| Presentation | 2018-01-19 Decentralized WLAN Access Point Selection through Reinforcement Learning Takuya Nakamura, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto, Toshihisa Nabetani, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Many operators provide public wireless LAN services in public places such as stations or cafes. In many cases, a station (STA) selects an access point (AP) with the maximum received signal strength indicator (RSSI), which may lead to low throughput due to network conditions such as the number of connected users and bandwidths of core networks. An AP selection method based on reinforcement learning (RL) has been proposed. It enables to adapt to various situations in wireless LANs because RL learns an AP selection policy adaptively from observation data. However, it is not evaluated whether RL works well with incomplete observations, such as situations that bandwidths of core networks are different and unknown, and a STA cannot observe information of all APs. In this paper, we evaluate the effectiveness of the RL-based method under the situation where bandwidths of the core networks differ between APs, and show that the RL-based method achieves higher throughput than the opportunistic method that a STA selects the AP with fewest associated users. We also evaluate an AP selection method using the number of users associated with the AP which the STA associates with, and show that a STA using the limited information achieves higher throughput compared with a STA using the number of users of all APs, when the amount of training data is small. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Reinforcement learning / Q-Learning / AP selection / Handover / Wireless LAN |
| Paper # | MoNA2017-51 |
| Date of Issue | 2018-01-11 (MoNA) |
| Conference Information | |
| Committee | MoNA |
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| Conference Date | 2018/1/18(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Campus Plaza Kyoto |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Network, Application of Machine Learning, Mobile Data, etc. |
| Chair | Ryoichi Shinkuma(Kyoto Univ.) |
| Vice Chair | Shigeaki Tagashira(Kansai Univ.) / Gen Kitagata(Tohoku Univ.) |
| Secretary | Shigeaki Tagashira(Kyushu Univ.) / Gen Kitagata(NTT) |
| Assistant | Takayuki Nishio(Kyoto Univ.) / Takato Saito(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Mobile Network and Applications |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Decentralized WLAN Access Point Selection through Reinforcement Learning |
| Sub Title (in English) | |
| Keyword(1) | Reinforcement learning |
| Keyword(2) | Q-Learning |
| Keyword(3) | AP selection |
| Keyword(4) | Handover |
| Keyword(5) | Wireless LAN |
| 1st Author's Name | Takuya Nakamura |
| 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.) |
| 5th Author's Name | Toshihisa Nabetani |
| 5th Author's Affiliation | TOSHIBA CORPORATION(TOSHIBA) |
| Date | 2018-01-19 |
| Paper # | MoNA2017-51 |
| Volume (vol) | vol.117 |
| Number (no) | MoNA-390 |
| Page | pp.pp.57-62(MoNA), |
| #Pages | 6 |
| Date of Issue | 2018-01-11 (MoNA) |