| Presentation | 2018-05-24 [Invited Talk] Wireless Link Quality Prediction And Wireless Control Through Machine Learning Takayuki Nishio, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In this talk, wireless link quality prediction and control methods based on supervised learning from sensing information are introduced. In millimeter-wave (mmWave) communication, throughput estimation using camera imagery has been studied. Human blockage in mmWave communication sharply degrades link quality, and the blockage can be predicted from imagery since camera imagery contains geometry of transmitter, receiver, and pedestrian, and shape and mobility of pedestrian, which characterize human blockage in mmWave communications. Experimental results demonstrate that the scheme predicts throughput from imagery. In a spectrum sharing system, we have proposed a scheme to estimate region where harmful interference could occur and update primary exclusive region (PER) in order not to cause harmful interference. Support vector machine (SVM) learns interference region and decides appropriate boundary for PER. The simulation results demonstrate that the area of PER with the proposed scheme is smaller than that of the fixed circular PER setting with the same interference probability. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Machine Learning / Supervised Learning / Wireless Networks / Link Quality Prediction / mmWave |
| Paper # | SR2018-1 |
| Date of Issue | 2018-05-17 (SR) |
| Conference Information | |
| Committee | SR |
|---|---|
| Conference Date | 2018/5/24(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo big sight |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Technical Exhibition, Machine Learning, AI |
| Chair | Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) |
| Vice Chair | Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) |
| Secretary | Masayuki Ariyoshi(NICT) / Suguru Kameda(ATR) |
| Assistant | Mamiko Inamori(Tokai Univ.) / Hiroyuki Shiba(NTT) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(NIT, Akashi College) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Invited Talk] Wireless Link Quality Prediction And Wireless Control Through Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Machine Learning |
| Keyword(2) | Supervised Learning |
| Keyword(3) | Wireless Networks |
| Keyword(4) | Link Quality Prediction |
| Keyword(5) | mmWave |
| Keyword(6) | |
| 1st Author's Name | Takayuki Nishio |
| 1st Author's Affiliation | Kyoto University(Kyoto Univ.) |
| Date | 2018-05-24 |
| Paper # | SR2018-1 |
| Volume (vol) | vol.118 |
| Number (no) | SR-57 |
| Page | pp.pp.1-6(SR), |
| #Pages | 6 |
| Date of Issue | 2018-05-17 (SR) |