Scalable user selection in FDD massive MIMO

Abstract User subset selection requires full downlink channel state information to realize effective multi-user beamforming in frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. However, the channel estimation overhead scales with the number of users in FDD systems....

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Autores principales:	Xing Zhang, Ashutosh Sabharwal
Formato:	article
Lenguaje:	EN
Publicado:	SpringerOpen 2021
Materias:	Massive MIMO FDD User selection Telecommunication TK5101-6720 Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/525537d1ef76445a8b55e4ff3326b7a6
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spelling	oai:doaj.org-article:525537d1ef76445a8b55e4ff3326b7a62021-12-05T12:06:34ZScalable user selection in FDD massive MIMO10.1186/s13638-021-02073-41687-1499https://doaj.org/article/525537d1ef76445a8b55e4ff3326b7a62021-12-01T00:00:00Zhttps://doi.org/10.1186/s13638-021-02073-4https://doaj.org/toc/1687-1499Abstract User subset selection requires full downlink channel state information to realize effective multi-user beamforming in frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. However, the channel estimation overhead scales with the number of users in FDD systems. In this paper, we propose a novel propagation domain-based user selection scheme, labeled as zero-measurement selection, for FDD massive MIMO systems with the aim of reducing the channel estimation overhead that scales with the number of users. The key idea is to infer downlink user channel norm and inter-user channel correlation from uplink channel in the propagation domain. In zero-measurement selection, the base-station performs downlink user selection before any downlink channel estimation. As a result, the downlink channel estimation overhead for both user selection and beamforming is independent of the total number of users. Then, we evaluate zero-measurement selection with both measured and simulated channels. The results show that zero-measurement selection achieves up to 92.5% weighted sum rate of genie-aided user selection on the average and scales well with both the number of base-station antennas and the number of users. We also employ simulated channels for further performance validation, and the numerical results yield similar observations as the experimental findings.Xing ZhangAshutosh SabharwalSpringerOpenarticleMassive MIMOFDDUser selectionTelecommunicationTK5101-6720ElectronicsTK7800-8360ENEURASIP Journal on Wireless Communications and Networking, Vol 2021, Iss 1, Pp 1-18 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Massive MIMO FDD User selection Telecommunication TK5101-6720 Electronics TK7800-8360
spellingShingle	Massive MIMO FDD User selection Telecommunication TK5101-6720 Electronics TK7800-8360 Xing Zhang Ashutosh Sabharwal Scalable user selection in FDD massive MIMO
description	Abstract User subset selection requires full downlink channel state information to realize effective multi-user beamforming in frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. However, the channel estimation overhead scales with the number of users in FDD systems. In this paper, we propose a novel propagation domain-based user selection scheme, labeled as zero-measurement selection, for FDD massive MIMO systems with the aim of reducing the channel estimation overhead that scales with the number of users. The key idea is to infer downlink user channel norm and inter-user channel correlation from uplink channel in the propagation domain. In zero-measurement selection, the base-station performs downlink user selection before any downlink channel estimation. As a result, the downlink channel estimation overhead for both user selection and beamforming is independent of the total number of users. Then, we evaluate zero-measurement selection with both measured and simulated channels. The results show that zero-measurement selection achieves up to 92.5% weighted sum rate of genie-aided user selection on the average and scales well with both the number of base-station antennas and the number of users. We also employ simulated channels for further performance validation, and the numerical results yield similar observations as the experimental findings.
format	article
author	Xing Zhang Ashutosh Sabharwal
author_facet	Xing Zhang Ashutosh Sabharwal
author_sort	Xing Zhang
title	Scalable user selection in FDD massive MIMO
title_short	Scalable user selection in FDD massive MIMO
title_full	Scalable user selection in FDD massive MIMO
title_fullStr	Scalable user selection in FDD massive MIMO
title_full_unstemmed	Scalable user selection in FDD massive MIMO
title_sort	scalable user selection in fdd massive mimo
publisher	SpringerOpen
publishDate	2021
url	https://doaj.org/article/525537d1ef76445a8b55e4ff3326b7a6
work_keys_str_mv	AT xingzhang scalableuserselectioninfddmassivemimo AT ashutoshsabharwal scalableuserselectioninfddmassivemimo
_version_	1718372253027008512

Scalable user selection in FDD massive MIMO

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