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Paper Abstract and Keywords
Presentation 2024-02-16 15:00
[Invited Lecture] Propagation loss prediction method by machine learning and ray-tracing for indoor environments
Takayuki Nakanishi, Kenya Shimizu (MELCO), Kenzaburo Hitomi (MEE), Yasuhiro Nishioka, Yoshio Inasawa (MELCO) AP2023-197
Abstract (in Japanese) (See Japanese page) 
(in English) Radio propagation estimation is important for improving the stability and reliability of wireless communications. However, the antenna radiation pattern of radio communication module changes by the effect of the installation location and the surrounding structure, which caused the undesirable directivity. This report proposes the propagation loss prediction method by machine learning and ray-tracing for indoor environments to consider the antenna directivity. To evaluate the accuracy of proposed model, we measured the received power with directivity antenna at a residential environment. For the front direction of directivity antenna, the accuracy is as well as the conventional model and the proposed model. For the side and back direction, the proposed model can estimate the propagation loss more accurately than conventional model.
Keyword (in Japanese) (See Japanese page) 
(in English) Radio Propagation Model / Indoor Propagation / Machine Learning / Ray-tracing / Antenna Directivity / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 378, AP2023-197, pp. 50-55, Feb. 2024.
Paper # AP2023-197 
Date of Issue 2024-02-08 (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 AP2023-197

Conference Information
Committee AP  
Conference Date 2024-02-15 - 2024-02-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Sinfonia Technology Hibiki Hall Ise 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Industrial Session, Antennas and Propagation 
Paper Information
Registration To AP 
Conference Code 2024-02-AP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Propagation loss prediction method by machine learning and ray-tracing for indoor environments 
Sub Title (in English)  
Keyword(1) Radio Propagation Model  
Keyword(2) Indoor Propagation  
Keyword(3) Machine Learning  
Keyword(4) Ray-tracing  
Keyword(5) Antenna Directivity  
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Keyword(7)  
Keyword(8)  
1st Author's Name Takayuki Nakanishi  
1st Author's Affiliation Mitsubishi Electric Corporation (MELCO)
2nd Author's Name Kenya Shimizu  
2nd Author's Affiliation Mitsubishi Electric Corporation (MELCO)
3rd Author's Name Kenzaburo Hitomi  
3rd Author's Affiliation Mitsubishi Electric Engineering Company Limited (MEE)
4th Author's Name Yasuhiro Nishioka  
4th Author's Affiliation Mitsubishi Electric Corporation (MELCO)
5th Author's Name Yoshio Inasawa  
5th Author's Affiliation Mitsubishi Electric Corporation (MELCO)
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Speaker Author-1 
Date Time 2024-02-16 15:00:00 
Presentation Time 25 minutes 
Registration for AP 
Paper # AP2023-197 
Volume (vol) vol.123 
Number (no) no.378 
Page pp.50-55 
#Pages 6 
Date of Issue 2024-02-08 (AP) 

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