File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: STAR-RIS Aided NOMA in Multicell Networks: A General Analytical Framework With Gamma Distributed Channel Modeling

TitleSTAR-RIS Aided NOMA in Multicell Networks: A General Analytical Framework With Gamma Distributed Channel Modeling
Authors
KeywordsMulti-cell networks
non-orthogonal multiple access
reconfigurable intelligent surface
simultaneous transmission and reflection
stochastic geometry
Issue Date2022
Citation
IEEE Transactions on Communications, 2022, v. 70, n. 8, p. 5629-5644 How to Cite?
AbstractThe simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that optimal energy splitting coefficients of STAR-RISs exist to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located on different sides; 2) STAR-RISs with appropriate energy splitting coefficients outperform conventional RISs in the coverage and the rate performance.
Persistent Identifierhttp://hdl.handle.net/10722/349745
ISSN
2023 Impact Factor: 7.2
2020 SCImago Journal Rankings: 1.468

 

DC FieldValueLanguage
dc.contributor.authorXie, Ziyi-
dc.contributor.authorYi, Wenqiang-
dc.contributor.authorWu, Xuanli-
dc.contributor.authorLiu, Yuanwei-
dc.contributor.authorNallanathan, Arumugam-
dc.date.accessioned2024-10-17T07:00:32Z-
dc.date.available2024-10-17T07:00:32Z-
dc.date.issued2022-
dc.identifier.citationIEEE Transactions on Communications, 2022, v. 70, n. 8, p. 5629-5644-
dc.identifier.issn0090-6778-
dc.identifier.urihttp://hdl.handle.net/10722/349745-
dc.description.abstractThe simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is capable of providing full-space coverage of smart radio environments. This work investigates STAR-RIS aided downlink non-orthogonal multiple access (NOMA) multi-cell networks, where the energy of incident signals at STAR-RISs is split into two portions for transmitting and reflecting. We first propose a fitting method to model the distribution of composite small-scale fading power as the tractable Gamma distribution. Then, a unified analytical framework based on stochastic geometry is provided to capture the random locations of RIS-RISs, base stations (BSs), and user equipments (UEs). Based on this framework, we derive the coverage probability and ergodic rate of both the typical UE and the connected UE. In particular, we obtain closed-form expressions of the coverage probability in interference-limited scenarios. We also deduce theoretical expressions in conventional RIS aided networks for comparison. The analytical results show that optimal energy splitting coefficients of STAR-RISs exist to simultaneously maximize the system coverage and ergodic rate. The numerical results demonstrate that: 1) STAR-RISs are able to meet different demands of UEs located on different sides; 2) STAR-RISs with appropriate energy splitting coefficients outperform conventional RISs in the coverage and the rate performance.-
dc.languageeng-
dc.relation.ispartofIEEE Transactions on Communications-
dc.subjectMulti-cell networks-
dc.subjectnon-orthogonal multiple access-
dc.subjectreconfigurable intelligent surface-
dc.subjectsimultaneous transmission and reflection-
dc.subjectstochastic geometry-
dc.titleSTAR-RIS Aided NOMA in Multicell Networks: A General Analytical Framework With Gamma Distributed Channel Modeling-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TCOMM.2022.3186409-
dc.identifier.scopuseid_2-s2.0-85133591273-
dc.identifier.volume70-
dc.identifier.issue8-
dc.identifier.spage5629-
dc.identifier.epage5644-
dc.identifier.eissn1558-0857-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats