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Optics Express

High-speed reconciliation with convergence-based early termination for CV-QKD using SC-LDPC codes

Chao Pan, Kun Zhang, Jia Hou

Published Jan 8, 2026• 0 citations
Publisher

Abstract

The information reconciliation (IR) stage is a critical component of post-processing in continuous-variable quantum key distribution (CV-QKD), which is essential to ensure high secret key rates and long transmission distances. Currently, improving reconciliation efficiency is a key research focus in the CV-QKD field. Additionally, the low-density parity-check (LDPC) decoding speed in IR is a post-processing bottleneck in high-speed CV-QKD. In this paper, we propose a construction scheme for spatially coupled (SC) LDPC codes in CV-QKD systems and maintain a constant code rate when extending the code length as required. Furthermore, we investigate the relationship between the syndrome variation pattern (SVP) and the frame error rate. Adaptively adjusting the number of decoding iterations according to the distinct convergence behaviors of the SVP, the convergence-based early termination (C-ET) scheme is proposed, which can reduce invalid iterations. The simulation results show that the proposed construction scheme for SC-LDPC codes can improve the reconciliation efficiency to 97% and achieve a flexible code length. The C-ET scheme achieves a 292% improvement in information throughput compared to the original ET scheme when the reconciliation efficiency reaches 97%. Moreover, the C-ET scheme also achieves a reduction in decoding latency compared to the existing syndrome-based early termination scheme. These advances provide a substantial step toward improving reconciliation efficiency and breaking the post-processing bottleneck in CV-QKD systems.

DOI
10.1364/oe.581729

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The information reconciliation (IR) stage is a critical component of post-processing in continuous-variable quantum key distribution (CV-QKD), which is essential to ensure high secret key rates and long transmission distances. Currently, improving reconciliation efficiency is a key research focus in the CV-QKD field. Additionally, the low-density parity-check (LDPC) decoding speed in IR is a post-processing bottleneck in high-speed CV-QKD. In this paper, we propose a construction scheme for spatially coupled (SC) LDPC codes in CV-QKD systems and maintain a constant code rate when extending the code length as required. Furthermore, we investigate the relationship between the syndrome variation pattern (SVP) and the frame error rate. Adaptively adjusting the number of decoding iterations according to the distinct convergence behaviors of the SVP, the convergence-based early termination (C-ET) scheme is proposed, which can reduce invalid iterations. The simulation results show that the proposed construction scheme for SC-LDPC codes can improve the reconciliation efficiency to 97% and achieve a flexible code length. The C-ET scheme achieves a 292% improvement in information throughput compared to the original ET scheme when the reconciliation efficiency reaches 97%. Moreover, the C-ET scheme also achieves a reduction in decoding latency compared to the existing syndrome-based early termination scheme. These advances provide a substantial step toward improving reconciliation efficiency and breaking the post-processing bottleneck in CV-QKD systems.
Information reconciliation (IR) is an indispensable component in the post-processing stage of continuous-variable quantum key distribution (CV-QKD), which adopts error-correcting codes to address the asymmetry of secret keys. Currently, low-density parity-check (LDPC) decoding in IR is a post-processing bottleneck in high-speed CV-QKD systems since the upper bound on secret key rate is higher than the information throughput delivered by decoder. In this paper, we study the relationship between the syndrome variation pattern (SVP) in iterative decoding and reconciliation frame error rate. An early termination scheme based on SVP is proposed and applied to multidimensional reconciliation, which can increase information throughput by adaptively adjusting the iteration number of iterative decoding to real-time decoding status. Furthermore, we show that only the resulting syndrome of the highest-rate code part in Raptor-like LDPC codes needs to be calculated to verify whether the reconciliation is successful by studying the convergency of resulting syndrome, which can save a large fraction of computational resources for syndrome calculation. Simulation results show that information throughput of the proposed scheme can be improved by 617.1% compared to the existing scheme when the IR efficiency reaches 97.09%. The proposed scheme points out a new direction for breaking the post-processing bottleneck in high-speed CV-QKD systems.
In continuous-variable (CV) quantum key distribution (QKD), the reconciliation efficiency and frame error rate of the information reconciliation have a significant impact on the secret key rate. For a fixed-rate multiedge-type low-density parity-check (LDPC) code, the reconciliation efficiency and frame error rate will inevitably vary due to the fluctuations of the signal-to-noise ratio (SNR) of the CV QKD system, which degrades the performance of the system. We propose a high-efficiency rate-adaptive information reconciliation scheme by combining raptorlike (RL) LDPC codes with the addition of trusted noises. We establish the model of adding trusted noises and combine it with the RL LDPC codes to optimize the secret key rate under the time-varying channel. The simulation results show that our scheme can maintain a high reconciliation efficiency of more than 94.4% and a low frame error rate within 15% fluctuation range of the SNR. Furthermore, we implement the hardware acceleration of the proposed rate-adaptive scheme on a graphics processing unit and achieve a decoding throughput of 65.5 Mbits/s by optimizing the storage of the parity-check matrix. Our results are useful for the practical CV QKD under the realistic time-varying channel.
The throughput of error correction is the main bottleneck of continuous variable quantum key distribution (CV-QKD) postprocessing. Implementing the decoder of low-density parity-check (LDPC) codes based on FPGA with limited precision can improve the decoding throughput significantly. However, the limited precision on FPGA results in the existence of residual error-bits after decoding, which lowers the secret key rate and restricts the application of high-rate real-time CVQKD system. In this paper, an efficient decoding scheme is proposed to erase the residual error-bits and decrease the frame errors rate (FER), where the decoding process into two stages and some values of initial Log Likelihood Ratio (LLR) are adjusted according to the proposed principles before starting the second-stage decoding. For the rates 0.2 and 0.1 LDPC codes, numerical results demonstrate that the proposed decoding scheme decreases the FER obviously and the throughputs of 152.47Mbps and 88.32Mbps are achieved, which can be applied to support high-speed CV-QKD system under transmission distance of 25km and 50km respectively.
In continuous-variable quantum key distribution (CV-QKD) systems, information reconciliation (IR) is a crucial step that significantly affects the secret key rate (SKR). The fixed-rate error-correcting codes used in IR are highly sensitive to changes in the signal-to-noise ratio (SNR) and cannot maintain a high reconciliation efficiency in practical CV-QKD systems. To address this issue, we first propose a rate-adaptive IR protocol, namely Threshold-based IR (TIR), which changes the code rate of low-density parity-check (LDPC) codes by selectively revealing bits with lower reliability and adjusting their log-likelihood ratios (LLRs). Then, we propose a rate-adaptive IR protocol, namely Sorting-based IR (SIR), which not only adjusts the code rate according to variations in SNR, but also enables the CV-QKD systems to achieve high reconciliation efficiency over a wide range of SNRs. Furthermore, we perform an analysis of the protocols in terms of code rate, reconciliation efficiency, and complexity. The simulation results demonstrate that the proposed protocols outperform other rate-adaptive IR protocols, achieving a reconciliation efficiency higher than 98.5% in the SNR range below -20 dB and maintaining a certain SKR in long-distance transmission.
Reconciliation is a necessary step in postprocessing of continuous-variable quantum key distribution (CV-QKD) system. We use globally coupled low-density parity-check (GC-LDPC) codes in reconciliation to extract a precise secret key from the raw keys over the authenticated classical public channel between two users. GC-LDPC codes have excellent performance over both the additive Gaussian white noise and binary-erasure channels. The reconciliation based on GC-LDPC codes can improve the reconciliation efficiency to 95.42% and reduce the frame error rate to 3.25 × 10–3. Using distillation, the decoding speed can achieve 23.8 Mbits/s and decrease the cost of memory. Given decoding speed and low memory usage, this makes the proposed reconciliation method viable approach for high-speed CV-QKD system.
Reconciliation is a significant procedure in a continuous-variable quantum key distribution (CV-QKD) system. It is employed to extract secure secret key from the resulted string through quantum channel between two users. However, the efficiency and the speed of previous reconciliation algorithms are low. These problems limit the secure communication distance and the secure key rate of CV-QKD systems. In this paper, we proposed a high-speed reconciliation algorithm through employing a well-structured decoding scheme based on low density parity-check (LDPC) code. The complexity of the proposed algorithm is reduced obviously. By using a graphics processing unit (GPU) device, our method may reach a reconciliation speed of 25 Mb/s for a CV-QKD system, which is currently the highest level and paves the way to high-speed CV-QKD.