Quantum key distribution (QKD) is a promising technique for secure communication based on quantum mechanical principles. To improve the secure key rate of a QKD system, most studies on reconciliation primarily focused on improving the efficiency. With the increasing performance of QKD systems, the research priority has shifted to the improvement of both throughput and efficiency. In this paper, we propose a high performance solution of Cascade reconciliation, including a high-throughput-oriented framework and an integrated-optimization-oriented scheme. Benefiting from the fully utilizing computation and storage resources, effectively dealing with communication delays, the integrated-optimization-oriented parameters setting, etc., an excellent overall performance was achieved. Experimental results showed that, the throughput of up to 570Mbps with an efficiency of 1.038 was achieved, which, to our knowledge, was more than four times faster than any throughput previously demonstrated. Furthermore, throughputs on real data sets were capable of reaching up to 86Mbps even on embedded platforms. Additionally, our solution offers good adaptability to the fluctuating communication delay and quantum bit error rate (QBER). Based on our study, low performance (i.e. low power-consumption and cost-effective) CPU platforms will be sufficient for reconciliation in the existing and near-term QKD systems.
Quantum key distribution (QKD) is a promising technique for secure communication based on quantum mechanical principles. To improve the secure key rate of a QKD system, most studies on reconciliation primarily focused on improving the efficiency. With the increasing performance of QKD systems, the research priority has shifted to the improvement of both throughput and efficiency. In this paper, we propose a high performance solution of Cascade reconciliation, including a high-throughput-oriented framework and an integrated-optimization-oriented scheme. Benefiting from the fully utilizing computation and storage resources, effectively dealing with communication delays, the integrated-optimization-oriented parameters setting, etc., an excellent overall performance was achieved. Experimental results showed that, the throughput of up to 570Mbps with an efficiency of 1.038 was achieved, which, to our knowledge, was more than four times faster than any throughput previously demonstrated. Furthermore, throughputs on real data sets were capable of reaching up to 86Mbps even on embedded platforms. Additionally, our solution offers good adaptability to the fluctuating communication delay and quantum bit error rate (QBER). Based on our study, low performance (i.e. low power-consumption and cost-effective) CPU platforms will be sufficient for reconciliation in the existing and near-term QKD systems.
Quantum key distribution (QKD) is a promising technique for secure communication based on quantum mechanical principles. To improve the secure key rate of a QKD system, most studies on reconciliation primarily focused on improving the efficiency. With the increasing performance of QKD systems, the research priority has shifted to the improvement of both throughput and efficiency. In this paper, we propose a high performance solution of Cascade reconciliation, including a high-throughput-oriented framework and an integrated-optimization-oriented scheme. Benefiting from the fully utilizing computation and storage resources, effectively dealing with communication delays, the integrated-optimization-oriented parameters setting, etc., an excellent overall performance was achieved. Experimental results showed that, the throughput of up to 570Mbps with an efficiency of 1.038 was achieved, which, to our knowledge, was more than four times faster than any throughput previously demonstrated. Furthermore, throughputs on real data sets were capable of reaching up to 86Mbps even on embedded platforms. Additionally, our solution offers good adaptability to the fluctuating communication delay and quantum bit error rate (QBER). Based on our study, low performance (i.e. low power-consumption and cost-effective) CPU platforms will be sufficient for reconciliation in the existing and near-term QKD systems.
Information reconciliation is a crucial procedure in the classical post-processing of quantum key distribution (QKD). Poor reconciliation efficiency, revealing more information than strictly needed, may compromise the maximum attainable distance, while poor performance of the algorithm limits the practical throughput in a QKD device. Historically, reconciliation has been mainly done using close to minimal information disclosure but heavily interactive procedures, like \textit{Cascade}, or using less efficient but also less interactive ---just one message is exchanged--- procedures, like the ones based in low-density parity-check (LDPC) codes. The price to pay in the LDPC case is that good efficiency is only attained for very long codes and in a very narrow range centered around the quantum bit error rate (QBER) that the code was designed to reconcile, thus forcing to have several codes if a broad range of QBER needs to be catered for. Real world implementations of these methods are thus very demanding, either on computational or communication resources or both, to the extent that the last generation of GHz clocked QKD systems are finding a bottleneck in the classical part. In order to produce compact, high performance and reliable QKD systems it would be highly desirable to remove these problems. Here we analyse the use of short-length LDPC codes in the information reconciliation context using a low interactivity, \textit{blind}, protocol that avoids an a priori error rate estimation. We demonstrate that 2×103 bits length LDPC codes are suitable for blind reconciliation. Such codes are of high interest in practice, since they can be used for hardware implementations with very high throughput.
Quantum Key Distribution (QKD) is a pivotal technology in the quest for secure communication, harnessing the power of quantum mechanics to ensure robust data protection. However, scaling QKD to meet the demands of high-speed, real-world applications remains a significant challenge. Traditional key rate determination methods, dependent on complex mathematical models, often fall short in efficiency and scalability. In this paper, we propose an approach that involves integrating machine learning (ML) techniques with the Cascade error correction protocol to enhance the scalability and efficiency of QKD systems. Our ML-based approach utilizes an autoencoder framework to predict the Quantum Bit Error Rate (QBER) and final key length with over 99\% accuracy. This method significantly reduces error correction time, maintaining a consistently low computation time even with large input sizes, such as data rates up to 156 Mbps. In contrast, traditional methods exhibit exponentially increasing computation times as input sizes grow, highlighting the superior scalability of our ML-based solution. Through comprehensive simulations, we demonstrate that our method not only accelerates the error correction process but also optimizes resource utilization, making it more cost-effective and practical for real-world deployment. The Cascade protocol's integration further enhances system security by dynamically adjusting error correction based on real-time QBER observations, providing robust protection against potential eavesdropping. Our research establishes a new benchmark for scalable, high-throughput QKD systems, proving that machine learning can significantly advance the field of quantum cryptography. This work continues the evolution towards truly scalable quantum communication.
For high-speed quantum key distribution (QKD) post processing, information reconciliation is the most computational step, which usually acts as the system speed bottleneck. Reconciliation efficiency and operation throughput are the two most important performance parameters, but they are often compromised to each other in actual realization due to the available hardware resources. Another characteristic of the information reconciliation is that its channel is time-varying, and in order to guarantee high efficiency, some rate-compatible error correction scheme should be adopted. To cope with the above problems, this paper proposes a rate-compatible high-efficiency reconciliation algorithm based on quasi-cyclic (QC) low-density parity-check (LDPC) codes and puncturing algorithms. On the other hand, in order to obtain high throughput while maintaining low implementation complexity, the normalized min-sum algorithm (NMSA) is realized and optimized by using the fast prototyping tool of high-level synthesis (HLS). The proposed information reconciliation module was implemented on the Xilinx Zynq Ultrascale+ ZCU102 development board. Experimental results show that the maximum throughput rate of the implemented reconciliation module in this paper can reach 136 Mbps, while the efficiency factor is kept lower than 1.32 across the error rate range of 1.7%∼10.6% under the remaining frame error rate level of 10−3. The comprehensive good performance obtained by our design can strongly support the development of modern high-speed QKD systems.
Quantum key distribution (QKD) enables unconditional secure communication by exploiting the principles of quantum mechanics. However, existing reconciliation protocols face a trade-off between error correction efficiency and information leakage. To address this challenge, we propose an enhanced QKD reconciliation scheme based on polynomial interpolation. The protocol introduces a block-wise algebraic structure to unify error detection and correction, significantly reducing interactive rounds while maintaining high efficiency. A comprehensive information-theoretic leakage model is established, covering polynomial interpolation, verification, and iterative error localization. To further ensure unconditional security, a cascaded privacy amplification mechanism is integrated, combining two compression stages tailored to reconciliation leakage and quantum channel leakage, respectively. Moreover, an adaptive parameter optimization strategy dynamically adjusts block size and polynomial order according to the quantum bit error rate (QBER), achieving robustness under diverse channel conditions. Theoretical analysis and simulations demonstrate that the proposed scheme achieves a secure key rate of 65–72% at QBER < 3%, outperforming the classical CASCADE protocol by 8–12%, and maintains 30–50% efficiency under moderate error rates. Computational complexity analysis shows performance comparable to LDPC-based approaches while offering superior leakage control. These results confirm that the proposed protocol provides a balanced trade-off among efficiency, security, and implementation complexity, making it suitable for deployment in practical QKD systems.
Quantum key distribution (QKD) relies on quantum and classical procedures in order to achieve the growing of a secret random string -the key- known only to the two parties executing the protocol. Limited intrinsic efficiency of the protocol, imperfect devices and eavesdropping produce errors and information leakage from which the set of measured signals -the raw key- must be stripped in order to distill a final, information theoretically secure, key. The key distillation process is a classical one in which basis reconciliation, error correction and privacy amplification protocols are applied to the raw key. This cleaning process is known as information reconciliation and must be done in a fast and efficient way to avoid cramping the performance of the QKD system. Brassard and Salvail proposed a very simple and elegant protocol to reconcile keys in the secret-key agreement context, known as Cascade, that has become the de-facto standard for all QKD practical implementations. However, it is highly interactive, requiring many communications between the legitimate parties and its efficiency is not optimal, imposing an early limit to the maximum tolerable error rate. In this paper we describe a low-density parity-check reconciliation protocol that improves significantly on these problems. The protocol exhibits better efficiency and limits the number of uses of the communications channel. It is also able to adapt to different error rates while remaining efficient, thus reaching longer distances or higher secure key rate for a given QKD system.