Abstract
Integrating quantum key distribution (QKD) into the optical network through wavelength division multiplex (WDM) is promising for establishing large-scale QKD networks. However, the existing wavelength assignment schemes for WDM-QKD network all require to reserve a dedicate waveband for quantum signals, which influences the provisioning of data services, especially when the resource is tight. In this article, considering the quantum key pool (QKP) technology in the current QKD network, we propose a flexible key-size-driven wavelength assignment (KSD-WA) scheme to recycle the wavelength fragment to transmit quantum signals. Additionally, considering the noise impacts and the limited reconfiguration operations, we propose a heuristic algorithm to optimize the fragment selection with the objective of maximizing the secure key rate in the dynamic scenario. We also design a deep reinforcement learning (DeepRL) based algorithm to automatically learn the optimization policy under different environments. The simulation results verify that comparing with the conventional fixed-band (FB) scheme, the KSD-WA scheme assisted by the proposed optimization algorithms can provide adequate keys for encryption without affecting the provisioning of coexisting data services, which improves the compatibility of QKD with the real-life optical networks.
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