A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit <a rel="external noopener" href="https://arxiv.org/pdf/1903.10107v1.pdf">the original URL</a>. The file type is <code>application/pdf</code>.
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Reconciliation is a crucial procedure in post-processing of Quantum Key Distribution (QKD), which is used for correcting the error bits in sifted key strings. Although most studies about reconciliation of QKD focus on how to improve the efficiency, throughput optimizations have become the highlight in high-speed QKD systems. Many researchers adpot high cost GPU implementations to improve the throughput. In this paper, an alternative high throughput and efficiency solution implemented in low<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1903.10107v1">arXiv:1903.10107v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nmbokbhuqrcmxngmnf4p7ep24e">fatcat:nmbokbhuqrcmxngmnf4p7ep24e</a> </span>
more »... CPU is proposed. The main contribution of the research is the design of a quantized LDPC decoder including improved RCBP-based check node processing and saturation-oriented variable node processing. Experiment results show that the throughput up to 60Mbps is achieved using the bi-directional approach with reconciliation efficiency approaching to 1.1, which is the optimal combination of throughput and efficiency in Discrete-Variable QKD (DV-QKD). Meanwhile, the performance remains stable when Quantum Bit Error Rate (QBER) varies from 1% to 8%.
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