Noise-suppressing channel allocation in dynamic DWDM-QKD networks using LightGBM

TL;DR

This paper introduces a machine learning-based method using LightGBM to dynamically allocate channels in DWDM-QKD networks, effectively reducing noise and improving secure key rates amidst fluctuating traffic and noise conditions.

Contribution

It presents a novel ML framework for real-time quantum channel allocation that adapts to dynamic noise, enhancing performance over static schemes.

Findings

Achieves higher secure key rates in dynamic noise environments

Reduces operational complexity compared to previous methods

Effectively resists noise impacts in realistic optical networks

Abstract

Integrating quantum key distribution (QKD) with existing optical networks is highly desired to reduce the deployment costs and achieve efficient resource utilization, and some pointtopoint transmitting experiments have verified its feasibility. Nevertheless, there are still many problems in the realistic scenario where QKD coexists with dynamic data traffics. On the one hand, the conventional static channel allocation schemes cannot guarantee the quality of quantum channels in the presence of the timevarying noises. On the other hand, considering the complex noise generation caused by dynamic classical data traffics with variable characters, it is challenging to achieve online high-performance quantum channel assignments. To address these problems, we propose a machine learning based noise-suppressing channel allocation (ML-NSCA) scheme. In this scheme, the LightGBM based ML framework is trained to predict the optimal channel allocations with lowest noise impacts, according to which, the quantum channels are periodically reallocated to guarantee high secure key rate. To improve the accuracy and scalability of the ML framework, we also optimize the method of feature extraction during the training process. The performance evaluation results indicate that the proposed scheme can effectively resist the dynamic noise impacts in the realistic optical networks and obtain higher secure key rate with less operation complexity than the previous schemes.