| Presentation | 2022-08-26 A study on rate control using Deep Q-network in IEEE802.11 Tomoki Nakashima, Leonardo Lanante, Masayuki Kurosaki, Hiroshi Ochi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | IEEE 802.11 / Wireless LAN / Rate Control / Reinforcement Learning / Deep Q-network |
| Paper # | SIP2022-63 |
| Date of Issue | 2022-08-18 (SIP) |
| Conference Information | |
| Committee | SIP |
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| Conference Date | 2022/8/25(2days) |
| 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. |
| Chair | Toshihisa Tanaka(Tokyo Univ. Agri.&Tech.) |
| Vice Chair | Koichi Ichige(Yokohama National Univ.) / Takayuki Nakachi(Ryukyu Univ.) |
| Secretary | Koichi Ichige(Tokyo Univ. Agri.&Tech.) / Takayuki Nakachi(Kogakuin Univ.) |
| Assistant | Taichi Yoshida(UEC) / Shoko Imaizumi(Chiba Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Signal Processing |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A study on rate control using Deep Q-network in IEEE802.11 |
| 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 |
| 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) |
| Date | 2022-08-26 |
| Paper # | SIP2022-63 |
| Volume (vol) | vol.122 |
| Number (no) | SIP-165 |
| Page | pp.pp.70-74(SIP), |
| #Pages | 5 |
| Date of Issue | 2022-08-18 (SIP) |