Enhancing reflective elements of intelligent reflective surfaces in 6G communications using artificial intelligence.
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| Title: | Enhancing reflective elements of intelligent reflective surfaces in 6G communications using artificial intelligence. |
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| Authors: | Al-Safi, Jehan Kadhim Shareef1, Alsahlanee, Abbas Thajeel Rhaif2 abbas.thajeel@utq.edu.iq |
| Source: | Telkomnika. Feb2026, Vol. 24 Issue 1, p22-33. 12p. |
| Subjects: | Artificial intelligence, Reflective materials, Cost effectiveness of energy consumption, Communication infrastructure, Rayleigh fading channels, Particle swarm optimization, 6G networks, Electromagnetic wave propagation |
| Abstract: | The dynamic landscape of 6G communication networks necessitates innovative strategies to address energy inefficiency and signal degradation in densely populated regions with limited line-of-sight (LOS) coverage. A novel technology known as an intelligent reflecting surface (IRS) has emerged; it can dynamically modify the characteristics of electromagnetic waves to enhance signal propagation. Unfortunately, current IRS models frequently neglect the balance between energy efficiency (EE) and the quantity of reflective elements (N) in Rayleigh fading scenarios. This study introduces an algorithm called dynamic-static particle swarm optimization (DS-PSO) aimed at improving EE and decreasing the quantity of reflective components in the performance optimization of IRS. The research assesses the proposed model in comparison to single-input single-output (SISO) systems, conventional IRS models, and IRS models from prior studies within a realistic urban framework. The optimized IRS, which only uses seven reflective elements, has a peak EE of 366 Mbit/Joule. This is a big improvement over IRS models from earlier research, as shown by the numbers. The findings indicate that artificial intelligence (AI)-driven optimization can enhance IRS technology for sustainable and efficient 6G networks. [ABSTRACT FROM AUTHOR] |
| Copyright of Telkomnika is the property of Department of Electrical Engineering, Ahmad Dahlan University 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: 192065402 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Enhancing reflective elements of intelligent reflective surfaces in 6G communications using artificial intelligence. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Al-Safi%2C+Jehan+Kadhim+Shareef%22">Al-Safi, Jehan Kadhim Shareef</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Alsahlanee%2C+Abbas+Thajeel+Rhaif%22">Alsahlanee, Abbas Thajeel Rhaif</searchLink><relatesTo>2</relatesTo><i> abbas.thajeel@utq.edu.iq</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Telkomnika%22">Telkomnika</searchLink>. Feb2026, Vol. 24 Issue 1, p22-33. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Reflective+materials%22">Reflective materials</searchLink><br /><searchLink fieldCode="DE" term="%22Cost+effectiveness+of+energy+consumption%22">Cost effectiveness of energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Communication+infrastructure%22">Communication infrastructure</searchLink><br /><searchLink fieldCode="DE" term="%22Rayleigh+fading+channels%22">Rayleigh fading channels</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%226G+networks%22">6G networks</searchLink><br /><searchLink fieldCode="DE" term="%22Electromagnetic+wave+propagation%22">Electromagnetic wave propagation</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The dynamic landscape of 6G communication networks necessitates innovative strategies to address energy inefficiency and signal degradation in densely populated regions with limited line-of-sight (LOS) coverage. A novel technology known as an intelligent reflecting surface (IRS) has emerged; it can dynamically modify the characteristics of electromagnetic waves to enhance signal propagation. Unfortunately, current IRS models frequently neglect the balance between energy efficiency (EE) and the quantity of reflective elements (N) in Rayleigh fading scenarios. This study introduces an algorithm called dynamic-static particle swarm optimization (DS-PSO) aimed at improving EE and decreasing the quantity of reflective components in the performance optimization of IRS. The research assesses the proposed model in comparison to single-input single-output (SISO) systems, conventional IRS models, and IRS models from prior studies within a realistic urban framework. The optimized IRS, which only uses seven reflective elements, has a peak EE of 366 Mbit/Joule. This is a big improvement over IRS models from earlier research, as shown by the numbers. The findings indicate that artificial intelligence (AI)-driven optimization can enhance IRS technology for sustainable and efficient 6G networks. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Telkomnika is the property of Department of Electrical Engineering, Ahmad Dahlan University 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: 10.12928/TELKOMNIKA.v24i1.27307 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 22 Subjects: – SubjectFull: Artificial intelligence Type: general – SubjectFull: Reflective materials Type: general – SubjectFull: Cost effectiveness of energy consumption Type: general – SubjectFull: Communication infrastructure Type: general – SubjectFull: Rayleigh fading channels Type: general – SubjectFull: Particle swarm optimization Type: general – SubjectFull: 6G networks Type: general – SubjectFull: Electromagnetic wave propagation Type: general Titles: – TitleFull: Enhancing reflective elements of intelligent reflective surfaces in 6G communications using artificial intelligence. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Al-Safi, Jehan Kadhim Shareef – PersonEntity: Name: NameFull: Alsahlanee, Abbas Thajeel Rhaif IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 16936930 Numbering: – Type: volume Value: 24 – Type: issue Value: 1 Titles: – TitleFull: Telkomnika Type: main |
| ResultId | 1 |
