Paper Abstract and Keywords |
Presentation |
2016-03-04 09:25
Interference Alignment for Time-Varying Channel with Low Complexity Channel Prediction based on Auto Regressive Model Masayoshi Ozawa, Tomoaki Ohtsuki (Keio Univ.), Wenjie Jiang, Yasushi Takatori, Tadao Nakagawa (NTT) RCS2015-381 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Interference alignment (IA) is a interference suppression technique with a few number of antennas by aligning interference signals using transmit weights. Although weights are calculated based on channel state information (CSI) fed back from each receiver, weights based on delayed channels can not align them due to time-varying channel. Therefore, IA with a channel prediction is gathering attention. Auto regressive (AR) model is a prediction method that predicts the future state based on past states. However, the calculation amount is large. In this report, we propose a low complexity and high accuracy channel prediction based on AR model and apply it to IA. We use differences of channels between adjacent time to predict future channel. Past channels are used directly in conventional IA with channel prediction. However, the prediction error becomes small when the future channel is predicted with differences of channels between adjacent time. Through computer simulation, IA with the proposed channel prediction is shown to improve the channel prediction accuracy, reduce the calculation amount, and improve the transmission rate. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Interference alignment / Channel prediction / Auto regressive model / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 472, RCS2015-381, pp. 279-284, March 2016. |
Paper # |
RCS2015-381 |
Date of Issue |
2016-02-24 (RCS) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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RCS2015-381 |
Conference Information |
Committee |
RCS CCS SR SRW |
Conference Date |
2016-03-02 - 2016-03-04 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Tokyo Institute of Technology |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Mobile Communication Workshop |
Paper Information |
Registration To |
RCS |
Conference Code |
2016-03-RCS-CCS-SR-SRW |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Interference Alignment for Time-Varying Channel with Low Complexity Channel Prediction based on Auto Regressive Model |
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Interference alignment |
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Channel prediction |
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Auto regressive model |
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1st Author's Name |
Masayoshi Ozawa |
1st Author's Affiliation |
Keio Univercity (Keio Univ.) |
2nd Author's Name |
Tomoaki Ohtsuki |
2nd Author's Affiliation |
Keio Univercity (Keio Univ.) |
3rd Author's Name |
Wenjie Jiang |
3rd Author's Affiliation |
Nippon Telegraph and Telephone Corporation (NTT) |
4th Author's Name |
Yasushi Takatori |
4th Author's Affiliation |
Nippon Telegraph and Telephone Corporation (NTT) |
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Tadao Nakagawa |
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Nippon Telegraph and Telephone Corporation (NTT) |
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Speaker |
Author-1 |
Date Time |
2016-03-04 09:25:00 |
Presentation Time |
25 minutes |
Registration for |
RCS |
Paper # |
RCS2015-381 |
Volume (vol) |
vol.115 |
Number (no) |
no.472 |
Page |
pp.279-284 |
#Pages |
6 |
Date of Issue |
2016-02-24 (RCS) |
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