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Article: Reconfigurable Intelligent Surface Aided NOMA Networks

TitleReconfigurable Intelligent Surface Aided NOMA Networks
Authors
KeywordsNOMA
passive beamforming
reconfigurable intelligent surface
Issue Date2020
Citation
IEEE Journal on Selected Areas in Communications, 2020, v. 38, n. 11, p. 2575-2588 How to Cite?
AbstractReconfigurable intelligent surfaces (RISs) constitute a promising performance enhancement for next-generation (NG) wireless networks in terms of enhancing both their spectral efficiency (SE) and energy efficiency (EE). We conceive a system for serving paired power-domain non-orthogonal multiple access (NOMA) users by designing the passive beamforming weights at the RISs. In an effort to evaluate the network performance, we first derive the best-case and worst-case of new channel statistics for characterizing the effective channel gains. Then, we derive the best-case and worst-case of our closed-form expressions derived both for the outage probability and for the ergodic rate of the prioritized user. For gleaning further insights, we investigate both the diversity orders of the outage probability and the high-signal-to-noise (SNR) slopes of the ergodic rate. We also derive both the SE and EE of the proposed network. Our analytical results demonstrate that the base station (BS)-user links have almost no impact on the diversity orders attained when the number of RISs is high enough. Numerical results are provided for confirming that: i) the high-SNR slope of the RIS-aided network is one; ii) the proposed RIS-aided NOMA network has superior network performance compared to its orthogonal counterpart.
Persistent Identifierhttp://hdl.handle.net/10722/350055
ISSN
2023 Impact Factor: 13.8
2023 SCImago Journal Rankings: 8.707

 

DC FieldValueLanguage
dc.contributor.authorHou, Tianwei-
dc.contributor.authorLiu, Yuanwei-
dc.contributor.authorSong, Zhengyu-
dc.contributor.authorSun, Xin-
dc.contributor.authorChen, Yue-
dc.contributor.authorHanzo, Lajos-
dc.date.accessioned2024-10-17T07:02:46Z-
dc.date.available2024-10-17T07:02:46Z-
dc.date.issued2020-
dc.identifier.citationIEEE Journal on Selected Areas in Communications, 2020, v. 38, n. 11, p. 2575-2588-
dc.identifier.issn0733-8716-
dc.identifier.urihttp://hdl.handle.net/10722/350055-
dc.description.abstractReconfigurable intelligent surfaces (RISs) constitute a promising performance enhancement for next-generation (NG) wireless networks in terms of enhancing both their spectral efficiency (SE) and energy efficiency (EE). We conceive a system for serving paired power-domain non-orthogonal multiple access (NOMA) users by designing the passive beamforming weights at the RISs. In an effort to evaluate the network performance, we first derive the best-case and worst-case of new channel statistics for characterizing the effective channel gains. Then, we derive the best-case and worst-case of our closed-form expressions derived both for the outage probability and for the ergodic rate of the prioritized user. For gleaning further insights, we investigate both the diversity orders of the outage probability and the high-signal-to-noise (SNR) slopes of the ergodic rate. We also derive both the SE and EE of the proposed network. Our analytical results demonstrate that the base station (BS)-user links have almost no impact on the diversity orders attained when the number of RISs is high enough. Numerical results are provided for confirming that: i) the high-SNR slope of the RIS-aided network is one; ii) the proposed RIS-aided NOMA network has superior network performance compared to its orthogonal counterpart.-
dc.languageeng-
dc.relation.ispartofIEEE Journal on Selected Areas in Communications-
dc.subjectNOMA-
dc.subjectpassive beamforming-
dc.subjectreconfigurable intelligent surface-
dc.titleReconfigurable Intelligent Surface Aided NOMA Networks-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/JSAC.2020.3007039-
dc.identifier.scopuseid_2-s2.0-85087524011-
dc.identifier.volume38-
dc.identifier.issue11-
dc.identifier.spage2575-
dc.identifier.epage2588-
dc.identifier.eissn1558-0008-

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