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Paper Abstract and Keywords
Presentation 2019-11-06 13:25
[Poster Presentation] Two-step Wireless Area Quality Prediction by Artificial Neural Network for Wireless Service Area Planning
Kentaro Saito, Yongri Jin, CheChia Kang, Jun-ichi Takada (Tokyo Tech.) SRW2019-40 SeMI2019-84 CNR2019-34
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, many kinds of wireless networks are constructed and managed by users in various industrial sectors owing to the wide spreads of Internet of Things (IoT) service. Therefore, the optimized network service area planning becomes a more urgent issue for the efficient usage of the radio resource. In the service area planning, the network is evaluated from several aspects such as the communication quality in the area, the grasping of the out-of-service region, and the detection of the interference to other service areas. In this research, we classified each point in the area into the service zone, the interference zone, and the negligible zone by the artificial neural network (ANN) classifier that was trained by the ray-tracing simulation result. And then the, receiving power in the respective zones was predicted by ANN regressors that were trained respectively. The receiving power prediction accuracy can be improved especially in the service zone by classifying the area into the zones where the communication qualities are similar. We evaluated our proposed algorithm in an indoor environment, and we showed that the root mean square error (RMSE) was improved from 7.9 dB to 4.1 dB. Especially, it was improved to 2.4 dB in the service zone. The evaluations in more variety of environments and the utilization of our proposal for actual service area planning will be the future works.
Keyword (in Japanese) (See Japanese page) 
(in English) Cell planning / Indoor propagation / Machine learning / Neural network / Path loss prediction / Radio propagation simulation / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 265, SRW2019-40, pp. 69-70, Nov. 2019.
Paper # SRW2019-40 
Date of Issue 2019-10-29 (SRW, SeMI, CNR) 
ISSN Online edition: ISSN 2432-6380
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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)
Download PDF SRW2019-40 SeMI2019-84 CNR2019-34

Conference Information
Committee SRW SeMI CNR  
Conference Date 2019-11-05 - 2019-11-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Kozo Keisaku Engineering Inc. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) IoT Workshop (Oral or Poster presentation) 
Paper Information
Registration To SRW 
Conference Code 2019-11-SRW-SeMI-CNR 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Two-step Wireless Area Quality Prediction by Artificial Neural Network for Wireless Service Area Planning 
Sub Title (in English)  
Keyword(1) Cell planning  
Keyword(2) Indoor propagation  
Keyword(3) Machine learning  
Keyword(4) Neural network  
Keyword(5) Path loss prediction  
Keyword(6) Radio propagation simulation  
Keyword(7)  
Keyword(8)  
1st Author's Name Kentaro Saito  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Tech.)
2nd Author's Name Yongri Jin  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech.)
3rd Author's Name CheChia Kang  
3rd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech.)
4th Author's Name Jun-ichi Takada  
4th Author's Affiliation Tokyo Institute of Technology (Tokyo Tech.)
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Speaker Author-1 
Date Time 2019-11-06 13:25:00 
Presentation Time 60 minutes 
Registration for SRW 
Paper # SRW2019-40, SeMI2019-84, CNR2019-34 
Volume (vol) vol.119 
Number (no) no.265(SRW), no.266(SeMI), no.267(CNR) 
Page pp.69-70(SRW), pp.89-90(SeMI), pp.67-68(CNR) 
#Pages
Date of Issue 2019-10-29 (SRW, SeMI, CNR) 


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