Presentation | 2020-07-08 Feasibility Study on Blockage Prediction with Machine Learning in Outdoor mm-Wave Environment Satoshi Ito, Shoichiro Mihara, Takahide Murakami, Hiroyuki Shinbo, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | mm-wave bands have large blockage loss in comparison with sub 6 GHz band. Therefore, we proposed the system that has multiple mm-wave band base stations and is able to keep wireless link connection by predicting blockage impact using some pictures and switching to another mm-wave band base station in advance. In around 50 m area covered by multiple mm-wave band base stations, precise prediction method for proper switching is needed to keep link connection. Conventional method which use CNN (Convolutional Neural Network) is proposed for one-to-one indoor environment. On the other hand, nano-area differs in terms of longer transmission distance of around 50 m and wider blocker distribution than conventional study. In this paper, we show prediction results and considerations when some vehicle and human body move within 50 m transmission distance in outdoor environment. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | mm-Wave / Blockage Prediction / Machine Learning / Nano-area |
Paper # | RCS2020-59 |
Date of Issue | 2020-07-01 (RCS) |
Conference Information | |
Committee | SR / NS / SeMI / RCC / RCS |
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Conference Date | 2020/7/8(3days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Online |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Communication and Network Technology of the AI Age, M2M (Machine-to-Machine),D2D (Device-to-Device),IoT(Internet of Things), etc |
Chair | Masayuki Ariyoshi(NEC) / Akihiro Nakao(Univ. of Tokyo) / Susumu Ishihara(Shizuoka Univ.) / HUAN-BANG LI(NICT) / Eiji Okamoto(Nagoya Inst. of Tech.) |
Vice Chair | Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Tetsuya Oishi(NTT) / Kazuya Monden(Hitachi) / Koji Yamamoto(Kyoto Univ.) / Shunichi Azuma(Nagoya Univ.) / Koji Ishii(Kagawa Univ.) / Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) |
Secretary | Suguru Kameda(ATR) / Osamu Takyu(Univ. of Electro-Comm.) / Kentaro Ishidu(Mie Univ.) / Tetsuya Oishi(NTT) / Kazuya Monden(Chuo Univ.) / Koji Yamamoto(Kyoto Univ.) / Shunichi Azuma(Osaka Univ.) / Koji Ishii(Hitachi) / Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(CRIEPI) / Tomoya Tandai(Osaka Univ.) |
Assistant | Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) / Shinya Kawano(NTT) / Yuki Katsumata(NTT DOCOMO) / Yu Nakayama(Tokyo Univ. of Agri. and Tech.) / Akira Uchiyama(Osaka Univ.) / SHAN LIN(NICT) / Masaki Ogura(Osaka Univ.) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) |
Paper Information | |
Registration To | Technical Committee on Smart Radio / Technical Committee on Network Systems / Technical Committee on Sensor Network and Mobile Intelligence / Technical Committee on Reliable Communication and Control / Technical Committee on Radio Communication Systems |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Feasibility Study on Blockage Prediction with Machine Learning in Outdoor mm-Wave Environment |
Sub Title (in English) | |
Keyword(1) | mm-Wave |
Keyword(2) | Blockage Prediction |
Keyword(3) | Machine Learning |
Keyword(4) | Nano-area |
1st Author's Name | Satoshi Ito |
1st Author's Affiliation | KDDI Research, Inc.(KDDI Research, Inc.) |
2nd Author's Name | Shoichiro Mihara |
2nd Author's Affiliation | KDDI Research, Inc.(KDDI Research, Inc.) |
3rd Author's Name | Takahide Murakami |
3rd Author's Affiliation | KDDI Research, Inc.(KDDI Research, Inc.) |
4th Author's Name | Hiroyuki Shinbo |
4th Author's Affiliation | KDDI Research, Inc.(KDDI Research, Inc.) |
Date | 2020-07-08 |
Paper # | RCS2020-59 |
Volume (vol) | vol.120 |
Number (no) | RCS-89 |
Page | pp.pp.7-12(RCS), |
#Pages | 6 |
Date of Issue | 2020-07-01 (RCS) |