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Paper Abstract and Keywords
Presentation 2019-06-21 10:50
Channel Estimation via Neural Network for Massive MIMO with Pilot Contamination
Hiroki Hirose, Tomoaki Ohtsuki (Keio Univ.) RCS2019-89
Abstract (in Japanese) (See Japanese page) 
(in English) In massive multiple-input multiple-output (MIMO) based on time division duplex (TDD), a base station (BS) needs accurate estimation of channel state information (CSI) for a user terminal (UT).
UTs transmit pilot signals to the BS to estimate the channels between them.
Since the propagation environment changes over time, the channel state also changes accordingly.
Due to the time-variant channel, the length of the pilot signal is limited and thus the number of orthogonal pilot signals is finite.
Therefore, same pilot signals are reused in neighboring cells.
For this reason, channel estimation accuracy deteriorates due to the interference from the neighboring cells, which is called pilot contamination.
With the minimum mean square error (MMSE) channel estimation, the influence of pilot contamination can be reduced if the covariance matrix of channels for all users is known.
However, this matrix is unknown to the BS a priori, and has to be estimated.
In this report, we propose a channel estimation method that reduces the influence of pilot contamination by learning a desired channel corresponding to a contaminated signal with a neural network.
We evaluate both the case where timing synchronization mismatches have occurred between the BS and the UTs in another cell, and the case where it is perfectly synchronized.
Our computer simulation results show that the proposed method improves the normalized mean square error (NMSE) of the channel compared with the conventional one.
Keyword (in Japanese) (See Japanese page) 
(in English) Massive MIMO / pilot contamination / channel estimation / neural network / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 90, RCS2019-89, pp. 303-308, June 2019.
Paper # RCS2019-89 
Date of Issue 2019-06-12 (RCS) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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  
Conference Date 2019-06-19 - 2019-06-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Miyakojima Hirara Port Terminal Building 
Topics (in Japanese) (See Japanese page) 
Topics (in English) First Presentation in IEICE Technical Committee, Resource Control, Scheduling, Wireless Communications, etc. 
Paper Information
Registration To RCS 
Conference Code 2019-06-RCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Channel Estimation via Neural Network for Massive MIMO with Pilot Contamination 
Sub Title (in English)  
Keyword(1) Massive MIMO  
Keyword(2) pilot contamination  
Keyword(3) channel estimation  
Keyword(4) neural network  
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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 2019-06-21 10:50:00 
Presentation Time 10 minutes 
Registration for RCS 
Paper # RCS2019-89 
Volume (vol) vol.119 
Number (no) no.90 
Page pp.303-308 
#Pages
Date of Issue 2019-06-12 (RCS) 


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