The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
L'une des technologies clés du système de communication mobile de cinquième génération (5G) est le MIMO (massive multiple-input multiple-output) qui applique la formation de faisceaux afin de compenser efficacement les pertes de propagation importantes dans les bandes de hautes fréquences et de permettre le multiplexage spatial d'un système de communication mobile de cinquième génération (XNUMXG). un grand nombre de flux de signaux sur plusieurs utilisateurs. Pour améliorer encore le débit du système, un système de cluster coordonné dans lequel un grand nombre de stations de base MIMO massives sont déployées à haute densité a été étudié. Le déploiement dense améliore considérablement la capacité du système en contrôlant les stations de base à partir d'une unité de bande de base centralisée. Cependant, lorsque les clusters sont rapprochés afin de desservir des zones densément peuplées, les interférences entre faisceaux entre clusters adjacents deviennent plus graves. Pour supprimer les interférences avec les clusters adjacents, seul un simple schéma de commande de commutation de faisceau à la limite d'un cluster a été étudié en tant que schéma conventionnel. Dans cet article, l'algorithme de planification pour la transmission massive en liaison descendante MIMO à proximité des limites des clusters, qui combine deux algorithmes de planification, a été proposé. Dans le schéma proposé, chaque station de base divise sa propre cellule en plusieurs zones, commute les zones de support de manière séquentielle et dessert les utilisateurs de ces zones. Les résultats numériques montrent que les débits s'améliorent avec une légère réduction de l'indice d'équité (FI) lorsque le nombre d'utilisateurs par bloc de ressources est de un. Le FI atteint son maximum lorsque le nombre d'utilisateurs par cellule est égal au nombre de zones divisées. Le schéma proposé réduit la complexité de calcul par rapport à celles des deux schémas conventionnels.
Masahito YATA
Keio University
Yukitoshi SANADA
Keio University
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Masahito YATA, Yukitoshi SANADA, "User Scheduling at Base Station Cluster Boundary for Massive MIMO Downlink Transmission" in IEICE TRANSACTIONS on Communications,
vol. E106-B, no. 9, pp. 837-843, September 2023, doi: 10.1587/transcom.2022EBP3157.
Abstract: One of the key technologies for the fifth-generation (5G) mobile communication system is massive multiple-input multiple-output (MIMO) that applies beamforming in order to effectively compensate for large propagation losses in high frequency bands and enable the spatial multiplexing of a large number of signal streams over multiple users. To further improve a system throughput, a coordinated cluster system in which a large number of massive MIMO base stations are deployed in high density has been investigated. The dense deployment greatly improves the system capacity by controlling base stations from a centralized base band unit. However, when clusters are closely located in order to serve densely populated areas, inter-beam interference between adjacent clusters becomes more severe. To suppress the interference to adjacent clusters, only a simple beam switch control scheme at a cluster boundary has been investigated as a conventional scheme. In this paper, the scheduling algorithm for massive MIMO downlink transmission near cluster boundaries, which combines two scheduling algorithms, has been proposed. In the proposed scheme, each base station divides its own cell to multiple areas, switches supporting areas sequentially, and serves users in those areas. The numerical results show that the throughputs improve with a little reduction in a fairness index (FI) when the number of users per resource block is one. The FI reaches the highest when the number of users per cell is equal to the number of divided areas. The proposed scheme reduces computational complexity as compared with those of conventional two schemes.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2022EBP3157/_p
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@ARTICLE{e106-b_9_837,
author={Masahito YATA, Yukitoshi SANADA, },
journal={IEICE TRANSACTIONS on Communications},
title={User Scheduling at Base Station Cluster Boundary for Massive MIMO Downlink Transmission},
year={2023},
volume={E106-B},
number={9},
pages={837-843},
abstract={One of the key technologies for the fifth-generation (5G) mobile communication system is massive multiple-input multiple-output (MIMO) that applies beamforming in order to effectively compensate for large propagation losses in high frequency bands and enable the spatial multiplexing of a large number of signal streams over multiple users. To further improve a system throughput, a coordinated cluster system in which a large number of massive MIMO base stations are deployed in high density has been investigated. The dense deployment greatly improves the system capacity by controlling base stations from a centralized base band unit. However, when clusters are closely located in order to serve densely populated areas, inter-beam interference between adjacent clusters becomes more severe. To suppress the interference to adjacent clusters, only a simple beam switch control scheme at a cluster boundary has been investigated as a conventional scheme. In this paper, the scheduling algorithm for massive MIMO downlink transmission near cluster boundaries, which combines two scheduling algorithms, has been proposed. In the proposed scheme, each base station divides its own cell to multiple areas, switches supporting areas sequentially, and serves users in those areas. The numerical results show that the throughputs improve with a little reduction in a fairness index (FI) when the number of users per resource block is one. The FI reaches the highest when the number of users per cell is equal to the number of divided areas. The proposed scheme reduces computational complexity as compared with those of conventional two schemes.},
keywords={},
doi={10.1587/transcom.2022EBP3157},
ISSN={1745-1345},
month={September},}
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TY - JOUR
TI - User Scheduling at Base Station Cluster Boundary for Massive MIMO Downlink Transmission
T2 - IEICE TRANSACTIONS on Communications
SP - 837
EP - 843
AU - Masahito YATA
AU - Yukitoshi SANADA
PY - 2023
DO - 10.1587/transcom.2022EBP3157
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E106-B
IS - 9
JA - IEICE TRANSACTIONS on Communications
Y1 - September 2023
AB - One of the key technologies for the fifth-generation (5G) mobile communication system is massive multiple-input multiple-output (MIMO) that applies beamforming in order to effectively compensate for large propagation losses in high frequency bands and enable the spatial multiplexing of a large number of signal streams over multiple users. To further improve a system throughput, a coordinated cluster system in which a large number of massive MIMO base stations are deployed in high density has been investigated. The dense deployment greatly improves the system capacity by controlling base stations from a centralized base band unit. However, when clusters are closely located in order to serve densely populated areas, inter-beam interference between adjacent clusters becomes more severe. To suppress the interference to adjacent clusters, only a simple beam switch control scheme at a cluster boundary has been investigated as a conventional scheme. In this paper, the scheduling algorithm for massive MIMO downlink transmission near cluster boundaries, which combines two scheduling algorithms, has been proposed. In the proposed scheme, each base station divides its own cell to multiple areas, switches supporting areas sequentially, and serves users in those areas. The numerical results show that the throughputs improve with a little reduction in a fairness index (FI) when the number of users per resource block is one. The FI reaches the highest when the number of users per cell is equal to the number of divided areas. The proposed scheme reduces computational complexity as compared with those of conventional two schemes.
ER -