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Paper Abstract and Keywords
Presentation 2023-02-17 11:25
Study on Switching Decision Accuracy of HAPS Site Diversity Based on Predicted Rain Attenuation by Deep Learning
Yuji Komatsuya, Tetsuro Imai (TDU), Miyuki Hirose (Kyutech) AP2022-224
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, It is actively to be studied for practical application of HAPS which is the next-generation platforms. It is necessary for HAPS to address rain attenuation due to the frequency HAPS used, hence proactive rain attenuation compensation using site diversity technology is considered currently. On the other hand, we have proposed rain attenuation prediction method by deep learning. In this study, we evaluated the characteristics of site switching decision accuracy when rain attenuation occurs using rain attenuation prediction method that we proposed.
Keyword (in Japanese) (See Japanese page) 
(in English) Rain attenuation / HAPS / Site diversity / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 378, AP2022-224, pp. 151-156, Feb. 2023.
Paper # AP2022-224 
Date of Issue 2023-02-08 (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)
Download PDF AP2022-224

Conference Information
Committee AP  
Conference Date 2023-02-15 - 2023-02-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku University, Aobayama Campus 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Industrial Session, Antennas and Propagation 
Paper Information
Registration To AP 
Conference Code 2023-02-AP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Study on Switching Decision Accuracy of HAPS Site Diversity Based on Predicted Rain Attenuation by Deep Learning 
Sub Title (in English)  
Keyword(1) Rain attenuation  
Keyword(2) HAPS  
Keyword(3) Site diversity  
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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 2023-02-17 11:25:00 
Presentation Time 25 minutes 
Registration for AP 
Paper # AP2022-224 
Volume (vol) vol.122 
Number (no) no.378 
Page pp.151-156 
#Pages 6 
Date of Issue 2023-02-08 (AP) 

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