Future-proofing 6G Networks: A Quantum Approach
Abstract
Integrating Quantum Key Distribution (QKD) with classical network infrastructures remains challenging due to the lack of end-to-end demonstrators that unify quantum key generation, classical post-processing, and secure network operation. This work presents a full-stack hybrid quantum-classical communication architecture that addresses this gap by combining E91 quantum key generation with supplementary Twin-Field QKD and Measurement-Device-Independent QKD central-node simulations, together with a rigorous classical post-processing pipeline comprising Low-Density Parity-Check (LDPC)-based information reconciliation, a Trevisan extractor for privacy amplification, and a dual-path session-key derivation architecture. The extractor-based Key Derivation Function (KDF) yields a fixed demonstration-scale key set, whereas the HKDF-SHA3-256 expansion pathway supports scalable multi-session key pools suitable for higher-throughput communication. These keys secure traffic in a hierarchical 6G-inspired NS-3 simulation that features Software-Defined Networking (SDN)-driven adaptive modulation, threshold-based anomaly detection, and a Flask + Socket.IO communication interface strengthened by QKD-backed authentication. Experimental evaluation showed 0% Quantum Bit Error Rate (QBER) under ideal conditions, an average QBER of 4-7% under injected noise, isolated spikes up to 9.32%, and a strict 5% abort threshold for key validity. Additional metrics include 100% reconciliation success, ≈ 1792-bit extractor outputs, ≈ 6 extractor-derived AES-256 session keys per valid run, substantially larger HKDF-derived key pools, and 3-12 ms encrypted-message latency. These results demonstrate the feasibility of directly coupling quantum-generated entropy into classical, secure communication pipelines, thereby offering a reproducible foundation for quantum-secure architectures in next-generation mission-critical networks.
Fields of Study & Subjects
Quantum Information and Cryptography
Quantum Mechanics and Applications
Quantum Computing Algorithms and Architecture
Publication details
- Publication date
- 5 January 2026
- Document type
- Preprint