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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,...

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Detalles Bibliográficos
Autores principales: Quan, Zhi, Luo, Jiyu, Zhang, Hailong, Jiang, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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.
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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
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