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Asia Communications and Photonics Conference

Dual-Agent-based Resource Allocation for Synergistic Transmission of Classical and Quantum Signals in Multi-Core Fiber Networks

Fengkai Sun, Yongmei Sun, Yaoxian Gao, Y J Wang

Published Nov 5, 2025• 0 citations
Publisher

Abstract

To address the challenge of synergistic transmission for classical and quantum signals in multi-core fiber networks, this paper proposes a synergistic dual-agent reinforcement learning resource allocation scheme (S-DARL) based on multi-agent reinforcement learning framework. Two cooperating agents adopted in this scheme allocate the spectrum and core resources for quantum and classical signals, which are enabled to propagate together under the constraints of physical layer noise to achieve efficient encrypted data transmission. Simulation results demonstrate that the proposed scheme significantly reduces the blocking probability and improves the overall network synergistic degree compared to previous state- of-the-art heuristic methods.

DOI
10.1109/acp66871.2025.11350803

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