Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares
In large-scale massive MIMO systems with intelligent reflecting surfaces (IRS), dynamic channel estimation (CE) is essential for optimizing the system performance and ensuring reliable communication. Traditional channel estimation techniques are not suitable for IRS-assisted systems due to the uniqu...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Ain Shams Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447924004180 |
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| author | E. Elakkiyachelvan R.J. Kavitha |
| author_facet | E. Elakkiyachelvan R.J. Kavitha |
| author_sort | E. Elakkiyachelvan |
| collection | DOAJ |
| description | In large-scale massive MIMO systems with intelligent reflecting surfaces (IRS), dynamic channel estimation (CE) is essential for optimizing the system performance and ensuring reliable communication. Traditional channel estimation techniques are not suitable for IRS-assisted systems due to the unique characteristics of Intelligent Reflecting Surfaces channels. To address the channel estimation problem in such dynamic environments, this paper introduces two novel channel estimation methods: Khatri-Rao Factorization (KRF) and Bilinear Alternating Least Squares (BALS). The first method uses KRF to efficiently solve rank-1 matrix approximation problems with a closed-form solution. The second method employs an iterative alternating estimation scheme. By disentangling these key channel matrices’ estimates, both methods provide more accurate and robust channel estimation, essential for optimizing communication system performance in challenging environments. The proposed CE-KRF-BALS-MIMO method is evaluated under performance metrics like Bit error rate (BER), Signal Noise Ratio (SNR), Normalized Mean Square Error (NMSE) Spectral Efficiency (SE), and Computational Complexity. |
| format | Article |
| id | doaj-art-32031cd2a8d64d0782d828150234b8c7 |
| institution | Kabale University |
| issn | 2090-4479 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj-art-32031cd2a8d64d0782d828150234b8c72024-11-18T04:32:58ZengElsevierAin Shams Engineering Journal2090-44792024-11-011511103043Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squaresE. Elakkiyachelvan0R.J. Kavitha1Department of Electronics and Communication Engineering, University College of Engineering,Thirukkuvalai, Nagapattinam, District. Nearest Railway Station, Thiruvarur 610204, India; Corresponding author.Department of Electronics and Communication Engineering, University College of Engineering Panruti, Chennai Kumbakkonam Highway, Panikankuppam, Panruti 607106, IndiaIn large-scale massive MIMO systems with intelligent reflecting surfaces (IRS), dynamic channel estimation (CE) is essential for optimizing the system performance and ensuring reliable communication. Traditional channel estimation techniques are not suitable for IRS-assisted systems due to the unique characteristics of Intelligent Reflecting Surfaces channels. To address the channel estimation problem in such dynamic environments, this paper introduces two novel channel estimation methods: Khatri-Rao Factorization (KRF) and Bilinear Alternating Least Squares (BALS). The first method uses KRF to efficiently solve rank-1 matrix approximation problems with a closed-form solution. The second method employs an iterative alternating estimation scheme. By disentangling these key channel matrices’ estimates, both methods provide more accurate and robust channel estimation, essential for optimizing communication system performance in challenging environments. The proposed CE-KRF-BALS-MIMO method is evaluated under performance metrics like Bit error rate (BER), Signal Noise Ratio (SNR), Normalized Mean Square Error (NMSE) Spectral Efficiency (SE), and Computational Complexity.http://www.sciencedirect.com/science/article/pii/S2090447924004180Bilinear Alternating Least SquaresChannel estimationKhatri-Rao FactorizationMIMOIntelligent Reflecting Surface |
| spellingShingle | E. Elakkiyachelvan R.J. Kavitha Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares Ain Shams Engineering Journal Bilinear Alternating Least Squares Channel estimation Khatri-Rao Factorization MIMO Intelligent Reflecting Surface |
| title | Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares |
| title_full | Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares |
| title_fullStr | Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares |
| title_full_unstemmed | Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares |
| title_short | Dynamic channel estimation in large-scale massive MIMO systems with intelligent reflecting surfaces: Leveraging Khatri-Rao factorization and bilinear alternating least squares |
| title_sort | dynamic channel estimation in large scale massive mimo systems with intelligent reflecting surfaces leveraging khatri rao factorization and bilinear alternating least squares |
| topic | Bilinear Alternating Least Squares Channel estimation Khatri-Rao Factorization MIMO Intelligent Reflecting Surface |
| url | http://www.sciencedirect.com/science/article/pii/S2090447924004180 |
| work_keys_str_mv | AT eelakkiyachelvan dynamicchannelestimationinlargescalemassivemimosystemswithintelligentreflectingsurfacesleveragingkhatriraofactorizationandbilinearalternatingleastsquares AT rjkavitha dynamicchannelestimationinlargescalemassivemimosystemswithintelligentreflectingsurfacesleveragingkhatriraofactorizationandbilinearalternatingleastsquares |