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Paper Abstract and Keywords
Presentation 2018-07-12 10:55
[Poster Presentation] Supervised Learning-based Primary Exclusive Region Update Robust Against Imbalanced Data for Spectrum Sharing
Aogu Yamada, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto (Kyoto Univ.) RCC2018-44 NS2018-57 RCS2018-102 SR2018-41 ASN2018-38
Abstract (in Japanese) (See Japanese page) 
(in English) In spectrum sharing, secondary users (SUs) utilize a licensed frequency band under a condition to avoid interference with a primary user (PU) such as primary exclusive region (PER), wherein SUs are prohibited to transmit.
In this talk, we propose a supervised learning-based PER update based on transmission logs of SUs and interference messages from PU.
In addition, to overcome imbalanced data which degrades learning performance, we design undersampling, oversampling and reverse sampling which uniformalize the number of the dominant non-interference labeled training data and the minority interference labeled data.
Simulation results show the framework for updating PER with the proposed sampling schemes achieves smaller PER compared to the other frameworks.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine learning / Spectrum sharing / Cognitive radio / Supervised learning / Imbalanced data / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 126, SR2018-41, pp. 107-108, July 2018.
Paper # SR2018-41 
Date of Issue 2018-07-04 (RCC, NS, RCS, SR, ASN) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 RCC2018-44 NS2018-57 RCS2018-102 SR2018-41 ASN2018-38

Conference Information
Committee ASN NS RCS SR RCC  
Conference Date 2018-07-11 - 2018-07-13 
Place (in Japanese) (See Japanese page) 
Place (in English) Hakodate Arena 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Wireless Distributed Network, Machine Learning and AI for Wireless Communications and Networks, M2M (Machine-to-Machine), D2D (Device-to-Device), IoT(Internet of Things), etc. 
Paper Information
Registration To SR 
Conference Code 2018-07-ASN-NS-RCS-SR-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Supervised Learning-based Primary Exclusive Region Update Robust Against Imbalanced Data for Spectrum Sharing 
Sub Title (in English)  
Keyword(1) Machine learning  
Keyword(2) Spectrum sharing  
Keyword(3) Cognitive radio  
Keyword(4) Supervised learning  
Keyword(5) Imbalanced data  
1st Author's Name Aogu Yamada  
1st Author's Affiliation Kyoto University (Kyoto Univ.)
2nd Author's Name Takayuki Nishio  
2nd Author's Affiliation Kyoto University (Kyoto Univ.)
3rd Author's Name Masahiro Morikura  
3rd Author's Affiliation Kyoto University (Kyoto Univ.)
4th Author's Name Koji Yamamoto  
4th Author's Affiliation Kyoto University (Kyoto Univ.)
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Date Time 2018-07-12 10:55:00 
Presentation Time 80 
Registration for SR 
Paper # IEICE-RCC2018-44,IEICE-NS2018-57,IEICE-RCS2018-102,IEICE-SR2018-41,IEICE-ASN2018-38 
Volume (vol) IEICE-118 
Number (no) no.123(RCC), no.124(NS), no.125(RCS), no.126(SR), no.127(ASN) 
Page pp.97-98(RCC), pp.103-104(NS), pp.115-116(RCS), pp.107-108(SR), pp.113-114(ASN) 
#Pages IEICE-2 
Date of Issue IEICE-RCC-2018-07-04,IEICE-NS-2018-07-04,IEICE-RCS-2018-07-04,IEICE-SR-2018-07-04,IEICE-ASN-2018-07-04 

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