Multi-Agent DRL for QKD-Enabled Resource Allocation in 6G TN-NTN Metaverse Service
Seid, Abegaz Mohammed Abishu, Hayla Nahom Dharejo, Fayaz Ali Erbad, Aiman Hamdi, Mounir Guizani, Mohsen
Seid, Abegaz Mohammed
Abishu, Hayla Nahom
Dharejo, Fayaz Ali
Erbad, Aiman
Hamdi, Mounir
Guizani, Mohsen
Supervisor
Department
Machine Learning
Embargo End Date
Type
Conference proceeding
Date
2025
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Language
English
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Abstract
The integration of terrestrial and non-terrestrial networks (TN-NTN) in 6 G is essential to support real-time applications like the Metaverse and intelligent edge services, which demand ultra-reliable low-latency communications (xURLLC). Managing these networks and maintaining robust security presents significant challenges due to their complexity and high-dimensional environments. Quantum communication, particularly quantum key distribution (QKD), offers a promising solution by providing unbreakable encryption and enhancing security across TN-NTN architectures. In this paper, we propose a novel deep reinforcement learning approach for QKD-enabled resource allocation in 6 G TN-NTN Metaverse service and transform the joint resource allocation and QKD deployment cost optimization problem into a stochastic game model to ensure secure and efficient resource distribution across TN-NTN environment. We introduce a novel hierarchical multi-agent proximal policy optimization (MAPPO) framework to address the formulated optimization problem. This framework enables dynamic and secure allocation of Metaverse resources and services from multiple providers to users while minimizing QKD deployment costs. Our simulations demonstrate that the proposed framework significantly enhances network performance, reduces key generation costs, and optimizes resource utilization and service quality.
Citation
Seid, Abegaz Mohammed
Abishu, Hayla Nahom
Dharejo, Fayaz Ali
Erbad, Aiman
Hamdi, Mounir
Guizani, Mohsen
Abishu, Hayla Nahom
Dharejo, Fayaz Ali
Erbad, Aiman
Hamdi, Mounir
Guizani, Mohsen
Source
Proceedings of the ICC 2025-IEEE International Conference on Communications
Conference
ICC 2025-IEEE International Conference on Communications
Keywords
Metaverse, TN-NTN, Quantum communication, QKD, MAPPO
Subjects
Source
ICC 2025-IEEE International Conference on Communications
Publisher
IEEE