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arXiv:2212.01121 · Entropy

Asymmetric Adaptive LDPC-Based Information Reconciliation for Industrial Quantum Key Distribution

N. V. Borisov, Ivan Petrov, A. Tayduganov

Published Dec 23, 2022• 17 citations
arXivHTMLPDF

Abstract

We develop a new approach for asymmetric LDPC-based information reconciliation in order to adapt to the current channel state and achieve better performance and scalability in practical resource-constrained QKD systems. The new scheme combines the advantages of LDPC codes, a priori error rate estimation, rate-adaptive and blind information reconciliation techniques. We compare the performance of several asymmetric and symmetric error correction schemes using a real industrial QKD setup. The proposed asymmetric algorithm achieves significantly higher throughput, providing a secret key rate that is close to the symmetric one in a wide range of error rates. Thus, our approach is found to be particularly efficient for applications with high key rates, limited classical channel capacity and asymmetric computational resource allocation.

DOI
10.3390/e25010031

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We develop a new approach for asymmetric LDPC-based information reconciliation in order to adapt to the current channel state and achieve better performance and scalability in practical resource-constrained QKD systems. The new scheme combines the advantages of LDPC codes, a priori error rate estimation, rate-adaptive and blind information reconciliation techniques. We compare the performance of several asymmetric and symmetric error correction schemes using a real industrial QKD setup. The proposed asymmetric algorithm achieves significantly higher throughput, providing a secret key rate that is close to the symmetric one in a wide range of error rates. Thus, our approach is found to be particularly efficient for applications with high key rates, limited classical channel capacity and asymmetric computational resource allocation.
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 is a critical component of Quantum Key Distribution, ensuring that mismatches between Alice's and Bob's keys are corrected. In this study, we analyze, simulate, optimize, and compare the performance of two prevalent algorithms used for Information Reconciliation: Cascade and LDPC codes in combination with the Blind protocol. We focus on their applicability in practical and industrial settings, operating in realistic and application-close conditions. The results are further validated through evaluation on a live industrial QKD system.
The purpose of reconciliation, one of classical aspects of quantum key distribution (QKD) protocol, is to mitigate errors after the distribution of quantum information over a quantum channel. In this paper, a rate-adaptive method is proposed by means of a channel coding scheme where specific low-density parity-check (LDPC) codes are adapted in the Slepian-Wolf coding system. Puncturing and shortening techniques are adopted to optimize their coding rates with all possible cases of error in QKD. This successful method utilizes the knowledge of the quantum bit error rate (QBER) based on the maximum-likelihood estimator with respect to the syndrome information. Its benefit is that avoids wasting sample keys in the traditional channel estimation and thus increases the size of the final secret key. Evidently, simulation results confirm an improvement in the reconciliation efficiency with minimal interaction that suitable for high QKD throughput applications.
Information Reconciliation (IR) is a key step in Quantum key distribution (QKD). In recent years, blind reconciliation based on low-density parity-check (LDPC) codes has replaced Cascade as a standardde facto, since it guarantees efficient information reconciliation without a priori quantum bit error rate estimation and with limited interactivity between the parties, which is essential in high key-rate and long distance QKD links. In this paper, a novel blind reconciliation scheme based on rateless protograph LDPC codes is proposed. The rate adaptivity, essential for blind reconciliation, is obtained by progressively splitting LDPC check nodes, which ensures a number of degrees of freedom larger than puncturing in code design. The protograph nature of the LDPC codes allows to use the same designed codes with a large variety of sifted-key lengths, enabling a blocklength flexibility, which is important in largely varying key-rate link conditions. The code design is based on a new protograph Discretized Density Evolution tool.
ABSTRACT Information reconciliation is a critical component of quantum key distribution, ensuring that mismatches between Alice's and Bob's keys are corrected. In this study, we analyse, simulate, optimise and compare the performance of two prevalent algorithms used for information reconciliation: Cascade and LDPC codes in combination with the blind protocol. We focus on their applicability in practical and industrial settings, operating in realistic and application‐close conditions. The results are further validated through evaluation on a live industrial QKD system.
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 2×1032 \times 10^32×103 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.