Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks
<p dir="ltr">This paper introduces a quantitative analytical framework for developing radio resource management (RRM) strategies tailored to 5G services of enhanced Mobile Broadband (eMBB) and ultra-Reliable Low Latency Communications (uRLLC). By leveraging the Open Radio Access Netw...
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2025
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| _version_ | 1864513523568082944 |
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| author | Tariq Mumtaz (10861635) |
| author2 | Shahabuddin Muhammad (23152507) Faouzi Bouali (23152510) |
| author2_role | author author |
| author_facet | Tariq Mumtaz (10861635) Shahabuddin Muhammad (23152507) Faouzi Bouali (23152510) |
| author_role | author |
| dc.creator.none.fl_str_mv | Tariq Mumtaz (10861635) Shahabuddin Muhammad (23152507) Faouzi Bouali (23152510) |
| dc.date.none.fl_str_mv | 2025-05-29T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2025.3575021 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Formal_Verification-_and_AI_ML-Assisted_Radio_Resource_Allocation_for_Open_RAN_Compliant_5G_6G_Networks/31289176 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Engineering Communications engineering Engineering practice and education Information and computing sciences Artificial intelligence Distributed computing and systems software Machine learning 5G RRM Open RAN Probabilistic model checking Machine learning |
| dc.title.none.fl_str_mv | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">This paper introduces a quantitative analytical framework for developing radio resource management (RRM) strategies tailored to 5G services of enhanced Mobile Broadband (eMBB) and ultra-Reliable Low Latency Communications (uRLLC). By leveraging the Open Radio Access Network (RAN) architecture, the framework enables flexible and efficient management of radio resources to meet the competing demands of services offered by the fifth/sixth generation (5G/6G) of wireless networks. The proposed RRM methodology incorporates formal verification capabilities to generate vast Pareto optimality datasets for specific RAN design parameters, establishing a foundation for rigorous RRM strategy selection. Additionally, the proposed approach enhances data-driven RRM decision-making through the application of unsupervised machine-learning techniques. Our proposed RRM methodology outperforms other baseline (i.e., stochastic and resource-proportional) RRM schemes, achieving up to 30% improvement in the 5G service reward.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License:<a href="https://creativecommons.org/licenses/by/4.0" rel="noreferrer" target="_blank"> https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3575021" target="_blank">https://dx.doi.org/10.1109/access.2025.3575021</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_e0bb759d8ebb68f1bbd68b878a234e4c |
| identifier_str_mv | 10.1109/access.2025.3575021 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/31289176 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G NetworksTariq Mumtaz (10861635)Shahabuddin Muhammad (23152507)Faouzi Bouali (23152510)EngineeringCommunications engineeringEngineering practice and educationInformation and computing sciencesArtificial intelligenceDistributed computing and systems softwareMachine learning5GRRMOpen RANProbabilistic model checkingMachine learning<p dir="ltr">This paper introduces a quantitative analytical framework for developing radio resource management (RRM) strategies tailored to 5G services of enhanced Mobile Broadband (eMBB) and ultra-Reliable Low Latency Communications (uRLLC). By leveraging the Open Radio Access Network (RAN) architecture, the framework enables flexible and efficient management of radio resources to meet the competing demands of services offered by the fifth/sixth generation (5G/6G) of wireless networks. The proposed RRM methodology incorporates formal verification capabilities to generate vast Pareto optimality datasets for specific RAN design parameters, establishing a foundation for rigorous RRM strategy selection. Additionally, the proposed approach enhances data-driven RRM decision-making through the application of unsupervised machine-learning techniques. Our proposed RRM methodology outperforms other baseline (i.e., stochastic and resource-proportional) RRM schemes, achieving up to 30% improvement in the 5G service reward.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License:<a href="https://creativecommons.org/licenses/by/4.0" rel="noreferrer" target="_blank"> https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3575021" target="_blank">https://dx.doi.org/10.1109/access.2025.3575021</a></p>2025-05-29T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2025.3575021https://figshare.com/articles/journal_contribution/Formal_Verification-_and_AI_ML-Assisted_Radio_Resource_Allocation_for_Open_RAN_Compliant_5G_6G_Networks/31289176CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/312891762025-05-29T03:00:00Z |
| spellingShingle | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks Tariq Mumtaz (10861635) Engineering Communications engineering Engineering practice and education Information and computing sciences Artificial intelligence Distributed computing and systems software Machine learning 5G RRM Open RAN Probabilistic model checking Machine learning |
| status_str | publishedVersion |
| title | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| title_full | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| title_fullStr | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| title_full_unstemmed | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| title_short | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| title_sort | Formal Verification- and AI/ML-Assisted Radio Resource Allocation for Open RAN Compliant 5G/6G Networks |
| topic | Engineering Communications engineering Engineering practice and education Information and computing sciences Artificial intelligence Distributed computing and systems software Machine learning 5G RRM Open RAN Probabilistic model checking Machine learning |