Improved channel quality indicator estimation using extended Kalman filter in LTE networks under diverse mobility models.
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| Title: | Improved channel quality indicator estimation using extended Kalman filter in LTE networks under diverse mobility models. |
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| Authors: | Ezea, Hilary U.1 hilary.ezea@fuoye.edu.ng, Ahaneku, Mamilus A.2 mamilus.ahaneku@unn.edu.ng, Chijindu, Vincent C.2 vincent.chijindu@unn.edu.ng, Ezeja, Obinna M.2 obinna.ezeja@unn.edu.ng, Nwawelu, Udora N.2 nwabuoku.nwawelu@unn.edu.ng |
| Source: | Telkomnika. Oct2025, Vol. 23 Issue 5, p1166-1176. 11p. |
| Subjects: | Long-Term Evolution (Telecommunications), Channel estimation, Resource allocation, Kalman filtering, Mobility (Structural dynamics), Signal-to-noise ratio |
| Abstract: | Accurate channel quality indicator (CQI) estimation is crucial for optimizing resource allocation, improving link adaptation, and sustaining high performance in long term evolution (LTE) networks. In real-world scenarios, where channel conditions fluctuate rapidly due to user mobility, inaccurate CQI estimation can lead to suboptimal scheduling, degraded throughput, and reduced quality of service (QoS) for both users and network operators. Traditional Kalman filter (KF) approaches often struggle with the non-linear and time-varying nature of wireless channels, especially under unpredictable mobility patterns. This paper proposes an improved CQI estimation method based on the extended Kalman filter (EKF), which models non-linear system dynamics more effectively. The method is implemented in LTE-Sim, analyzed using MATLAB, and evaluated under random and Manhattan mobility models. Results show that across mobility regimes, KF outperforms EKF in the structured Manhattan model, while in the non-linear randomdirection model, EKF yields markedly higher signal-to-interference-plusnoise ratio (SINR) stability and robustness to channel variation with SINR values above 10 dB between 300-450 s and a peak of approximately 60 dB. These results underscore the importance of mobility-aware estimation strategies in enhancing LTE network adaptability and throughput. [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: 188641859 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Improved channel quality indicator estimation using extended Kalman filter in LTE networks under diverse mobility models. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ezea%2C+Hilary+U%2E%22">Ezea, Hilary U.</searchLink><relatesTo>1</relatesTo><i> hilary.ezea@fuoye.edu.ng</i><br /><searchLink fieldCode="AR" term="%22Ahaneku%2C+Mamilus+A%2E%22">Ahaneku, Mamilus A.</searchLink><relatesTo>2</relatesTo><i> mamilus.ahaneku@unn.edu.ng</i><br /><searchLink fieldCode="AR" term="%22Chijindu%2C+Vincent+C%2E%22">Chijindu, Vincent C.</searchLink><relatesTo>2</relatesTo><i> vincent.chijindu@unn.edu.ng</i><br /><searchLink fieldCode="AR" term="%22Ezeja%2C+Obinna+M%2E%22">Ezeja, Obinna M.</searchLink><relatesTo>2</relatesTo><i> obinna.ezeja@unn.edu.ng</i><br /><searchLink fieldCode="AR" term="%22Nwawelu%2C+Udora+N%2E%22">Nwawelu, Udora N.</searchLink><relatesTo>2</relatesTo><i> nwabuoku.nwawelu@unn.edu.ng</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Telkomnika%22">Telkomnika</searchLink>. Oct2025, Vol. 23 Issue 5, p1166-1176. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Long-Term+Evolution+%28Telecommunications%29%22">Long-Term Evolution (Telecommunications)</searchLink><br /><searchLink fieldCode="DE" term="%22Channel+estimation%22">Channel estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink><br /><searchLink fieldCode="DE" term="%22Mobility+%28Structural+dynamics%29%22">Mobility (Structural dynamics)</searchLink><br /><searchLink fieldCode="DE" term="%22Signal-to-noise+ratio%22">Signal-to-noise ratio</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Accurate channel quality indicator (CQI) estimation is crucial for optimizing resource allocation, improving link adaptation, and sustaining high performance in long term evolution (LTE) networks. In real-world scenarios, where channel conditions fluctuate rapidly due to user mobility, inaccurate CQI estimation can lead to suboptimal scheduling, degraded throughput, and reduced quality of service (QoS) for both users and network operators. Traditional Kalman filter (KF) approaches often struggle with the non-linear and time-varying nature of wireless channels, especially under unpredictable mobility patterns. This paper proposes an improved CQI estimation method based on the extended Kalman filter (EKF), which models non-linear system dynamics more effectively. The method is implemented in LTE-Sim, analyzed using MATLAB, and evaluated under random and Manhattan mobility models. Results show that across mobility regimes, KF outperforms EKF in the structured Manhattan model, while in the non-linear randomdirection model, EKF yields markedly higher signal-to-interference-plusnoise ratio (SINR) stability and robustness to channel variation with SINR values above 10 dB between 300-450 s and a peak of approximately 60 dB. These results underscore the importance of mobility-aware estimation strategies in enhancing LTE network adaptability and throughput. [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.v23i5.27205 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 1166 Subjects: – SubjectFull: Long-Term Evolution (Telecommunications) Type: general – SubjectFull: Channel estimation Type: general – SubjectFull: Resource allocation Type: general – SubjectFull: Kalman filtering Type: general – SubjectFull: Mobility (Structural dynamics) Type: general – SubjectFull: Signal-to-noise ratio Type: general Titles: – TitleFull: Improved channel quality indicator estimation using extended Kalman filter in LTE networks under diverse mobility models. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ezea, Hilary U. – PersonEntity: Name: NameFull: Ahaneku, Mamilus A. – PersonEntity: Name: NameFull: Chijindu, Vincent C. – PersonEntity: Name: NameFull: Ezeja, Obinna M. – PersonEntity: Name: NameFull: Nwawelu, Udora N. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 10 Text: Oct2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 16936930 Numbering: – Type: volume Value: 23 – Type: issue Value: 5 Titles: – TitleFull: Telkomnika Type: main |
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