Discrete-modulation continuous-variable quantum key distribution with high key rate

Abstract

Discrete-modulation continuous-variable quantum key distribution has the potential for large-scale deployment in the secure quantum communication networks due to low implementation complexity and compatibility with the current telecom systems. The security proof for four coherent states phase-shift keying (4-PSK) protocol has recently been established by applying numerical methods. However, the achievable key rate is relatively low compared with the optimal Gaussian modulation scheme. To enhance the key rate of discrete-modulation protocol, we first show that 8-PSK increases the key rate by about 60% in comparison to 4-PSK, whereas the key rate has no significant improvement from 8-PSK to 12-PSK. We then expand the 12-PSK to two-ring constellation structure with four states in the inner ring and eight states in the outer ring, which significantly improves the key rate to be 2.4 times of that of 4-PSK. The key rate of the two-ring constellation structure can reach 70% of the key rate achieved by Gaussian modulation in long distance transmissions, making this protocol an attractive alternative for high-rate and low-cost application in secure quantum communication networks.

Experimental Demonstration of Discrete Modulation Formats for Continuous Variable Quantum Key Distribution

“…Such a modulation has been used for advanced experimental implementations [4][5][6] , but is not a common industrial practice; a more practical approach is to send coherent states chosen from a finite constellation in phase space. Although such discrete modulations were considered early in CV-QKD [12][13][14] , sound security proofs have been developed only recently, for protocols with either very large constellation sizes 15 or very small ones [16][17][18][19] , with some experimental implementations in the latter case 20,21 . But the most interesting format of medium-size quadrature amplitude modulation (QAM) used in classical optical communications remained out of reach for these methods, which rely on solving huge convex optimization problems.…”