Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments

Yamaguchi, Kanako; Huu Phu Bui; Ogawa, Yasutaka; Nishimura, Toshihiko; Ohgane, Takeo

doi:10.1587/transcom.E97.B.2747


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Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/59897

Title:	Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments
Authors:	Yamaguchi, Kanako Browse this author
	Huu Phu Bui Browse this author
	Ogawa, Yasutaka Browse this author →KAKEN DB
	Nishimura, Toshihiko Browse this author →KAKEN DB
	Ohgane, Takeo Browse this author →KAKEN DB
Keywords:	channel prediction
	multi-user MIMO system
	block diagonalization
	eigenbeam-space division multiplexing
	time-varying environments
	AR model
	lagrange extrapolation
Issue Date:	Dec-2014
Publisher:	The Institute of Electronics, Information and Communication Engineers (IEICE)
Journal Title:	IEICE transactions on communications
Volume:	E97B
Issue:	12
Start Page:	2747
End Page:	2755
Publisher DOI:	10.1587/transcom.E97.B.2747
Abstract:	Although multi-user multiple-input multiple-output (MIMO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multi-plexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.
Rights:	copyright©2014 IEICE
Type:	article
URI:	http://hdl.handle.net/2115/59897
Appears in Collections:	情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 西村寿彦

OAI-PMH ( junii2 , jpcoar_1.0 )

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