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量子卫星星舰通信是量子保密通信的重要应用场景之一, 在海面上, 由于不同风速所引起的气溶胶粒子浓度发生剧烈变化, 而气溶胶粒子浓度的剧变, 必然导致星舰量子链路性能的剧烈衰减. 然而, 有关不同海面风速与量子卫星星舰通信信道参数关系的研究, 迄今尚未展开. 本文根据海面风速与气溶胶的Gras模型, 分别建立了风速与星舰量子信道误码率、信道容量和信道平均保真度的定量关系. 仿真结果表明, 当风速分别为4 m/s和20 m/s时, 海洋大气信道误码率、信道容量、信道平均保真度分别依次为4.62 × 10–3和4.91 × 10–3、0.957和0.65、0.999和0.974. 由此可见, 风速对海上量子通信性能有显著的影响. 因此, 为了提高通信的可靠性, 应根据风速大小, 自适应调整系统的各项参数.In the ocean atmosphere boundary layer far from the continent, marine aerosols generally include two types: sea salt aerosols and secondary marine aerosols. The sea salt aerosols, also called sea salt droplets, stay in the atmosphere for a short time. The sea salt aerosols are produced by the splashing of waves caused by sea breeze on the sea surface. Quantum satellite-to-ship communication is one of the important application scenarios of quantum secret communication. The quantum satellite-to-ship communication is an important part of building a global quantum communication network. In the South China Sea, because the change of wind speed will cause a sharp change in the concentration of aerosol particles and the sharp change of the concentration of aerosol particles can change its own extinction characteristics, the change of aerosol extinction characteristics will inevitably lead to a dramatic attenuation of the satellite-to-ship’s quantum link performance. However, the research on the relationship between wind speed on the sea surface and quantum satellite satellite-to-ship communication channel parameters has not been carried out so far. In this paper, based on the Gras model of wind speeds on the sea surface and aerosol, the quantitative relationship between wind speed and satellite-to-ship quantum channel error rate, channel capacity and channel average fidelity are established respectively. The simulation results show that when the transmission distance is constant, as the sea surface wind speed increases, the channel bit error rate increases; as the wind speed increases, the channel capacity of quantum satellite satellite-to-ship communication decreases; when the source probability is constant, as the wind speed increases, the average fidelity of the channel shows a decreasing trend. When the wind speeds are 4 m/s and 20 m/s, the oceanic atmospheric channel error rate, channel capacity, and channel average fidelity are respectively 4.62 × 10–3 and 4.91 × 10–3, 0.957 and 0.65, 0.999 and 0.974. It can be seen that the wind speed has a significant effect on the performance of maritime quantum communication. Therefore, when quantum communication over the ocean, in order to improve the reliability of communication, the parameters of the system should be adaptively adjusted according to the wind speed.
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Keywords:
- aerosol particle concentration /
- wind speed at sea /
- quantum satellite communication /
- depolarizing channel
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Lu X Y 2017 Ph. D. Dissertation (Hefei: University of Science and Technology of China) (in Chinese)
[15] 耿蒙 2017 硕士学位论文 (合肥: 中国科学技术大学)
Geng M 2017 M.S. Thesis (Hefei: University of Science and Technology of China) (in Chinese)
[16] 王菲菲, 李学彬, 郑显明, 张文忠, 罗涛, 朱文越, 成巍, 邓志武 2019 红外与激光工程 48 89Google Scholar
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Zhang X Z, Xu Q, Liu B Y 2020 Acta Optica Sin. 40 165
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Zhang D Y 2013 Quantum Logic Gates and Quantum Decoherence (Beijing: Science Press) pp90−110 (in Chinese)
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Yin H, Ma H X 2006 Introduction to Quantum Communication in Military (Beijing: Military Science Press) pp224−228 (in Chinese)
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Yin H, Han Y 2013 Quantum Communication Theory and Technology (Beijing: Publishing House of Electronics Industry) pp76−83 (in Chinese)
[22] 尼尔森, 庄著(郑大钟, 赵千川译)2005 量子计算和量子信息(二) (北京: 清华大学出版社)第57−60页
Nielsen A, Chuang I (translated by Zheng D Z, Zhao Q C) 2005 Quantum Computation and Quantum Information (Vol.2) (Beijing: TsingHua University Press) pp57−60 (in Chinese)
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表 1 南海气溶胶粒子谱分布各参量取值情况
Table 1. The value of each parameter of size distribution of aerosol particle in the South China Sea.
Mode ${N_{\rm{o}}}$ ${r_{\rm{g} } }/$μm ${\sigma _{\rm{g}}}$ Fine mode $254.93$ $0.09$ $0.53$ Middle mode $7.96$ $1$ $0.7$ 表 2 信道误码率各参量取值情况
Table 2. The value of each parameter of channel bit error rate.
${F_{\rm{s}}}$ ${R_{\rm{r}}}$ $\mu $ ${P_{\rm{a}}}$ ${T_{\rm{a}}}$ ${\eta _{\rm{d}}}$ ${F_{\rm{m}}}$ ${n_1}$ ${n_2}$ $\theta $ $0.5$ $0.5$ $1$ $0.5$ $1$ $0.65$ $1$ ${10^{ - 3}}$ ${10^{ - 6}}$ $\pi /6$ -
[1] Dai J N, Liu Y M, Wang P, Fu X, Xia M, Wang T 2020 Atmos. Environ. 236 117604Google Scholar
[2] Plauškaitė K, Špirkauskaitė N, Byčenkienė S, Kecorius S, Jasinevičienė D, Petelski T, Zielinski T, Andriejauskienė J, Barisevičiūtė R, Garbaras A, Makuch P, Dudoitis V, Ulevicius V 2017 Mar. Chem. 190 13Google Scholar
[3] Ueda S, Miura K, Kawata R, Furutani H, Uematsu M, Omori Y, Tanimoto H 2016 Atmos. Environ. 142 324Google Scholar
[4] Yin J, Li Y H, Liao S K, Yang M, Cao Y, Zhang L, Ren J G, Cai W Q, Liu W Y, Li S L, Shu R, Huang Y M, Deng L, Li L, Zhang Q, Liu N L, Chen Y A, Lu C Y, Wang X B, Xu F H, Wang J Y, Peng C Z, Ekert A K, Pan J W 2020 Nature 582 501Google Scholar
[5] Vergoossen T, Loarte S, Bedington R, Kuiper H, Ling A 2020 Acta Astronaut. 173 164Google Scholar
[6] 杨璐, 马鸿洋, 郑超, 丁晓兰, 高建存, 龙桂鲁 2017 物理学报 66 230303Google Scholar
Yang L, Ma H Y, Zheng C, Ding X L, Gao J C, Long G L 2017 Acta Phys. Sin. 66 230303Google Scholar
[7] Xue P, Wang K K, Wang X P 2017 Sci. Rep. 7 661Google Scholar
[8] 聂敏, 任杰, 杨光, 张美玲, 裴昌幸 2015 物理学报 64 150301Google Scholar
Nie M, Ren J, Yang G, Zhang M L, Pei C X 2015 Acta Phys. Sin. 64 150301Google Scholar
[9] 谷文苑, 赵尚弘, 东晨, 朱卓丹, 屈亚运 2019 物理学报 68 090302Google Scholar
Gu W Y, Zhao S H, Dong C, Zhu Z D, Qu Y Y 2019 Acta Phys. Sin. 68 090302Google Scholar
[10] 聂敏, 潘越, 杨光, 孙爱晶, 禹赛雅, 张美玲, 裴昌幸 2018 物理学报 67 140305Google Scholar
Nie M, Pan Y, Yang G, Sun A J, Yu S Y, Zhang M L, Pei C Y 2018 Acta Phys. Sin. 67 140305Google Scholar
[11] 卫容宇, 聂敏, 杨光, 张美玲, 孙爱晶, 裴昌幸 2019 物理学报 68 140302Google Scholar
Wei R Y, Nie M, Yang G, Zhang M L, Sun A J, Pei C X 2019 Acta Phys. Sin. 68 140302Google Scholar
[12] Tian P F, Cao X J, Zhang L, Wang H B, Shi J S, Huang Z W, Zhou T, Liu H 2015 Atmos. Environ. 117 212Google Scholar
[13] Dumka U C, Ningombam S S, Kaskaoutis D G, Madhavan B L, Song H J, Angchuk D, Jorphail S 2020 Sci. Total Environ. 734 139354Google Scholar
[14] 鲁先洋 2017 博士学位论文 (合肥: 中国科学技术大学)
Lu X Y 2017 Ph. D. Dissertation (Hefei: University of Science and Technology of China) (in Chinese)
[15] 耿蒙 2017 硕士学位论文 (合肥: 中国科学技术大学)
Geng M 2017 M.S. Thesis (Hefei: University of Science and Technology of China) (in Chinese)
[16] 王菲菲, 李学彬, 郑显明, 张文忠, 罗涛, 朱文越, 成巍, 邓志武 2019 红外与激光工程 48 89Google Scholar
Wang F F, Li X B, Zheng X M, Zhang W Z, Luo T, Zhu W Y, Cheng W, Deng Z W 2019 Infrared Laser Eng. 48 89Google Scholar
[17] 张秀再, 徐茜, 刘邦宇 2020 光学学报 40 165
Zhang X Z, Xu Q, Liu B Y 2020 Acta Optica Sin. 40 165
[18] 聂敏, 常乐, 杨光, 张美玲, 裴昌幸 2017 光子学报 46 16Google Scholar
Nie M, Chang L, Yang G, Zhang M L, Pei C X 2017 Acta Phtonica Sin. 46 16Google Scholar
[19] 张登玉 2013 量子逻辑门与量子退相干 (北京: 科学出版社) 第90−110页
Zhang D Y 2013 Quantum Logic Gates and Quantum Decoherence (Beijing: Science Press) pp90−110 (in Chinese)
[20] 尹浩, 马怀新 2006 军事量子通信概论(北京: 军事科学出版社) 第224−228页
Yin H, Ma H X 2006 Introduction to Quantum Communication in Military (Beijing: Military Science Press) pp224−228 (in Chinese)
[21] 尹浩, 韩阳 2013 量子通信原理与技术(北京: 电子工业出版社) 第76−83页
Yin H, Han Y 2013 Quantum Communication Theory and Technology (Beijing: Publishing House of Electronics Industry) pp76−83 (in Chinese)
[22] 尼尔森, 庄著(郑大钟, 赵千川译)2005 量子计算和量子信息(二) (北京: 清华大学出版社)第57−60页
Nielsen A, Chuang I (translated by Zheng D Z, Zhao Q C) 2005 Quantum Computation and Quantum Information (Vol.2) (Beijing: TsingHua University Press) pp57−60 (in Chinese)
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