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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CAS2018-153 CS2018-121 |
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) |
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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 |
Author-1 |
Date Time |
2019-03-09 14:00:00 |
Presentation Time |
25 minutes |
Registration for |
CS |
Paper # |
CAS2018-153, CS2018-121 |
Volume (vol) |
vol.118 |
Number (no) |
no.488(CAS), no.489(CS) |
Page |
pp.81-86 |
#Pages |
6 |
Date of Issue |
2019-03-01 (CAS, CS) |
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