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Paper Abstract and Keywords
Presentation 2022-10-20 14:00
A Study on Rain Attenuation Prediction Method by Deep Learning 2 -- Error Characteristics --
Yuji Komatsuya, Tetsuro Imai (TDU), Miyuki Hirose (Kyutech) AP2022-141
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, the frequency used in wireless systems has got higher significantly, such as B5G (6G), HAPS, etc., and the importance of predicting rainfall attenuation has increased. We proposed a rain attenuation prediction method by deep learning which inputs rainfall rate and path distance, and conducted prediction. In this study, we improved the input data and scale of the proposed model, achieved broad-sense performance improvement of the proposed model. Furthermore, we indicated superiority of proposed model over conventional method using rain attenuation coefficients defined in the ITU-R Recommendation. In addition, we considered the output result of proposed model.
Keyword (in Japanese) (See Japanese page) 
(in English) Rain Attenuation / Deep Learningp / CNN / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 214, AP2022-141, pp. 211-215, Oct. 2022.
Paper # AP2022-141 
Date of Issue 2022-10-12 (AP) 
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)
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Conference Information
Committee AP  
Conference Date 2022-10-19 - 2022-10-20 
Place (in Japanese) (See Japanese page) 
Place (in English) GIFU CITY CULTURE CENTER 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Student Session, Antennas and Propagation 
Paper Information
Registration To AP 
Conference Code 2022-10-AP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Rain Attenuation Prediction Method by Deep Learning 2 
Sub Title (in English) Error Characteristics 
Keyword(1) Rain Attenuation  
Keyword(2) Deep Learningp  
Keyword(3) CNN  
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1st Author's Name Yuji Komatsuya  
1st Author's Affiliation Tokyo Denki University (TDU)
2nd Author's Name Tetsuro Imai  
2nd Author's Affiliation Tokyo Denki University (TDU)
3rd Author's Name Miyuki Hirose  
3rd Author's Affiliation Kyushu Institute of Technology (Kyutech)
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Speaker Author-1 
Date Time 2022-10-20 14:00:00 
Presentation Time 25 minutes 
Registration for AP 
Paper # AP2022-141 
Volume (vol) vol.122 
Number (no) no.214 
Page pp.211-215 
#Pages
Date of Issue 2022-10-12 (AP) 


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