Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

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

Haider Abdulkarim, Hussein Khaleel, Marwa K. Farhan

Published Oct 12, 2026• 0 citations
Publisher

Abstract

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.

DOI
10.21203/rs.3.rs-10251569/v1

Related papers

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

Performance Simulation of a Layered QC-LDPC Decoder for URLLC Applications

Bilal Mejmaa, Chakir Aqil, Ismail Akharraz +1 more

This research investigates the simulation performance of a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G New-Radio (NR) standards. The proposed work focuses on short block-length QC-LDPC codes (280,176) to meet the dual challenge of achieving ultra-low latency (<1ms) while maintaining high reliability. LDPC codes have traditionally excelled at longer code lengths; this study demonstrates the effectiveness of LDPC codes in short-length contexts through architectural optimization utilizing a layered decoding approach, which provides improved convergence speed and reduced latency compared to traditional flooding techniques. The baseline QC-LDPC decoder performs better in terms of Bit Error Rate (BER) and Block Error Rate (BLER) with only 7 iterations. For a target BLER of 10 −2 , the decoder outperforms reference shorter codes (K40, K64) with an E b /N o gain of up to 0.9 dB.

EPJ Web of Conferences•Jan 1, 2026•0 citations

Performance Simulation of a Layered QC-LDPC Decoder for URLLC Applications

Bilal Mejmaa, Chakir Aqil, Ismail Akharraz +1 more

This research investigates the simulation performance of a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G New-Radio (NR) standards. The proposed work focuses on short block-length QC-LDPC codes (280,176) to meet the dual challenge of achieving ultra-low latency (<1ms) while maintaining high reliability. LDPC codes have traditionally excelled at longer code lengths; this study demonstrates the effectiveness of LDPC codes in short-length contexts through architectural optimization utilizing a layered decoding approach, which provides improved convergence speed and reduced latency compared to traditional flooding techniques. The baseline QC-LDPC decoder performs better in terms of Bit Error Rate (BER) and Block Error Rate (BLER) with only 7 iterations. For a target BLER of 10−2, the decoder outperforms reference shorter codes (K40, K64) with an Eb/No gain of up to 0.9 dB.

•Jul 1, 2026•0 citations

Trapping-Set-Assisted Decoding for Short-Length Low-Density Parity-Check Codes

Asif Ali Zamzami, Zhu-En Yu, Yuh-Tser Wu +1 more

To guarantee that every device in industrial Internet of Things (IoT) is reliable for fast data exchange, ultrareliable and low-latency communication (URLLC) technology from 5G is crucial. To reduce latency, typically, only up to 1000 code blocklength is allowed. Indeed, a block error rate (BLER) of less than$10^{-5}$and latency of less than 1 ms are achievable in 5G URLLC. The short code blocklength feature is also required in satellite IoT. Though low-density parity-check (LDPC) decoding via belief propagation (BP) shows promise for achieving low BLER with long blocklength, its BLER is high in short LDPC codes due to error-prone patterns, with the trapping set (TS) being one of the most significant patterns. To alleviate the damage of TS, which can be identified offline, we propose two decoding algorithms named dynamic TS-assisted reinforced BP (DTS-RBP) and TS-assisted relaxation for neural-network BP (TSR-NNBP), respectively. Compared with previous works, only proposed TS assisted decoders can meet URLLC requirements under 308 code blocklength at a 3 dB signal-to-noise ratio (SNR). Moreover, under 128 code blocklength for satellite IoT, our DTS-RBP decoder provides the best memory-performance tradeoff with approximately the same number of iterations as BP.

IEEE Internet of Things Journal•Apr 24, 2025•2 citations

Hardware Efficient FPGA Implementation of a Layered QC-LDPC Decoder for Ultra-Reliable Low-Latency Communications

Bilal Mejmaa, Chakir Aqil, Abdelaziz Lberni +2 more

Low-Density Parity-Check (LDPC) codes have traditionally performed better at longer code lengths. This research develops and rigorously evaluates a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder architecture intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G and subsequent technologies. The paper investigates LDPC codes in short-length contexts through architectural optimization based on a layered decoding approach, which provides improved convergence speed and reduced latency compared with traditional flooding techniques. The short block-length QC-LDPC code (280,176) addresses the dual challenge of achieving ultra-low latency while maintaining high performance relative to existing work. For a target BLER of 10−2, the decoder outperforms the shorter reference codes (60,40) and (96,64), with an Eb/N0 gain of up to 0.9 dB, part of which is attributable to the longer block length rather than to the decoder alone. The FPGA implementation results demonstrate that the design is hardware-efficient: it operates at a maximum frequency of 218.62 MHz, resulting in a throughput of 155.77 Mbps, while maintaining a decoding latency of only 1.129 µs and a power consumption of 0.201 W.

Chips•Aug 4, 2026•0 citations

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

Li Juan DENG, Zilong Liu, Yong Liang Guan +4 more

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.

arXiv:2012.10743•IEEE Transactions on Communications•Dec 24, 2020•17 citations
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) of3×10−53 \times 10^{-5}3×10−5by around 0.176 and 0.092 dB respectively, with almost the same number of iterations.
This research investigates the simulation performance of a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G New-Radio (NR) standards. The proposed work focuses on short block-length QC-LDPC codes (280,176) to meet the dual challenge of achieving ultra-low latency (<1ms) while maintaining high reliability. LDPC codes have traditionally excelled at longer code lengths; this study demonstrates the effectiveness of LDPC codes in short-length contexts through architectural optimization utilizing a layered decoding approach, which provides improved convergence speed and reduced latency compared to traditional flooding techniques. The baseline QC-LDPC decoder performs better in terms of Bit Error Rate (BER) and Block Error Rate (BLER) with only 7 iterations. For a target BLER of 10 −2 , the decoder outperforms reference shorter codes (K40, K64) with an E b /N o gain of up to 0.9 dB.
This research investigates the simulation performance of a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G New-Radio (NR) standards. The proposed work focuses on short block-length QC-LDPC codes (280,176) to meet the dual challenge of achieving ultra-low latency (<1ms) while maintaining high reliability. LDPC codes have traditionally excelled at longer code lengths; this study demonstrates the effectiveness of LDPC codes in short-length contexts through architectural optimization utilizing a layered decoding approach, which provides improved convergence speed and reduced latency compared to traditional flooding techniques. The baseline QC-LDPC decoder performs better in terms of Bit Error Rate (BER) and Block Error Rate (BLER) with only 7 iterations. For a target BLER of 10−2, the decoder outperforms reference shorter codes (K40, K64) with an Eb/No gain of up to 0.9 dB.
To guarantee that every device in industrial Internet of Things (IoT) is reliable for fast data exchange, ultrareliable and low-latency communication (URLLC) technology from 5G is crucial. To reduce latency, typically, only up to 1000 code blocklength is allowed. Indeed, a block error rate (BLER) of less than10−510^{-5}10−5and latency of less than 1 ms are achievable in 5G URLLC. The short code blocklength feature is also required in satellite IoT. Though low-density parity-check (LDPC) decoding via belief propagation (BP) shows promise for achieving low BLER with long blocklength, its BLER is high in short LDPC codes due to error-prone patterns, with the trapping set (TS) being one of the most significant patterns. To alleviate the damage of TS, which can be identified offline, we propose two decoding algorithms named dynamic TS-assisted reinforced BP (DTS-RBP) and TS-assisted relaxation for neural-network BP (TSR-NNBP), respectively. Compared with previous works, only proposed TS assisted decoders can meet URLLC requirements under 308 code blocklength at a 3 dB signal-to-noise ratio (SNR). Moreover, under 128 code blocklength for satellite IoT, our DTS-RBP decoder provides the best memory-performance tradeoff with approximately the same number of iterations as BP.
Low-Density Parity-Check (LDPC) codes have traditionally performed better at longer code lengths. This research develops and rigorously evaluates a layered Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) decoder architecture intended for Ultra-Reliable Low-Latency Communication (URLLC) applications in 5G and subsequent technologies. The paper investigates LDPC codes in short-length contexts through architectural optimization based on a layered decoding approach, which provides improved convergence speed and reduced latency compared with traditional flooding techniques. The short block-length QC-LDPC code (280,176) addresses the dual challenge of achieving ultra-low latency while maintaining high performance relative to existing work. For a target BLER of 10−2, the decoder outperforms the shorter reference codes (60,40) and (96,64), with an Eb/N0 gain of up to 0.9 dB, part of which is attributable to the longer block length rather than to the decoder alone. The FPGA implementation results demonstrate that the design is hardware-efficient: it operates at a maximum frequency of 218.62 MHz, resulting in a throughput of 155.77 Mbps, while maintaining a decoding latency of only 1.129 µs and a power consumption of 0.201 W.
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.