Publications

Detailed Information

Performance Analysis of Uplink Sounding in Frequency Selective Fading Channel

DC Field Value Language
dc.contributor.authorKim, Hyung-Sin-
dc.contributor.authorLee, Seung-Hwan-
dc.contributor.authorLee, Yong-Hwan-
dc.date.accessioned2024-05-14T08:08:10Z-
dc.date.available2024-05-14T08:08:10Z-
dc.date.created2024-04-16-
dc.date.issued2010-
dc.identifier.citationTENCON 2010: 2010 IEEE REGION 10 CONFERENCE, pp.841-846-
dc.identifier.issn2159-3442-
dc.identifier.urihttps://hdl.handle.net/10371/202164-
dc.description.abstractChannel sounding is an efficient technique to get the channel state information (CSI) in time division duplex wireless communication systems. The base station can employ downlink beamforming by estimating the CSI from the sounding signal. To support a large number of users, the sounding signals of multiple users are multiplexed in the same physical resource unit by means of decimation separation (DS) or cyclic shift separation (CSS). This paper investigates the performance of DS and CSS-based channel sounding techniques in frequency selective fading channel. It is shown that the sounding performance is associated with the number of users, decimation or maximum cyclic shift index, frequency channel correlation, and channel estimation method.(1)-
dc.language영어-
dc.publisherIEEE-
dc.titlePerformance Analysis of Uplink Sounding in Frequency Selective Fading Channel-
dc.typeArticle-
dc.identifier.doi10.1109/TENCON.2010.5686575-
dc.citation.journaltitleTENCON 2010: 2010 IEEE REGION 10 CONFERENCE-
dc.identifier.wosid000287978600137-
dc.identifier.scopusid2-s2.0-79951586937-
dc.citation.endpage846-
dc.citation.startpage841-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorKim, Hyung-Sin-
dc.contributor.affiliatedAuthorLee, Yong-Hwan-
dc.type.docTypeProceedings Paper-
dc.description.journalClass1-
dc.subject.keywordAuthoruplink sounding-
dc.subject.keywordAuthordecimation separation-
dc.subject.keywordAuthorcyclic shift separation-
Appears in Collections:
Files in This Item:
There are no files associated with this item.

Related Researcher

  • Graduate School of Data Science
Research Area Distributed machine learning, Edge, Mobile AI

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share