Scalable user selection in FDD massive MIMO

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dc.citation.articleNumber193en_US
dc.citation.journalTitleEURASIP Journal on Wireless Communications and Networkingen_US
dc.citation.volumeNumber2021en_US
dc.contributor.authorZhang, Xingen_US
dc.contributor.authorSabharwal, Ashutoshen_US
dc.date.accessioned2021-12-15T22:10:21Zen_US
dc.date.available2021-12-15T22:10:21Zen_US
dc.date.issued2021en_US
dc.description.abstractUser 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.en_US
dc.identifier.citationZhang, Xing and Sabharwal, Ashutosh. "Scalable user selection in FDD massive MIMO." <i>EURASIP Journal on Wireless Communications and Networking,</i> 2021, (2021) Springer Nature: https://doi.org/10.1186/s13638-021-02073-4.en_US
dc.identifier.digitals13638-021-02073-4en_US
dc.identifier.doihttps://doi.org/10.1186/s13638-021-02073-4en_US
dc.identifier.urihttps://hdl.handle.net/1911/111795en_US
dc.language.isoengen_US
dc.publisherSpringer Natureen_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleScalable user selection in FDD massive MIMOen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
dc.type.publicationpublisher versionen_US
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