Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework
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 latenc...
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| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of the Communications Society |
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| Online Access: | https://ieeexplore.ieee.org/document/10772596/ |
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| author | Rana Muhammad Sohaib Syed Tariq Shah Poonam Yadav |
| author_facet | Rana Muhammad Sohaib Syed Tariq Shah Poonam Yadav |
| author_sort | Rana Muhammad Sohaib |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d9e4aad0361c43cb9add00c484225b9b |
| institution | Kabale University |
| issn | 2644-125X |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of the Communications Society |
| spelling | doaj-art-d9e4aad0361c43cb9add00c484225b9b2024-12-14T00:02:06ZengIEEEIEEE Open Journal of the Communications Society2644-125X2024-01-0157701771410.1109/OJCOMS.2024.351027310772596Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation FrameworkRana Muhammad Sohaib0https://orcid.org/0000-0002-5132-2654Syed Tariq Shah1https://orcid.org/0000-0003-4722-1786Poonam Yadav2https://orcid.org/0000-0003-0169-0704Department of CS, University of York, York, U.K.School of Computer Science and Electronic Engineering, University of Essex, Colchester, U.K.Department of CS, University of York, York, U.K.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.https://ieeexplore.ieee.org/document/10772596/eMBBDRLURLLCresource allocationO-RAN |
| spellingShingle | Rana Muhammad Sohaib Syed Tariq Shah Poonam Yadav Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework IEEE Open Journal of the Communications Society eMBB DRL URLLC resource allocation O-RAN |
| title | Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework |
| title_full | Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework |
| title_fullStr | Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework |
| title_full_unstemmed | Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework |
| title_short | Towards Resilient 6G O-RAN: An Energy-Efficient URLLC Resource Allocation Framework |
| title_sort | towards resilient 6g o ran an energy efficient urllc resource allocation framework |
| topic | eMBB DRL URLLC resource allocation O-RAN |
| url | https://ieeexplore.ieee.org/document/10772596/ |
| work_keys_str_mv | AT ranamuhammadsohaib towardsresilient6gorananenergyefficienturllcresourceallocationframework AT syedtariqshah towardsresilient6gorananenergyefficienturllcresourceallocationframework AT poonamyadav towardsresilient6gorananenergyefficienturllcresourceallocationframework |