1.School of Automation, Central South University, Changsha 410083, China 2.School of Business, Central South University, Changsha 410083, China 3.Hunan Aerospace Construction Engineering Co., Ltd., Changsha 410205, China 4.School of Computer Science and Engineering, Central South University, Changsha 410083, China
Fund Project:Project supported by the National Natural Science Foundation of China (Grant Nos. 61871407, 61872390, 61801522)
Received Date:07 December 2020
Accepted Date:13 January 2021
Available Online:27 May 2021
Published Online:05 June 2021
Abstract:Continuous-variable quantum key distribution (CVQKD) is an important application of quantum technology, which enables long-distance communicating parties to establish a string of unconditionally secure keys in an insecure environment. However, in a practical CVQKD system, the finite sampling bandwidth of the analog-to-digital converter (ADC) at the receiver may create inaccurate sampling results, leading to errors in parameter estimation process and leaving a security loophole for eavesdroppers. In order to eliminate the finite sampling bandwidth effect, we propose a peak-compensation-based CVQKD scheme, which estimates the discrepancy between the maximum sampling value and the peak value of each pulse based on the characteristics of Gaussian pulse. The maximum sampling values are compensated by the estimated discrepancy, so that the legitimate parties can obtain correct sampling results. We analyze the influence of the finite sampling bandwidth on the security of the system, expounding the specific steps of peak-compensation, comparing the estimated excess noise before and after peak-compensation, and discussing the security of the system under Gaussian collective attacks. Simulation results show that this scheme can greatly improve the accuracy of pulse peak sampling and remove the finite sampling bandwidth effect. Moreover, the channel parameters estimated by the communicating parties are also corrected by using the compensated values. Compared with the scheme without peak-compensation, this scheme eliminates the limitation of the system repetition to the secret key bit rate, and has longer secure transmission distance and higher secret key bit rate. In addition, compared with other methods of solving the finite sampling bandwidth effect, the proposed scheme can be directly implemented in data processing stage after sampling without any additional devices, and thus increasing no complexity of the system. Keywords:continuous variable/ quantum key distribution/ sampling bandwidth/ peak compensation
图 2 零差探测器输出脉冲的时域波形, 箭头表示采样位置. ${t_{\rm{s}}}$为采样间隔, ${U_{\rm{p}}}$为脉冲的峰值, ${U_{\rm{m}}}$为最大测量值, ${T_0}$为脉冲持续时间 Figure2. Time-domain shape of an output pulse from the balanced homodyne detector. ${t_{\rm{s}}}$, sampling interval; ${U_{\rm{p}}}$, peak value of the pulse; ${U_{\rm{m}}}$, maximal measurement value; ${T_0}$, duration of each pulse.
$\Delta t = \frac{{{\sigma ^2}}}{{2{t_s}}}{\rm{In}}\frac{{{U_2}}}{{{U_4}}}.$
3)用得到的ΔU补偿Um, 可得正确的脉冲峰值Up. 图3(a)是在系统重复率为120 MHz、采样频率为1 GHz时一串高斯脉冲的被采样情况, 在这种情况下每个脉冲的最大采样值都不是脉冲的峰值点. 图3(b)是对最大采样值进行峰值补偿之后的采样情况, 我们发现补偿后的值刚好是每个脉冲的峰值点, 证明了提出的峰值补偿方案的有效性. 图 3 (a)有限采样带宽影响下的高斯脉冲时域采样情况; (b)峰值补偿后的采样值. 其中蓝色线表示脉冲时域波形, 红色圆点代表采样值 Figure3. (a) Sampling positions of Gaussian pulses effected by finite-sampling bandwidth; (b) sampling values after peak compensation. The blue line represents the time-domain shape of the pulses, and the red dots represent the sampled values.
图4给出了在不同信道过噪声下的估计过噪声随系统重复率的变化情况. 从上到下的曲线分别代表$\varepsilon {{ = 0}}.{\rm{04}}, \varepsilon {{ = 0}}.{\rm{02}}, \varepsilon {{ = 0}}.{\rm{01}}$时的结果. 显然, 在不进行峰值补偿时, 估计的过噪声会随系统重复率的增加而减小, 这意味着系统重复率越高, Eve越容易隐藏自己; 而在进行峰值补偿后, 估计的过噪声在不同系统重复率下都保持恒定. 图 4 不同信道过噪声情况下的估计过噪声随系统重复率的变化. 图中PC表示峰值补偿(peak-compensation, PC) Figure4. The estimated excess noise as a function of the system repetition rate under different channel excess noise. PC in the figure represents peak-compensation.
在进行峰值补偿的情况下, 实际的过噪声等于估计的过噪声. 图5(a)给出了不同系统重复率${f_{{\rm{rep}}}} = 2 , 5 , $$ 8 \;{\rm{MHz}}$的安全密钥率随传输距离的变化, 从图中可知, 峰值补偿后系统的密钥率和传输距离不受系统重复率的影响, 且此时的安全传输距离大于不进行峰值补偿时的情况. 图5(b)给出了不同传输距离$L = 30 , 40 , 50 \;{\rm{km}}$的密钥比特率随系统重复率的变化, 显然, 在进行峰值补偿后, 系统的密钥比特率随系统重复率的增加而呈正比持续增加; 而在不采取峰值补偿时, 密钥比特率随系统重复率的增加呈现先增加后减小的趋势. 因此, 本文提出的峰值补偿方案不仅增加了系统的安全性, 消除了由于有限采样带宽引入的安全性漏洞, 也解除了系统重复频率对密钥比特率的限制. 在计算密钥率的过程中, 涉及的系统参数分别设置为${V_{\rm{A}}} = 20$, ${v_{{\rm{el}}}} = $$ 0.01$, $\beta = 0.95$, $\eta = 0.6$, ${f_{{\rm{samp}}}} = 1$ GHz. 图 5 (a)不同系统重复率下的密钥率随传输距离的变化; (b)不同传输距离下的密钥比特率随系统重复率的变化 Figure5. (a) The secret key rate as a function of the transmission distance under different system repetition rate; (b) the secret bit rate as a function of the system repetition rate under different transmission distance.