Sohaib, Rana Muhammad, Tariq Shah, Syed and Yadav, Poonam orcid.org/0000-0003-0169-0704 (2024) Towards Resilient 6G O-RAN:An Energy-Efficient URLLC Resource Allocation Framework. IEEE Open Journal of the Communications Society. pp. 7701-7714. ISSN 2644-125X
Abstract
The demands of ultra-reliable low-latency communication (URLLC) in "NextG"cellular networks necessitate innovative approaches for efficient resource utilization. The current literature on 6G O-RAN primarily addresses improved mobile broadband (eMBB) performance or URLLC latency optimization individually, often neglecting the intricate balance required to optimize both simultaneously under practical constraints. This paper addresses this gap by proposing a DRL-based resource allocation framework integrated with meta-learning to manage eMBB and URLLC services adaptively. Our approach efficiently allocates heterogeneous network resources, aiming to maximize energy efficiency (EE) while minimizing URLLC latency, even under varying environmental conditions. We highlight the critical importance of accurately estimating the traffic distribution flow in the multi-connectivity (MC) scenario, as its uncertainty can significantly degrade EE. The proposed framework demonstrates superior adaptability across different path loss models, outperforming traditional methods and paving the way for more resilient and efficient 6G networks.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Publisher Copyright: © 2024 The Authors. |
Keywords: | DRL,eMBB,O-RAN,resource allocation,URLLC |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Computer Science (York) |
Funding Information: | Funder Grant number DEPARTMENT FOR SCIENCE, INNOVATION AND TECHNOLOGY TS/Y008952/1 EPSRC EP/X040518/1 EPSRC EP/Y019229/1 |
Depositing User: | Pure (York) |
Date Deposited: | 21 Mar 2025 11:00 |
Last Modified: | 21 Mar 2025 11:00 |
Published Version: | https://doi.org/10.1109/OJCOMS.2024.3510273 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/OJCOMS.2024.3510273 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:224700 |
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