Lossy compression based on polar codes for high throughput information reconciliation in CV-QKD systems

Abstract

Information reconciliation (IR) is a crucial component in the post-processing stage of continuous-variable quantum key distribution (CV-QKD) systems. However, the requirement to process a large amount of information in IR has become the bottleneck of realizing high-throughput CV-QKD systems, and the phenomenon of classical channel overloads appears. To solve these issues, we first propose a lossy compression scheme based on polar codes for the Gaussian sequences, and then propose an efficient IR protocol by combining such a lossy compression. By compressing the Gaussian sequences obtained by Alice and Bob, the new proposed protocol reduces the amount of information to be processed in IR, effectively breaking the bottleneck of realizing high-throughput CV-QKD systems. Additionally, it reduces the information Alice and Bob need to transmit over classical channels, easing the classical channel load. The theoretical analysis conducted on the compression ratio of the protocol and throughput offers valuable guidance for IR. Simulations confirmed that the proposed protocol can achieve higher throughput over the other polar-code-based IR protocols.