High-throughput GPU layered decoder of multi-edge type low density parity check codes in continuous-variable quantum key distribution systems

TL;DR

This paper introduces a GPU-based layered decoder for multi-edge type LDPC codes in CV-QKD systems, significantly increasing decoding throughput and enabling faster quantum key distribution postprocessing.

Contribution

It presents a novel GPU-optimized layered decoding method for QC-METLDPC codes, improving decoding speed and efficiency in CV-QKD systems.

Findings

Decoding speeds up to 64.11 Mbits/s for rate 0.1

Achieves 48.65 Mbits/s for rate 0.05

Reaches 39.51 Mbits/s for rate 0.02

Abstract

The decoding throughput in the postprocessing is one of the bottlenecks for a continuous-variable quantum key distribution (CV-QKD) system. In this paper, we propose a layered decoder to decode quasi-cyclic multi-edge type LDPC (QC-METLDPC) codes based on graphic processing unit (GPU) in continuous-variable quantum key distribution (CV-QKD) systems. We optimize the storage method of the parity check matrix, merge the sub-matrices which are unrelated, and decode multiple codewords in parallel on GPU. Simulation results demonstrate that the average decoding speed of LDPC codes with three typical code rates, i.e., 0.1, 0.05 and 0.02, is up to 64.11Mbits/s, 48.65Mbits/s and 39.51Mbits/s, respectively, when decoding 128 codewords of length 106 simultaneously without early termination.