| Presentation | 2021-03-03 Performance Evaluation of a Machine Learning-Based Rate Selection Scheme for Wireless LAN in the Presence of Contention and Hidden Nodes Souki Watanabe, Hiraku Okada, Ben Naila Chedlia, Masaaki Katayama, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In IEEE802.11, the transmission rate is specified in multiple steps by the Modulation and Coding Scheme (MCS), which is an index of combinations of modulation schemes and coding rates. In order to maximize throughput, it is necessary to select an appropriate transmission rate for the communication environment. However, the actual communication environment is complicated by many factors, such as the effects of fading, contention by other communications, and hidden terminal problem. In our previous study, we investigated a rate adaptation method for complex communication environments by applying machine learning. However, only one-to-one communication experiments were conducted, and the results were not sufficiently compared with those of conventional methods. In this paper, we show the superiority of the proposed method by comparing and verifying the transmission rate selection using LightGBM and the conventional method in the presence of competing communications. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | IEEE 802.11 / machine learning / rate adaptation |
| Paper # | RCS2020-203 |
| Date of Issue | 2021-02-24 (RCS) |
| Conference Information | |
| Committee | RCS / SR / SRW |
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| Conference Date | 2021/3/3(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Chair | Eiji Okamoto(Nagoya Inst. of Tech.) / Masayuki Ariyoshi(NEC) / Satoshi Denno(Okayama Univ.) |
| Vice Chair | Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) / Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Keiichi Mizutani(Kyoto Univ.) / Kentaro Saito(Tokyo Inst. of Tech.) / Hanako Noda(Anritsu) |
| Secretary | Fumiaki Maehara(Kyushu Univ.) / Toshihiko Nishimura(NEC) / Tomoya Tandai(ATR) / Suguru Kameda(Univ. of Electro-Comm.) / Osamu Takyu(Mie Univ.) / Kentaro Ishidu(NTT) / Keiichi Mizutani(NIigata Univ.) / Kentaro Saito / Hanako Noda |
| Assistant | Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) / Masaaki Fuse(Anritsu) / Akihito Noda(Nanzan Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Performance Evaluation of a Machine Learning-Based Rate Selection Scheme for Wireless LAN in the Presence of Contention and Hidden Nodes |
| Sub Title (in English) | |
| Keyword(1) | IEEE 802.11 |
| Keyword(2) | machine learning |
| Keyword(3) | rate adaptation |
| 1st Author's Name | Souki Watanabe |
| 1st Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 2nd Author's Name | Hiraku Okada |
| 2nd Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 3rd Author's Name | Ben Naila Chedlia |
| 3rd Author's Affiliation | Nagoya University(Nagoya Univ.) |
| 4th Author's Name | Masaaki Katayama |
| 4th Author's Affiliation | Nagoya University(Nagoya Univ.) |
| Date | 2021-03-03 |
| Paper # | RCS2020-203 |
| Volume (vol) | vol.120 |
| Number (no) | RCS-404 |
| Page | pp.pp.1-6(RCS), |
| #Pages | 6 |
| Date of Issue | 2021-02-24 (RCS) |