| Presentation | 2021-01-20 A Study of Online Training Method for Image-based Wireless Link Quality Prediction Sohei Itahara, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve the reliability of wireless communications, especially at higher frequencies (e.g., millimeter-wave and terahertz technologies), through predictive handover and beamforming to solve line- of-sight (LOS) blockage problem. In this study, a real-time online trainable wireless link quality prediction system was proposed; the system was implemented with commercially available laptops. The proposed system collects datasets, updates a model, and infers the received power in real-time. The experimental evaluation was conducted using 5 GHz Wi-Fi, where received signal strength could be degraded by 10 dB when the LOS path was blocked by large obstacles. The experimental results demonstrate that the prediction model is updated in real-time, adapts to the change in environment, and predicts the time-varying Wi-Fi received power accurately. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | higher frequency communications / machine learning / camera assisted / implementation / 5G / beyond 5G |
| Paper # | SeMI2020-44 |
| Date of Issue | 2021-01-13 (SeMI) |
| Conference Information | |
| Committee | SeMI |
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| Conference Date | 2021/1/20(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Susumu Ishihara(Shizuoka Univ.) |
| Vice Chair | Kazuya Monden(Hitachi) / Koji Yamamoto(Kyoto Univ.) |
| Secretary | Kazuya Monden(Kyoto Univ.) / Koji Yamamoto(Cyber Univ.) |
| Assistant | Yuki Katsumata(NTT DOCOMO) / Yu Nakayama(Tokyo Univ. of Agri. and Tech.) / Akira Uchiyama(Osaka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Sensor Network and Mobile Intelligence |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study of Online Training Method for Image-based Wireless Link Quality Prediction |
| Sub Title (in English) | |
| Keyword(1) | higher frequency communications |
| Keyword(2) | machine learning |
| Keyword(3) | camera assisted |
| Keyword(4) | implementation |
| Keyword(5) | 5G |
| Keyword(6) | beyond 5G |
| 1st Author's Name | Sohei Itahara |
| 1st Author's Affiliation | Kyoto University(Kyoto Univ) |
| 2nd Author's Name | Takayuki Nishio |
| 2nd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
| 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) |
| Date | 2021-01-20 |
| Paper # | SeMI2020-44 |
| Volume (vol) | vol.120 |
| Number (no) | SeMI-315 |
| Page | pp.pp.7-9(SeMI), |
| #Pages | 3 |
| Date of Issue | 2021-01-13 (SeMI) |