Bayesian Parameter Estimation for Continuous-Variable Quantum Key Distribution

The effectiveness and accuracy of parameter estimation are guarantees for the high-performance and high-safety operation of practical continuous-variable quantum key distribution systems. A scheme based on Bayesian estimation is proposed to tackle the fluctuations of channels. In free-space channel, the Bayesian random-effects model is employed to construct complete prior information, and the channel state information extracted through pilot signals is applied to rectify the prior information. Compressed sensing technology is applied due to the sparsity of the free-space channel to reduce the cost of the system. Experimental results show that the proposed scheme has higher estimation accuracy under the free space, and the system performance is also enhanced. Moreover, the results under fiber show higher estimation accuracy and better stability than that of traditional methods. In conclusion, the scheme can create practical conditions for the construction of future global quantum networks.