additional complexity without extra hardware requirements.Finally, the validity and the complexity analysis of the proposed unreliable path search algorithm is presented.The proposed algorithm effectively finds the variable nodes in small trapping sets much more faster than the previous random selection method.Also, it is verified that the additional complexity of the parallel unreliable path search algorithm is less than that of one iteration of iterative decoders.