© 2026 Aqora Quantum S.A.S.

Terms Privacy Legal Notice

arXiv:2012.10743 · IEEE Transactions on Communications

Perturbed Adaptive Belief Propagation Decoding for High-Density Parity-Check Codes

Li Juan DENG, Zilong Liu, Yong Liang Guan, Xiaobei Liu, Chaudhry Adnan Aslam, Xiaoxi Yu, Zhiping Shi

Published Dec 24, 2020• 17 citations

Abstract

Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This article aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding for high-density parity-check (HDPC) algebraic codes, such as Reed-Solomon (RS) codes, Bose-Chaudhuri-Hocquenghem (BCH) codes, and product codes. The key idea of traditional ABP is to sparsify certain columns of the parity-check matrix corresponding to the least reliable bits with small log-likelihood-ratio (LLR) values. This sparsification strategy may not be optimal when some bits have large LLR magnitudes but wrong signs. Motivated by this observation, we propose a Perturbed ABP (P-ABP) to incorporate a small number of unstable bits with large LLRs into the sparsification operation of the parity-check matrix. In addition, we propose to apply partial layered scheduling or hybrid dynamic scheduling to further enhance the performance of P-ABP. Simulation results show that our proposed decoding algorithms lead to improved error correction performances and faster convergence rates than the prior-art ABP variants.

DOI: 10.1109/tcomm.2020.3047085

Related papers

CRC-Aided Adaptive Belief Propagation Decoding of NR LDPC Codes

Xianwen Zhang, Ming Jiang, Mingyang Zhu +2 more

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.

IEEE Vehicular Technology Conference•Jun 1, 2022•3 citations

Adaptive Belief Propagation Decoding of CRC Concatenated NR LDPC and Polar Codes

Mingyang Zhu, Ming Jiang, Chunming Zhao

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.

IEEE Transactions on Communications•Jun 20, 2022•13 citations

Improving Short-Block LDPC Decoding Using Perturbation-Based Rescue with Maximum Likelihood Based Candidate Validation

Haider Abdulkarim, Hussein Khaleel, Marwa K. Farhan

Abstract Meeting the latency and reliability requirements of 5G Ultra-Reliable Low-Latency Communications (URLLC) is enabled through the adoption of short-block Low-Density Parity-Check (LDPC) codes. Traditional decoding of short-block LDPC using Belief Propagation (BP) may fail due to trapping sets, resulting in degraded decoding performance. This paper proposes a three-stage decoding algorithm that combines low-iteration BP decoding, a perturbation-based rescue process, and Maximum Likelihood (ML) based candidate validation to improve decoding reliability. When the low-iteration BP decoding stage fails to converge, the rescue stage perturbs the least reliable bits to generate multiple decoding candidates, which are subsequently evaluated using an ML-based metric to select the most likely candidate and reduce miscorrections. The proposed algorithm was evaluated through MATLAB simulations with a short-block LDPC configuration for 5G URLLC systems. QAM modulation was used and two channel models were considered, Additive White Gaussian Noise and flat Rayleigh fading. The performance was investigated for different numbers of perturbed bits and different coding rates. The results show improved decoding performance compared to standard LDPC, achieving coding gains exceeding 1 dB at low bit error rates while reducing decoding failures caused by trapping sets.

•Oct 12, 2026•0 citations

Stopping-Set Assisted Reinforced Belief Propagation for Decoding Short LDPC Codes

Asif Ali Zamzami, Kuan-Chuan Chao, Shih‐Chun Lin

The low-density parity-check (LDPC) code is chosen to be a channel coding scheme for ultra-reliable and low-latency communications (URLLC) in 5G. However, short LDPC compromises the belief propagation (BP) decoder because of the stopping set (SS) in the decoding graph. We propose to perform different node operations according to the SS. A dynamic SS selection according to the received sequence is further applied. In the length 308 5G LDPC, our decoders outperform prior work, improving BP and collaborative BP at block error probability (BLER) of$3 \times 10^{-5}$by around 0.176 and 0.092 dB respectively, with almost the same number of iterations.

IEEE Communications Letters•Dec 21, 2021•5 citations

Belief Propagation Decoding for Short Codes on Structured Sparse Parity-Check Matrices

Yifei Shen, Zongyao Li, Emmanuel Boutillon +5 more

As successfully adopted in standard long code scenarios, belief propagation (BP) decoding has been considered a promising universal decoding candidate for next-generation wireless communications. However, when applied to short codes, BP decoding suffers from poor error correction performance due to harmful cycle structures in the Tanner graph. In this paper, we address this issue by designing a structured, sparse parity-check matrix (ssPCM) framework, composed of multiple cycle-free parity-check row blocks (PCRBs). The resulting ssPCMs feature regular row weights and perform better than the state-of-theart 4 -cycle-free row redundant PCMs across Bose-Chaudhuri-Hocquenghem (BCH) codes of length 63.

IEEE International Symposium on Information Theory (ISIT)•Jun 22, 2025•3 citations

Two Effective Scheduling Schemes for Layered Belief Propagation of 5G LDPC Codes

Bingbing Wang, Yan Zhu, Jing Kang

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.

IEEE Communications Letters•Apr 30, 2020•40 citations

Algebraic codes such as BCH code are receiving renewed interest as their short block lengths and low/no error floors make them attractive for ultra-reliable low-latency communications (URLLC) in 5G wireless networks. This article aims at enhancing the traditional adaptive belief propagation (ABP) decoding, which is a soft-in-soft-out (SISO) decoding for high-density parity-check (HDPC) algebraic codes, such as Reed-Solomon (RS) codes, Bose-Chaudhuri-Hocquenghem (BCH) codes, and product codes. The key idea of traditional ABP is to sparsify certain columns of the parity-check matrix corresponding to the least reliable bits with small log-likelihood-ratio (LLR) values. This sparsification strategy may not be optimal when some bits have large LLR magnitudes but wrong signs. Motivated by this observation, we propose a Perturbed ABP (P-ABP) to incorporate a small number of unstable bits with large LLRs into the sparsification operation of the parity-check matrix. In addition, we propose to apply partial layered scheduling or hybrid dynamic scheduling to further enhance the performance of P-ABP. Simulation results show that our proposed decoding algorithms lead to improved error correction performances and faster convergence rates than the prior-art ABP variants.

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 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.

Abstract Meeting the latency and reliability requirements of 5G Ultra-Reliable Low-Latency Communications (URLLC) is enabled through the adoption of short-block Low-Density Parity-Check (LDPC) codes. Traditional decoding of short-block LDPC using Belief Propagation (BP) may fail due to trapping sets, resulting in degraded decoding performance. This paper proposes a three-stage decoding algorithm that combines low-iteration BP decoding, a perturbation-based rescue process, and Maximum Likelihood (ML) based candidate validation to improve decoding reliability. When the low-iteration BP decoding stage fails to converge, the rescue stage perturbs the least reliable bits to generate multiple decoding candidates, which are subsequently evaluated using an ML-based metric to select the most likely candidate and reduce miscorrections. The proposed algorithm was evaluated through MATLAB simulations with a short-block LDPC configuration for 5G URLLC systems. QAM modulation was used and two channel models were considered, Additive White Gaussian Noise and flat Rayleigh fading. The performance was investigated for different numbers of perturbed bits and different coding rates. The results show improved decoding performance compared to standard LDPC, achieving coding gains exceeding 1 dB at low bit error rates while reducing decoding failures caused by trapping sets.

The low-density parity-check (LDPC) code is chosen to be a channel coding scheme for ultra-reliable and low-latency communications (URLLC) in 5G. However, short LDPC compromises the belief propagation (BP) decoder because of the stopping set (SS) in the decoding graph. We propose to perform different node operations according to the SS. A dynamic SS selection according to the received sequence is further applied. In the length 308 5G LDPC, our decoders outperform prior work, improving BP and collaborative BP at block error probability (BLER) of

3 \times 10^{-5}

by around 0.176 and 0.092 dB respectively, with almost the same number of iterations.

As successfully adopted in standard long code scenarios, belief propagation (BP) decoding has been considered a promising universal decoding candidate for next-generation wireless communications. However, when applied to short codes, BP decoding suffers from poor error correction performance due to harmful cycle structures in the Tanner graph. In this paper, we address this issue by designing a structured, sparse parity-check matrix (ssPCM) framework, composed of multiple cycle-free parity-check row blocks (PCRBs). The resulting ssPCMs feature regular row weights and perform better than the state-of-theart 4 -cycle-free row redundant PCMs across Bose-Chaudhuri-Hocquenghem (BCH) codes of length 63.

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.