| Presentation | 2020-11-27 [Invited Lecture] Two-step Path Loss Prediction Method by Artificial Neural Network for Wireless Service Area Planning Kentaro Saito, Yongri JIN, CheChia Kang, Jun-ichi Takada, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, wireless network systems are utilized in various industry fields and the wireless service area planning became one of the important tasks to realize efficient and high-quality wireless communication service. The machine learning technology attracts the interests of researchers to improve the efficiency of the area planning task because the radio propagation loss in unknown locations can be predicted by the training data without explicit algorithms. Our previous work showed that the path loss (PL) characteristics become complicated in the high PL region, and it can degrade the entire prediction accuracy. In this paper, we propose the two-step PL prediction method by the artificial neural network (ANN) to solve the issue. Firstly, the area is classified into several zones according to the PL range. And then the PL is predicted by ANNs that were trained for respective zones. Our proposal was evaluated by the ray-tracing simulation data, and the result showed that it improved the root mean square error (RMSE) of PL prediction from 7.9 dB to 4.1 dB. The method is expected to be utilized for the wireless service area planning in various environments. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Cell planning / Indoor propagation / Machine learning / Neural network / Path loss prediction / propagation simulation |
| Paper # | SRW2020-38 |
| Date of Issue | 2020-11-19 (SRW) |
| Conference Information | |
| Committee | SRW / SeMI / CNR |
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| Conference Date | 2020/11/26(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IoT Workshop |
| Chair | Satoshi Denno(Okayama Univ.) / Susumu Ishihara(Shizuoka Univ.) / Kazunori Takashio(Keio Univ.) |
| Vice Chair | Keiichi Mizutani(Kyoto Univ.) / Kentaro Saito(Tokyo Inst. of Tech.) / Hanako Noda(Anritsu) / Kazuya Monden(Hitachi) / Koji Yamamoto(Kyoto Univ.) / Masayuki Kanbara(NAIST) / Yoshihiko Murakawa(Fujitsu Labs.) |
| Secretary | Keiichi Mizutani(NTT) / Kentaro Saito(NIigata Univ.) / Hanako Noda(Kyoto Univ.) / Kazuya Monden(Osaka Univ.) / Koji Yamamoto(Hitachi) / Masayuki Kanbara(Waseda Univ.) / Yoshihiko Murakawa(Shibaura Inst. of Tech.) |
| Assistant | Masaaki Fuse(Anritsu) / Akihito Noda(Nanzan Univ.) / Yuki Katsumata(NTT DOCOMO) / Yu Nakayama(Tokyo Univ. of Agri. and Tech.) / Akira Uchiyama(Osaka Univ.) / Yuka Kobayashi(Toshiba) / Masanori Yokoyama(ＮＴＴ) |
| Paper Information | |
| Registration To | Technical Committee on Short Range Wireless Communications / Technical Committee on Sensor Network and Mobile Intelligence / Technical Committee on Cloud Network Robotics |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Invited Lecture] Two-step Path Loss Prediction Method by Artificial Neural Network for Wireless Service Area Planning |
| Sub Title (in English) | |
| Keyword(1) | Cell planning |
| Keyword(2) | Indoor propagation |
| Keyword(3) | Machine learning |
| Keyword(4) | Neural network |
| Keyword(5) | Path loss prediction |
| Keyword(6) | propagation simulation |
| 1st Author's Name | Kentaro Saito |
| 1st Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech.) |
| 2nd Author's Name | Yongri JIN |
| 2nd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech.) |
| 3rd Author's Name | CheChia Kang |
| 3rd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech.) |
| 4th Author's Name | Jun-ichi Takada |
| 4th Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech.) |
| Date | 2020-11-27 |
| Paper # | SRW2020-38 |
| Volume (vol) | vol.120 |
| Number (no) | SRW-260 |
| Page | pp.pp.61-66(SRW), |
| #Pages | 6 |
| Date of Issue | 2020-11-19 (SRW) |