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| Presentation | 2022-08-26 09:54 A study on adaptive rate control using Deep Q-network in IEEE 802.11 Tomoki Nakashima (Kyutech), Leonardo Lanante (Ofinno), Masayuki Kurosaki, Hiroshi Ochi (Kyutech)  SIP2022-63 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Transmission rate control in wireless LANs is one of the factors that affect communication quality. Although many transmission rate control algorithms have been proposed, there are cases in which existing algorithms cannot adaptively control the rate depending on changes in the wireless communication environment. In this study, we propose a transmission rate control method using Deep Q-Network (DQN) to adapt to changes in the communication environment due to node movement. We evaluate the proposed DQN-based transmission rate control using the ns3-ai framework. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | IEEE 802.11 / Wireless LAN / Rate Control / Reinforcement Learning / Deep Q-network / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 122, no. 165, SIP2022-63, pp. 70-74, Aug. 2022. | |
| Paper # | SIP2022-63 | |
| Date of Issue | 2022-08-18 (SIP) | |
| 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 | SIP2022-63 |
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| Conference Information | |
| Committee | SIP |
| Conference Date | 2022-08-25 - 2022-08-26 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nobumoto Ohama Memorial Hall (Ishigaki Island) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Signal processing, etc. |
| Paper Information | |
| Registration To | SIP |
| Conference Code | 2022-08-SIP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study on adaptive rate control using Deep Q-network in IEEE 802.11 |
| Sub Title (in English) | |
| Keyword(1) | IEEE 802.11 |
| Keyword(2) | Wireless LAN |
| Keyword(3) | Rate Control |
| Keyword(4) | Reinforcement Learning |
| Keyword(5) | Deep Q-network |
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| Keyword(8) | |
| 1st Author's Name | Tomoki Nakashima |
| 1st Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 2nd Author's Name | Leonardo Lanante |
| 2nd Author's Affiliation | Ofinno LLC (Ofinno) |
| 3rd Author's Name | Masayuki Kurosaki |
| 3rd Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 4th Author's Name | Hiroshi Ochi |
| 4th Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
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| Speaker | Author-1 |
| Date Time | 2022-08-26 09:54:00 |
| Presentation Time | 18 minutes |
| Registration for | SIP |
| Paper # | SIP2022-63 |
| Volume (vol) | vol.122 |
| Number (no) | no.165 |
| Page | pp.70-74 |
| #Pages | 5 |
| Date of Issue | 2022-08-18 (SIP) |
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