IEICE TRANSACTIONS on Communications
Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments
Summary :
Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (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 The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI.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.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E97-B No.12 pp.2747-2755
- Publication Date
- 2014/12/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.E97.B.2747
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Kanako YAMAGUCHI
Hokkaido University
Huu Phu BUI
University of Technology, Vietnam National University
Yasutaka OGAWA
Hokkaido University
Toshihiko NISHIMURA
Hokkaido University
Takeo OHGANE
Hokkaido University
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Kanako YAMAGUCHI, Huu Phu BUI, Yasutaka OGAWA, Toshihiko NISHIMURA, Takeo OHGANE, "Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments" in IEICE TRANSACTIONS on Communications,
vol. E97-B, no. 12, pp. 2747-2755, December 2014, doi: 10.1587/transcom.E97.B.2747.
Abstract: Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (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.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E97.B.2747/_p
Copy
@ARTICLE{e97-b_12_2747,
author={Kanako YAMAGUCHI, Huu Phu BUI, Yasutaka OGAWA, Toshihiko NISHIMURA, Takeo OHGANE, },
journal={IEICE TRANSACTIONS on Communications},
title={Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments},
year={2014},
volume={E97-B},
number={12},
pages={2747-2755},
abstract={Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (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.},
keywords={},
doi={10.1587/transcom.E97.B.2747},
ISSN={1745-1345},
month={December},}
Copy
TY - JOUR
TI - Channel Prediction Techniques for a Multi-User MIMO System in Time-Varying Environments
T2 - IEICE TRANSACTIONS on Communications
SP - 2747
EP - 2755
AU - Kanako YAMAGUCHI
AU - Huu Phu BUI
AU - Yasutaka OGAWA
AU - Toshihiko NISHIMURA
AU - Takeo OHGANE
PY - 2014
DO - 10.1587/transcom.E97.B.2747
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E97-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2014
AB - Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (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.
ER -
English
