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Paper Abstract and Keywords
Presentation 2021-03-05 09:50
Deep Learning-based Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.) RCS2020-254
Abstract (in Japanese) (See Japanese page) 
(in English) In a massive multiple-input multiple-output (MIMO) system based on time division duplex (TDD), the channel state information (CSI) between the base station (BS) and the user terminal (UT) is required. Due to Doppler shift, the fluctuations of the channel between the BS and the UT causes differences of the channel between the channel estimation and channel utilization, which is an issue called channel aging. In this report, we propose a data-aided channel estimation method based on deep learning to mitigate the effect of channel aging in a massive MIMO system with pilot contamination. After signal detection using the estimated channel obtained from the received signal in the pilot part, the detected symbol is regarded as a pilot and the channel for each time slot is estimated from the received signal in the data part. Through computer simulations, we show that the proposed method improves the channel estimation accuracy compared with the deep learning-based channel estimation with received pilot signal and the interpolation method.
Keyword (in Japanese) (See Japanese page) 
(in English) Channel aging / Channel estimation / Convolutional neural network / Massive MIMO / Pilot contamination / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 404, RCS2020-254, pp. 234-239, March 2021.
Paper # RCS2020-254 
Date of Issue 2021-02-24 (RCS) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 SR SRW  
Conference Date 2021-03-03 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Mobile Communication Workshop 
Paper Information
Registration To RCS 
Conference Code 2021-03-RCS-SR-SRW 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Deep Learning-based Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination 
Sub Title (in English)  
Keyword(1) Channel aging  
Keyword(2) Channel estimation  
Keyword(3) Convolutional neural network  
Keyword(4) Massive MIMO  
Keyword(5) Pilot contamination  
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1st Author's Name Hiroki Hirose  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Tomoaki Ohtsuki  
2nd Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2021-03-05 09:50:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2020-254 
Volume (vol) vol.120 
Number (no) no.404 
Page pp.234-239 
#Pages
Date of Issue 2021-02-24 (RCS) 


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