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Paper Abstract and Keywords
Presentation 2019-03-09 14:00
A Deep Learning Based Spatial Spectrum Reuse Approach in Multiple Dense WLAN Scenarios
Jin Liu, Masahide Hatanaka, Takao Onoye (Osaka Univ.) CAS2018-153 CS2018-121
Abstract (in Japanese) (See Japanese page) 
(in English) Recently, with the development of wireless local area network (WLAN) applications, a considerable expansion of wireless devices has resulted in dense WLANs. However, due to the limited resource such as spectrum, an increasing number of these wireless devices are working on the same channel. This dense deployment may incur co-channel interference and lead to the degradation of the overall network performance. To solve this problem, IEEE 802.11ax task group (IEEE 802.11 TGax) will adopt dynamic sensitivity control (DSC) in the next generation WLAN. DSC is a new scheme to improve spatial spectrum reuse by configuring the carrier sensing threshold (CST). In this study, we propose a deep belief network based DSC (DBN-DSC) algorithm to improve the spatial spectrum reuse in dense WLANs. We evaluate the DBN-DSC algorithm under all six standard dense scenarios proposed by IEEE 802.11 TGax. Our simulation results show that both the throughput and fairness of DBN-DSC algorithm outperform the established, beacon RSSI based DSC (BR-DSC) algorithm, under all six scenarios.
Keyword (in Japanese) (See Japanese page) 
(in English) IEEE 802.11ax / Deep learning / Dynamic sensitivity control (DSC) / Dense deployment / Spatial spectrum reuse / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 489, CS2018-121, pp. 81-86, March 2019.
Paper # CS2018-121 
Date of Issue 2019-03-01 (CAS, CS) 
ISSN Print edition: ISSN 0913-5685  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 CAS CS  
Conference Date 2019-03-08 - 2019-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) Shonan Institute of Technology 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network processor, Signal processing and circuits for communications, Wireless LAN / PAN, etc. 
Paper Information
Registration To CS 
Conference Code 2019-03-CAS-CS 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Deep Learning Based Spatial Spectrum Reuse Approach in Multiple Dense WLAN Scenarios 
Sub Title (in English)  
Keyword(1) IEEE 802.11ax  
Keyword(2) Deep learning  
Keyword(3) Dynamic sensitivity control (DSC)  
Keyword(4) Dense deployment  
Keyword(5) Spatial spectrum reuse  
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1st Author's Name Jin Liu  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Masahide Hatanaka  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Takao Onoye  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Speaker
Date Time 2019-03-09 14:00:00 
Presentation Time 25 
Registration for CS 
Paper # IEICE-CAS2018-153,IEICE-CS2018-121 
Volume (vol) IEICE-118 
Number (no) no.488(CAS), no.489(CS) 
Page pp.81-86 
#Pages IEICE-6 
Date of Issue IEICE-CAS-2019-03-01,IEICE-CS-2019-03-01 


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