Radio Resource Management for Intelligent Neutral Host (INH) in Multi-Operator Environments
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| Názov: | Radio Resource Management for Intelligent Neutral Host (INH) in Multi-Operator Environments |
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| Autori: | Hojjat Navidan, Mostafa Naseri, Ingrid Moerman, Adnan Shahid |
| Zdroj: | IEEE Open Journal of the Communications Society, Vol 5, Pp 1975-1986 (2024) IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY IEEE Open Journal of the Communications Society |
| Informácie o vydavateľovi: | Institute of Electrical and Electronics Engineers (IEEE), 2024. |
| Rok vydania: | 2024 |
| Predmety: | 0301 basic medicine, reinforcement learning, 0303 health sciences, Technology and Engineering, O-RAN, multi-operator core network, service level agreement, TK5101-6720, ALLOCATION, radio resource management, 03 medical and health sciences, FUTURE, Intelligent neutral host, Q-learning, Telecommunication, deep Q-learning, Transportation and communications, 5G, HE1-9990 |
| Popis: | In the era of fifth-generation (5G) cellular networks and beyond, network sharing has emerged as a promising approach to address the escalating demand for spectrum and infrastructure resources. Intelligent Neutral Host (INH) is an advanced network-sharing method facilitated by Open Radio Access Network (O-RAN) capabilities. This paper addresses the challenge of Radio Resource Management (RRM) in a multi-operator, multi-slice scenario. We propose an algorithm based on Q-learning and deep Q-learning, particularly concerning different Physical Resource Block (PRB) types to cater to diverse operator requirements. Implemented as an xApp on the Colosseum platform, our algorithm introduces a dynamic resource allocation strategy that adheres to Service Level Agreement (SLA) constraints and optimizes real-time Key Performance metrics (KPMs), including throughput, buffer occupancy, and PRB utilization. We assess the performance and efficacy of our algorithm in a complex traffic scenario to demonstrate how it effectively allocates resources among operators’ slices to satisfy their respective SLA while ensuring optimal resource utilization. The experimental results show that our proposed algorithm can efficiently allocate resources to individual slices while satisfying the SLA. Compared to traditional algorithms, our approach significantly minimizes SLA violations, reducing them to 2.5% for enhanced Mobile Broadband (eMBB) slices and eliminating them entirely for Ultra-Reliable Low-Latency Communications (URLLC) slices. |
| Druh dokumentu: | Article |
| Popis súboru: | application/pdf |
| ISSN: | 2644-125X |
| DOI: | 10.1109/ojcoms.2024.3380517 |
| Prístupová URL adresa: | https://doaj.org/article/44f4a9c4b9dd45b8ba32d137db3dbdf2 https://biblio.ugent.be/publication/01HWWRFCMGG8ZAWKDV7RJK1E96 http://doi.org/10.1109/OJCOMS.2024.3380517 https://biblio.ugent.be/publication/01HWWRFCMGG8ZAWKDV7RJK1E96/file/01HWWRGT2Q64E37NFAD7RZ5HRQ http://hdl.handle.net/1854/LU-01HWWRFCMGG8ZAWKDV7RJK1E96 |
| Rights: | CC BY |
| Prístupové číslo: | edsair.doi.dedup.....829f9e0824d0b61c1b08e25a8c87e110 |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | In the era of fifth-generation (5G) cellular networks and beyond, network sharing has emerged as a promising approach to address the escalating demand for spectrum and infrastructure resources. Intelligent Neutral Host (INH) is an advanced network-sharing method facilitated by Open Radio Access Network (O-RAN) capabilities. This paper addresses the challenge of Radio Resource Management (RRM) in a multi-operator, multi-slice scenario. We propose an algorithm based on Q-learning and deep Q-learning, particularly concerning different Physical Resource Block (PRB) types to cater to diverse operator requirements. Implemented as an xApp on the Colosseum platform, our algorithm introduces a dynamic resource allocation strategy that adheres to Service Level Agreement (SLA) constraints and optimizes real-time Key Performance metrics (KPMs), including throughput, buffer occupancy, and PRB utilization. We assess the performance and efficacy of our algorithm in a complex traffic scenario to demonstrate how it effectively allocates resources among operators’ slices to satisfy their respective SLA while ensuring optimal resource utilization. The experimental results show that our proposed algorithm can efficiently allocate resources to individual slices while satisfying the SLA. Compared to traditional algorithms, our approach significantly minimizes SLA violations, reducing them to 2.5% for enhanced Mobile Broadband (eMBB) slices and eliminating them entirely for Ultra-Reliable Low-Latency Communications (URLLC) slices. |
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| ISSN: | 2644125X |
| DOI: | 10.1109/ojcoms.2024.3380517 |