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International Conference on Information and Communication Technology Convergence (ICTC)

Twofold Information Reconciliation Based on Polar Codes for CV-QKD

Chuwen Yang, Meixiang Zhang, Yuheng Wang, Xueqin Jiang

Published Oct 16, 2024• 0 citations
Publisher

Abstract

Continuous variable quantum key distribution (CV-QKD) enables authenticated parties to share a key. Information reconciliation (IR) is a critical step of the post-processing in CV-QKD, significantly affecting the secret key rate (SKR) shared between the legitimate parties. To improve the SKR performance of the CV-QKD without increasing the key inconsistency rate (KIR), this paper proposes a twofold IR method by performing independent operations on the Gaussian modulated coherent states (GMCS) obtained over the quantum channel. Specifically, assuming reverse reconciliation, after the GMCS are quantized, Bob generates parity bits, which are shared with Alice to help her correct the inconsistent bits in the quantized bits to generate the partial key. At the same time, the parity bits are used as frozen bits of polar codes in the multidimensional reconciliation (MR) to generate the other partial key. Simulation results demonstrate that the proposed twofold IR method increases the SKR nearly twice without increasing the inconsistent bits. In addition, we propose to apply symbol expansion and rotation (SER) based on the mapped GMCS to reduce the amount of information to be transmitted over the public error-free channel. Simulation results demonstrate that the performance of the proposed twofold IR with SER method can achieve a higher SKR with 3dB performance gap to that of the traditional MR protocol.

DOI
10.1109/ictc62082.2024.10827110

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Continuous variable quantum key distribution (CV-QKD) enables authenticated parties to share a key. Information reconciliation (IR) is a critical step of the post-processing in CV-QKD, significantly affecting the secret key rate (SKR) shared between the legitimate parties. To improve the SKR performance of the CV-QKD without increasing the key inconsistency rate (KIR), this paper proposes a twofold IR method by performing independent operations on the Gaussian modulated coherent states (GMCS) obtained over the quantum channel. Specifically, assuming reverse reconciliation, after the GMCS are quantized, Bob generates parity bits, which are shared with Alice to help her correct the inconsistent bits in the quantized bits to generate the partial key. At the same time, the parity bits are used as frozen bits of polar codes in the multidimensional reconciliation (MR) to generate the other partial key. Simulation results demonstrate that the proposed twofold IR method increases the SKR nearly twice without increasing the inconsistent bits. In addition, we propose to apply symbol expansion and rotation (SER) based on the mapped GMCS to reduce the amount of information to be transmitted over the public error-free channel. Simulation results demonstrate that the performance of the proposed twofold IR with SER method can achieve a higher SKR with 3dB performance gap to that of the traditional MR protocol.
Abstract Information reconciliation (IR) is a crucial component in the post-processing stage of continuous-variable quantum key distribution (CV-QKD) systems. However, the requirement to process a large amount of information in IR has become the bottleneck of realizing high-throughput CV-QKD systems, and the phenomenon of classical channel overloads appears. To solve these issues, we first propose a lossy compression scheme based on polar codes for the Gaussian sequences, and then propose an efficient IR protocol by combining such a lossy compression. By compressing the Gaussian sequences obtained by Alice and Bob, the new proposed protocol reduces the amount of information to be processed in IR, effectively breaking the bottleneck of realizing high-throughput CV-QKD systems. Additionally, it reduces the information Alice and Bob need to transmit over classical channels, easing the classical channel load. The theoretical analysis conducted on the compression ratio of the protocol and throughput offers valuable guidance for IR. Simulations confirmed that the proposed protocol can achieve higher throughput over the other polar-code-based IR protocols.
Quantum Key Distribution (QKD) is a communication method which exchanges secret keys using cryptographic protocols involving elements from quantum science. Continuous Variable (CV) QKD is a method to implement key exchange using sampling of Gaussian signals. Reconciliation in CV-QKD is fundamentally realized via coding of the Alice or Bob binary labels of the Gaussian samples using either one-way or interactive communications between the parties, Alice and Bob, over a public authenticated channel. We assume that the communication is performed through an Optical Wireless (OW) or Free Space Optics (FSO) channel. In that case the received signal suffers from stochastic fading due to pointing jitter or atmospheric turbulence. As a result of the channel fading and noise Alice and Bob Gaussian samples will not match. Information Reconciliation (IR) is the phase of the CV-QKD protocol that makes sure that Alice and Bob agree on a common and identical labeling of their samples, i.e. agree on a common stream of bits that we denote as “reconciled key.” The information reconciliation in CV-QKD could be done by one-way or two-way channel coding to correct the actual labels so that they do match. To do so Bob generates a sequence of parity bits using a systematic code. These bits are sent to Alice over an authenticated public channel. Alice then uses her own sequence of labels she obtains after quantization with the redundancy provided by Bob to recover Bob’s binary sequence. In this work we analyze the problem of information reconciliation for continuous variable quantum key distribution over a free space optics channel.
Continuous-variable quantum key distribution (CV-QKD) systems face challenges in maintaining efficient reconciliation over long distances due to the time variant signal-to-noise ratio (SNR) imposed by channel quality fluctuations. Hence fixed-rate error-correction schemes using low-density parity-check (LDPC) or Polar codes lead to high block-error rates (BLER) and degraded secret key rates (SKR). To overcome this, we propose an incremental redundancy aided hybrid automatic repeat request (IR-HARQ) protocol using rate-compatible Polar and LDPC codes. Explicitly, by puncturing a mother code and progressively transmitting additional redundant bits, our method dynamically adapts the effective coding rate to the prevalent channel conditions, achieving 2–3 dB SNR gains per retransmission. This adaptive strategy avoids unnecessary redundancy in good channels and strengthens protection in poor channels, thereby improving reconciliation efficiency. Simulation results show that our IR-HARQ scheme significantly enhances the BLER, throughput, and secure transmission distance compared with single-transmission schemes. Moreover, our study highlights that Polar IR-HARQ achieves superior performance in short block-length and low-SNR scenarios, while LDPC IR-HARQ is more competitive for longer codes and higher SNR. These findings confirm IR-HARQ as an attractive and versatile reconciliation solution for real-world CV-QKD deployments.
Abstract Quantum key distribution (QKD) is a secure cryptographic technology that enables two authenticated parties to share secret keys. Information reconciliation is an essential step in continuous-variable quantum key distribution (CV-QKD) protocols, which affects both the complexity and performance of the system. This paper reviews adaptive reconciliation protocols, and also proposes a new efficient scheme using systematic polar codes. Simulation results show that the proposed scheme can significantly increase reconciliation efficiency and reduce the overall computational complexity by reducing the average number of retransmissions, without significant reduction in effective secret key length.
In multidimensional reconciliation (MR) of continuous-variable quantum key distribution (CV-QKD) systems, the performance of conventional schemes is often limited by unreliable Gaussian-modulated coherent states (GMCSs). In this paper, we propose a reliability-driven preprocessing framework for MR. The proposed framework introduces a multi-step sample interleaver that redistributes GMCSs to increase intra-vector reliability while reducing the reliability imbalance across vectors. In addition, a bit-allocation strategy is designed to align the reliability of the soft information generated by MR with the reliability requirements of the employed forward error correction (FEC) codes. To further reduce implementation overhead, simplified log-likelihood ratio (LLR) estimation methods are also investigated. Simulation results demonstrate that the proposed scheme significantly improves the frame error rate (FER) performance compared with conventional schemes, while introducing only negligible additional latency, thereby extending the achievable transmission distance of CV-QKD systems.
Information reconciliation is an essential step of continuous-variable quantum key distribution (CV-QKD) because its efficiency affects both the maximum transmission distance and the final secret key rate of the whole system. Slice reconciliation can achieve high secret key rates for the CV-QKD systems under high signal-to-noise ratios (SNRs). However, it suffers from the high designing cost of the error-correcting codes in the multi-level coding and multi-stage decoding step. To reconcile one set of data with fixed SNR, multiple error-correcting codes with different code rates need to be designed. If the channel environment changed, the code rates need to change along to maintain high reconciliation efficiency, making it complicated and costly. In this paper, we introduce polar codes into slice reconciliation and proposed a scheme that is simply constructed, effectively performed, and well adapted to the systems with wide-range and variational SNRs. Simulation results show that the proposed scheme offers reconciliation efficiency over 95% for the systems with SNRs range from 1 to 10, which can support the systems with high secret key rates. The decrease of complexity and the increase of secret key rate have great significance for a practical CV-QKD system.