Noise-aware resource allocation with integrated key generation and consumption for CV-QKD over WDM networks
Shifeng Ding, Gangxiang Shen, Fengxian Tang, Chun-Kit Chan
Abstract
Continuous-variable quantum key distribution (CV-QKD) has been regarded as a promising approach to secure optical communications over wavelength division multiplexing (WDM) networks. Conventionally, the key generation and the key consumption were considered separately, thus potentially leading to a possible mismatch between them and significantly degrading the network efficiency. A few studies considered these two parts jointly but assumed the worst noise condition, which may lead to an over-supply of quantum keys. In this paper, we propose a noise-aware resource allocation (NARA) scheme and design a framework to balance the generation and the consumption of quantum keys for CV-QKD over WDM networks. We formulate the NARA problem as a mixed-integer linear programming (MILP) model. An efficient heuristic algorithm with three allocation schemes, including threshold-based noise loading (TNL), stress-based noise loading (SNL), and noise margin reservation (NMR), has been designed. Simulation results show that NARA with the NMR scheme can significantly reduce the total number of wavelengths used and the total network cost under all system parameters by more than 10% and 20%, respectively, compared to the other two schemes.