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Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems
Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The prop...
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/PMC10255352/ https://www.ncbi.nlm.nih.gov/pubmed/37299740 http://dx.doi.org/10.3390/s23115014 |
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author | Huang, Xinyu Wang, Yubo Chen, Shiyong Li, Yan Wu, Yucheng |
author_facet | Huang, Xinyu Wang, Yubo Chen, Shiyong Li, Yan Wu, Yucheng |
author_sort | Huang, Xinyu |
collection | PubMed |
description | Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity. |
format | Online Article Text |
id | pubmed-10255352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102553522023-06-10 Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems Huang, Xinyu Wang, Yubo Chen, Shiyong Li, Yan Wu, Yucheng Sensors (Basel) Article Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity. MDPI 2023-05-23 /pmc/articles/PMC10255352/ /pubmed/37299740 http://dx.doi.org/10.3390/s23115014 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 Huang, Xinyu Wang, Yubo Chen, Shiyong Li, Yan Wu, Yucheng Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title | Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title_full | Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title_fullStr | Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title_full_unstemmed | Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title_short | Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems |
title_sort | joint user clustering and graph coloring based pilot assignment for cell-free massive mimo systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10255352/ https://www.ncbi.nlm.nih.gov/pubmed/37299740 http://dx.doi.org/10.3390/s23115014 |
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