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Advanced Quantum Technologies

Rate‐Adaptive Non‐Binary LDPC Code‐Based Information Reconciliation Protocol for Continuous‐Variable Quantum Key Distribution

Xing Long, Dengke Qi, Ziyang Chen, Song Yu, Xiangyu Wang

Published Aug 28, 2025• 1 citation
Publisher

Abstract

Abstract Non‐binary (NB) low‐density parity‐check (LDPC) codes over high‐order finite fields offer error‐correction performance closer to the Shannon limit while directly processing NB symbols, making them well‐suited for continuous‐variable quantum key distribution (CV‐QKD), which inherently involves high‐dimensional data. However, current CV‐QKD implementations have not been deeply researched in this area and still rely on binary error‐correcting codes, limiting the full exploitation of continuous‐variable information. Furthermore, the high sensitivity of CV‐QKD to signal‐to‐noise ratio (SNR) fluctuations renders fixed‐rate codes inadequate for practical channel variations. To address these issues, in this work an information reconciliation protocol is proposed based on rate‐adaptive NB LDPC codes. It not only leverages the advantages of using LDPC codes over NB fields, but also exploits their ability to directly correct NB symbols by incorporating rate‐adaptive techniques at both the symbol‐wise and bit‐wise granularity. Simulation results indicate that under identical conditions, reconciliation efficiency increases with field order, reaching 98.90% over Galois Field(GF)(64). In addition, both symbol‐wise and bit‐wise rate‐adaptive techniques extend the applicability of fixed‐rate NB LDPC codes, with the bit‐wise scheme consistently yielding higher secure‐key rates across all fields. Together, these techniques significantly enhance the efficiency and adaptability of CV‐QKD information reconciliation.

DOI
10.1002/qute.202500389

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Abstract Non‐binary (NB) low‐density parity‐check (LDPC) codes over high‐order finite fields offer error‐correction performance closer to the Shannon limit while directly processing NB symbols, making them well‐suited for continuous‐variable quantum key distribution (CV‐QKD), which inherently involves high‐dimensional data. However, current CV‐QKD implementations have not been deeply researched in this area and still rely on binary error‐correcting codes, limiting the full exploitation of continuous‐variable information. Furthermore, the high sensitivity of CV‐QKD to signal‐to‐noise ratio (SNR) fluctuations renders fixed‐rate codes inadequate for practical channel variations. To address these issues, in this work an information reconciliation protocol is proposed based on rate‐adaptive NB LDPC codes. It not only leverages the advantages of using LDPC codes over NB fields, but also exploits their ability to directly correct NB symbols by incorporating rate‐adaptive techniques at both the symbol‐wise and bit‐wise granularity. Simulation results indicate that under identical conditions, reconciliation efficiency increases with field order, reaching 98.90% over Galois Field(GF)(64). In addition, both symbol‐wise and bit‐wise rate‐adaptive techniques extend the applicability of fixed‐rate NB LDPC codes, with the bit‐wise scheme consistently yielding higher secure‐key rates across all fields. Together, these techniques significantly enhance the efficiency and adaptability of CV‐QKD information reconciliation.
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.
Quantum key distribution (QKD) relies on information reconciliation to determine transmission distance and secure key rate. Existing schemes (e.g., Cascade) demand costly multiround interaction, while binary LDPC-based methods suffer limited error correction capability. This work proposes a QKD reconciliation scheme using non-binary (NB) LDPC codes, combined with a rate-adaptive technique tailored to NB LDPC characteristics. Simulations show NB LDPC codes outperform binary counterparts in error correction performance and reconciliation efficiency-with gains increasing with finite field order, achieving 1.0661 over the finite field GF(128). The rate-adaptive technique extends fixed-rate code applicability, alleviating practical code construction and storage challenges.
Information reconciliation protocol has a significant effect on the secret key rate and maximal transmission distance of continuous-variable quantum key distribution (CV-QKD) systems. We propose an efficient rate-adaptive reconciliation protocol suitable for practical CV-QKD systems with time-varying quantum channel. This protocol changes the code rate of multi-edge type low density parity check codes, by puncturing (increasing the code rate) and shortening (decreasing the code rate) techniques, to enlarge the correctable signal-to-noise ratios regime, thus improves the overall reconciliation efficiency comparing to the original fixed rate reconciliation protocol. We verify our rate-adaptive reconciliation protocol with three typical code rate, i.e., 0.1, 0.05 and 0.02, the reconciliation efficiency keep around 93.5%, 95.4% and 96.4% for different signal-to-noise ratios, which shows the potential of implementing high-performance CV-QKD systems using single code rate matrix.
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.
In continuous-variable quantum key distribution (CV-QKD), the information reconciliation step plays a crucial role in ensuring the security and efficiency of the key exchange process. This paper investigates the use of heuristic and reinforcement learning-based methods to adaptively adjust the low-density parity check (LDPC) code rate in response to the time-varying channel signal-noise-ratio (SNR), with the goal of maximizing the final key rate. Leaving the SNR to fluctuate by ±1dB around a fixed value, we analyze the trade-off between the reconciliation efficiency and the frame error rate (FER). We propose a rate-adaptive reconciliation scheme that leverages reinforcement learning to select the optimal LDPC code rate, comparing its performance against traditional fixed-rate approaches. The results demonstrate that the proposed adaptive scheme significantly enhances the key rate and shows potential in applying for a wide range of SNR.
Long block length rate-compatible low-density parity-compatible (LDPC) codes are designed to solve the problems of great variation of quantum channel noise and extremely low signal-to-noise ratio in continuous-variable quantum key distribution (CV-QKD). The existing rate-compatible methods for CV-QKD inevitably cost abundant hardware resources and waste secret key resources. In this paper, we propose a design rule of rate-compatible LDPC codes that can cover all potential SNRs with single check matrix. Based on this long block length LDPC code, we achieve high efficiency continuous-variable quantum key distribution information reconciliation with a reconciliation efficiency of 91.80% and we have higher hardware processing efficiency and lower frame error rate than other schemes. Our proposed LDPC code can obtain a high practical secret key rate and a long transmission distance in an extremely unstable channel.