基于RC-LDPC/误差估计的星载FSO/QKD系统密钥协商
Key Reconciliation with RC-LDPC/Error Estimation for Satellite-based FSO/QKD Systems
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- The University of Aizu（会津大学）
- IIT Roorkee（罗尔基印度理工学院）
- Indian Institute of Technology Indore（印多尔印度理工学院）
机构由 AI 辅助整理，请以论文原文为准。
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中文总结 AI 辅助
针对星载FSO/QKD系统信道波动导致的密钥协商难题，提出结合RC-LDPC码与综合征误差估计的方案，减少通信轮数并首次建立端到端SKT分析框架，数值验证其优于传统盲协商。
中文摘要 AI 辅助
星载自由空间光（FSO）量子密钥分发（QKD）系统因其实现全球安全应用的潜力，近期引起了显著的研究兴趣。然而，由天气条件和卫星移动性引起的FSO信道固有不确定性，导致合法用户之间的量子比特误码率（QBER）出现剧烈波动。这使得设计高效的密钥协商（QKD后处理中的关键步骤）尤为具有挑战性。在本工作中，我们提出了一种密钥协商方案，该方案将原模图速率兼容（RC）低密度奇偶校验（LDPC）码与基于综合征的误差估计方法相结合。所提出的误差估计方法减少了通信轮数，且无需额外的信息泄露。此外，据我们所知，我们首次开发了一个分析框架来评估端到端密钥吞吐量（SKT），该框架考虑了不完美误差估计和动态FSO信道条件的影响。数值结果表明，所提出的方案在不同FSO信道条件下始终优于传统盲协商，并为系统参数选择提供了实用指南。最后，我们通过一个包含Starlink低地球轨道（LEO）卫星和移动地面车辆的案例研究验证了所提出的框架。
英文摘要
Satellite-based free-space optics (FSO) quantum key distribution (QKD) systems have recently attracted significant research interest due to their potential to enable globally secured applications. However, the inherent uncertainty of FSO channels, caused by weather conditions and satellite mobility, induces severe fluctuations in quantum bit-error rate (QBER) between legitimate users. This makes designing an efficient key reconciliation, an essential step in the QKD post-processing, particularly challenging. In this work, we propose a key reconciliation scheme that combines protograph rate-compatible (RC) low-density parity-check (LDPC) codes with a syndrome-based error estimation method. The proposed error estimation method reduces the number of communication rounds without requiring additional information disclosure. Furthermore, to our best knowledge, an analytical framework is first developed to evaluate end-to-end secret-key throughput (SKT), accounting for the impact of imperfect error estimation and dynamic FSO channel conditions. Numerical results demonstrate that the proposed scheme consistently outperforms conventional blind reconciliation under diverse FSO channel conditions and provide practical guidelines for system parameter selection. Finally, we validate the proposed framework through a case study that incorporates data from a Starlink low-Earth orbit (LEO) satellite and moving ground vehicles.
