Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning.
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| Title: | Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning. |
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| Authors: | Al-Shaeli, Intisar1 intisark302@uowasit.edu.iq, Hburi, Ismail Sharhan1 isharhan@uowasit.edu.iq, Majeed, Ammar A.1 ammara302@uowasit.edu.iq |
| Source: | International Journal of Electrical & Computer Engineering (2088-8708). Feb2023, Vol. 13 Issue 1, p493-501. 9p. |
| Subjects: | Multiuser computer systems, Beamforming, Semidefinite programming, Antennas (Electronics), Computer systems |
| Abstract: | Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 160447184 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Al-Shaeli%2C+Intisar%22">Al-Shaeli, Intisar</searchLink><relatesTo>1</relatesTo><i> intisark302@uowasit.edu.iq</i><br /><searchLink fieldCode="AR" term="%22Hburi%2C+Ismail+Sharhan%22">Hburi, Ismail Sharhan</searchLink><relatesTo>1</relatesTo><i> isharhan@uowasit.edu.iq</i><br /><searchLink fieldCode="AR" term="%22Majeed%2C+Ammar+A%2E%22">Majeed, Ammar A.</searchLink><relatesTo>1</relatesTo><i> ammara302@uowasit.edu.iq</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Electrical+%26+Computer+Engineering+%282088-8708%29%22">International Journal of Electrical & Computer Engineering (2088-8708)</searchLink>. Feb2023, Vol. 13 Issue 1, p493-501. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Multiuser+computer+systems%22">Multiuser computer systems</searchLink><br /><searchLink fieldCode="DE" term="%22Beamforming%22">Beamforming</searchLink><br /><searchLink fieldCode="DE" term="%22Semidefinite+programming%22">Semidefinite programming</searchLink><br /><searchLink fieldCode="DE" term="%22Antennas+%28Electronics%29%22">Antennas (Electronics)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Reconfigurable intelligent surfaces (RIS) is a wireless technology that has the potential to improve cellular communication systems significantly. This paper considers enhancing the RIS beamforming in a RIS-aided multiuser multi-input multi-output (MIMO) system to enhance user throughput in cellular networks. The study offers an unsupervised/deep neural network (U/DNN) that simultaneously optimizes the intelligent surface beamforming with less complexity to overcome the non-convex sum-rate problem difficulty. The numerical outcomes comparing the suggested approach to the near-optimal iterative semi-definite programming strategy indicate that the proposed method retains most performance (more than 95% of optimal throughput value when the number of antennas is 4 and RIS’s elements are 30) while drastically reducing system computing complexity. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Electrical & Computer Engineering (2088-8708) is the property of Institute of Advanced Engineering & Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.11591/ijece.v13i1.pp493-501 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 493 Subjects: – SubjectFull: Multiuser computer systems Type: general – SubjectFull: Beamforming Type: general – SubjectFull: Semidefinite programming Type: general – SubjectFull: Antennas (Electronics) Type: general – SubjectFull: Computer systems Type: general Titles: – TitleFull: Reconfigurable intelligent surface passive beamforming enhancement using unsupervised learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Al-Shaeli, Intisar – PersonEntity: Name: NameFull: Hburi, Ismail Sharhan – PersonEntity: Name: NameFull: Majeed, Ammar A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 20888708 Numbering: – Type: volume Value: 13 – Type: issue Value: 1 Titles: – TitleFull: International Journal of Electrical & Computer Engineering (2088-8708) Type: main |
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