Parameter estimation calibration of discretized polar modulation continuous-variable quantum key distribution

In experimental setups of continuous-variable quantum key distribution (CV-QKD), the ideal Gaussian modulation will suffer from discretization and degrade into discretized polar modulation (DPM), which deteriorates the accuracy of parameter estimation and results in an overestimation of excess noise. We demonstrate that in the asymptotic case, the DPM-induced estimation bias is determined exclusively by the modulation resolutions and can be modeled as a quadratic function. To obtain an accurate estimation, a calibration on the estimated excess noise is implemented based on the closed-form expression of the quadratic bias model, while statistical analysis of the model residuals defines the upper bound of estimated excess noise and the lower bound of secret key rate. Simulation results show that when modulation variance is 25 and excess noise is 0.02, the proposed calibration scheme can eliminate an estimation bias of 14.5%, thus enhancing the efficiency and feasibility of DPM CV-QKD.