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Efficient Massive MIMO Detection for M-QAM Symbols
Massive multiple-input multiple-output (MIMO) systems significantly outperform small-scale MIMO systems in terms of data rate, making them an enabling technology for next-generation wireless systems. However, the increased number of antennas increases the computational difficulty of data detection,...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047872/ https://www.ncbi.nlm.nih.gov/pubmed/36981280 http://dx.doi.org/10.3390/e25030391 |
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author | Quan, Zhi Luo, Jiyu Zhang, Hailong Jiang, Li |
author_facet | Quan, Zhi Luo, Jiyu Zhang, Hailong Jiang, Li |
author_sort | Quan, Zhi |
collection | PubMed |
description | Massive multiple-input multiple-output (MIMO) systems significantly outperform small-scale MIMO systems in terms of data rate, making them an enabling technology for next-generation wireless systems. However, the increased number of antennas increases the computational difficulty of data detection, necessitating more efficient detection techniques. This paper presents a detector based on joint deregularized and box-constrained dichotomous coordinate descent (BOXDCD) with iterations for rectangular m-ary quadrature amplitude modulation (M-QAM) symbols. Deregularization maximized the energy of the solution. With the box-constraint, the deregularization forces the solution to be close to the rectangular boundary set. The numerical results demonstrate that the proposed detector achieves a considerable performance gain compared to existing detection algorithms. The performance advantage increases with the system size and signal-to-noise ratio. |
format | Online Article Text |
id | pubmed-10047872 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100478722023-03-29 Efficient Massive MIMO Detection for M-QAM Symbols Quan, Zhi Luo, Jiyu Zhang, Hailong Jiang, Li Entropy (Basel) Article Massive multiple-input multiple-output (MIMO) systems significantly outperform small-scale MIMO systems in terms of data rate, making them an enabling technology for next-generation wireless systems. However, the increased number of antennas increases the computational difficulty of data detection, necessitating more efficient detection techniques. This paper presents a detector based on joint deregularized and box-constrained dichotomous coordinate descent (BOXDCD) with iterations for rectangular m-ary quadrature amplitude modulation (M-QAM) symbols. Deregularization maximized the energy of the solution. With the box-constraint, the deregularization forces the solution to be close to the rectangular boundary set. The numerical results demonstrate that the proposed detector achieves a considerable performance gain compared to existing detection algorithms. The performance advantage increases with the system size and signal-to-noise ratio. MDPI 2023-02-21 /pmc/articles/PMC10047872/ /pubmed/36981280 http://dx.doi.org/10.3390/e25030391 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Quan, Zhi Luo, Jiyu Zhang, Hailong Jiang, Li Efficient Massive MIMO Detection for M-QAM Symbols |
title | Efficient Massive MIMO Detection for M-QAM Symbols |
title_full | Efficient Massive MIMO Detection for M-QAM Symbols |
title_fullStr | Efficient Massive MIMO Detection for M-QAM Symbols |
title_full_unstemmed | Efficient Massive MIMO Detection for M-QAM Symbols |
title_short | Efficient Massive MIMO Detection for M-QAM Symbols |
title_sort | efficient massive mimo detection for m-qam symbols |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10047872/ https://www.ncbi.nlm.nih.gov/pubmed/36981280 http://dx.doi.org/10.3390/e25030391 |
work_keys_str_mv | AT quanzhi efficientmassivemimodetectionformqamsymbols AT luojiyu efficientmassivemimodetectionformqamsymbols AT zhanghailong efficientmassivemimodetectionformqamsymbols AT jiangli efficientmassivemimodetectionformqamsymbols |