Facing the 6G: an AI-enhance quantum-secured fronthaul architecture

Amidst the development of communication technologies, the limitations of 5G communication systems, particularly in security and resource management, have become increasingly apparent. As the 6G era approaches, there are growing demands for integrated systems that ensure robust security and optimize resource utilization. To address these challenges, this paper proposes a novel architecture that integrates classical communication channels and quantum key distribution (QKD) channels using wavelength-division multiplexing (WDM). This innovative approach allows classical and quantum channels to coexist within a single optical fiber, improving security and fiber utilization while reducing system complexity and cost. A key contribution of this work is introducing an AI-based prediction and management module, dynamically adjusting the quantum key generation rate according to real-time usage and forecasted demand. By leveraging machine learning, the module predicts quantum key consumption patterns, ensuring that the key generation rate aligns with the system’s security and performance requirements. This approach balances key generation and usage, minimizing resource waste and enhancing the system’s overall efficiency. The feasibility of the proposed architecture is validated through an analysis of spontaneous Raman scattering (SpRS), showing the architecture maintains high key generation rates and low quantum bit error rates (QBER) under optimal system conditions. Furthermore, an analysis reveals that the AI module meets the requirement of predicting key usage and managing the key generation rate. Lastly, the feasibility is further validated by an experiment. Overall, this study presents a comprehensive framework for integrating classical and quantum channels in future 6G networks, providing enhanced security, efficiency, and scalability.