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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
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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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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 
Sub Title (in English)  
Keyword(1) Interference alignment  
Keyword(2) Channel prediction  
Keyword(3) 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)
5th Author's Name Tadao Nakagawa  
5th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
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Speaker
Date Time 2016-03-04 09:25:00 
Presentation Time 25 
Registration for RCS 
Paper # IEICE-RCS2015-381 
Volume (vol) IEICE-115 
Number (no) no.472 
Page pp.279-284 
#Pages IEICE-6 
Date of Issue IEICE-RCS-2016-02-24 


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