Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/10090
DC FieldValueLanguage
dc.contributor.authorLiang, Weiqianen_US
dc.contributor.authorAbdrabou, Atefen_US
dc.contributor.authorOrumwense, Efe Francisen_US
dc.contributor.authorMadsen, Dag Øivinden_US
dc.date.accessioned2025-09-23T09:02:27Z-
dc.date.available2025-09-23T09:02:27Z-
dc.date.issued2024-
dc.identifier.citationLiang, W. et al. 2024. An efficient algorithm for resource optimization in IRS-mmWave-NOMA B5G wireless networks. Heliyon, 10(3): 1-16. [https://doi.org/10.1016/j.heliyon.2024.e25107]en_US
dc.identifier.issn2405-8440 (Online)-
dc.identifier.urihttp://hdl.handle.net/11189/10090-
dc.description.abstractThe effectiveness of implementing intelligent reflecting surface (IRS) for millimeter-wave (mmWave)-non-orthogonal multiple-access (NOMA) systems has allowed for significant sum-rate improvements. The majority of recent research has not discussed how well the IRS-mmWave-NOMA combination performs. Therefore, a new technique for resource optimization in IRS-mmWave-NOMA B5G wireless networks is proposed in this research. The key concept is to use an iterative algorithm to solve the optimization issue while incorporating many crucial constraints like the selection of the IRS beam, transmit power distribution, and decoding order, among others. Simulation results show that the proposed approach outperforms existing state-of-the-art algorithms in terms of computation delay, sum rate and NMSE. The computational complexity also validated the simplicity and hardware-friendly feature of the proposed algorithm.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofHeliyonen_US
dc.subjectB5G networksen_US
dc.subjectmmWave communicationen_US
dc.subjectResource optimizationen_US
dc.subjectNOMAen_US
dc.subjectIRSen_US
dc.titleAn efficient algorithm for resource optimization in IRS-mmWave-NOMA B5G wireless networksen_US
dc.identifier.doihttps://doi.org/10.1016/j.heliyon.2024.e25107-
dc.typeArticleen_US
Appears in Collections:Eng - Journal articles (DHET subsidised)
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