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Paper Abstract and Keywords
Presentation 2022-01-20 13:40
Received Power Prediction of 60 GHz Millimeter-Wave Propagation in Indoor Environment from Time-Series Images Using Neural Networks
Khanh Nam Nguyen, Kenichi Takizawa (NICT) IT2021-55 SIP2021-63 RCS2021-223
Abstract (in Japanese) (See Japanese page) 
(in English) A millimeter-wave (mmWave) indoor propagation environment with obstacles in 60 GHz frequency band is set up where received signal data can be collected analytically from the proposed calculation method called Kirchhoff approximation (KA). In addition, experimental mmWave received power is also obtained to validate the formulated results, and utilized to train and evaluate predictive models. Two architectures of neural networks are utilized to predict mmWave propagation received power values from time-series images. In detail, three-dimensional (3D) convolutional neural network (CNN) and its combination with long short-term memory (CNN+LSTM) models are evaluated to predict up to 3 seconds ahead with root-mean-square errors of 3.02 dB and 2.32 dB, respectively.
Keyword (in Japanese) (See Japanese page) 
(in English) mmWave / indoor propagation / 60 GHz / time-series images / neural networks / Kirchhoff approximation / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 329, RCS2021-223, pp. 149-154, Jan. 2022.
Paper # RCS2021-223 
Date of Issue 2022-01-13 (IT, SIP, RCS) 
ISSN 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)
Download PDF IT2021-55 SIP2021-63 RCS2021-223

Conference Information
Committee RCS SIP IT  
Conference Date 2022-01-20 - 2022-01-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To RCS 
Conference Code 2022-01-RCS-SIP-IT 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Received Power Prediction of 60 GHz Millimeter-Wave Propagation in Indoor Environment from Time-Series Images Using Neural Networks 
Sub Title (in English)  
Keyword(1) mmWave  
Keyword(2) indoor propagation  
Keyword(3) 60 GHz  
Keyword(4) time-series images  
Keyword(5) neural networks  
Keyword(6) Kirchhoff approximation  
Keyword(7)  
Keyword(8)  
1st Author's Name Khanh Nam Nguyen  
1st Author's Affiliation National Institute of Information and Communications Technology (NICT)
2nd Author's Name Kenichi Takizawa  
2nd Author's Affiliation National Institute of Information and Communications Technology (NICT)
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Speaker Author-1 
Date Time 2022-01-20 13:40:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # IT2021-55, SIP2021-63, RCS2021-223 
Volume (vol) vol.121 
Number (no) no.327(IT), no.328(SIP), no.329(RCS) 
Page pp.149-154 
#Pages 6 
Date of Issue 2022-01-13 (IT, SIP, RCS) 

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