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基于多边型低密度奇偶校验码的连续变量量子密钥分发高速纠错

High speed error correction for continuous-variable quantum key distribution with multi-edge type LDPC code.

作者信息

Wang Xiangyu, Zhang Yichen, Yu Song, Guo Hong

机构信息

State Key Laboratory of Information Photonics and Optical Communications, Beijing University of Posts and Telecommunications, Beijing, 100876, China.

State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics Engineering and Computer Science, Center for Quantum Information Technology, Center for Computational Science and Engineering, Peking University, Beijing, 100871, China.

出版信息

Sci Rep. 2018 Jul 12;8(1):10543. doi: 10.1038/s41598-018-28703-4.

Abstract

Error correction is a significant step in postprocessing of continuous-variable quantum key distribution system, which is used to make two distant legitimate parties share identical corrected keys. We propose an experiment demonstration of high speed error correction with multi-edge type low-density parity check (MET-LDPC) codes based on graphic processing unit (GPU). GPU supports to calculate the messages of MET-LDPC codes simultaneously and decode multiple codewords in parallel. We optimize the memory structure of parity check matrix and the belief propagation decoding algorithm to reduce computational complexity. Our results show that GPU-based decoding algorithm greatly improves the error correction speed. For the three typical code rate, i.e., 0.1, 0.05 and 0.02, when the block length is 10 and the iteration number are 100, 150 and 200, the average error correction speed can be respectively achieved to 30.39 Mbits/s (over three times faster than previous demonstrations), 21.23 Mbits/s and 16.41 Mbits/s with 64 codewords decoding in parallel, which supports high-speed real-time continuous-variable quantum key distribution system.

摘要

纠错是连续变量量子密钥分发系统后处理中的一个重要步骤,该系统用于使两个相距遥远的合法方共享相同的纠错密钥。我们提出了一种基于图形处理单元(GPU)的、采用多边类型低密度奇偶校验(MET-LDPC)码的高速纠错实验演示。GPU支持同时计算MET-LDPC码的消息并并行解码多个码字。我们优化了奇偶校验矩阵的内存结构和置信传播解码算法,以降低计算复杂度。我们的结果表明,基于GPU的解码算法大大提高了纠错速度。对于三种典型码率,即0.1、0.05和0.02,当码块长度为10且迭代次数分别为100、150和200时,并行解码64个码字时,平均纠错速度分别可达30.39 Mbits/s(比之前的演示快三倍多)、21.23 Mbits/s和16.41 Mbits/s,这支持高速实时连续变量量子密钥分发系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5d06/6043537/2e6fcbde838e/41598_2018_28703_Fig1_HTML.jpg

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