| Presentation | 2021-11-10 Channel Parameter Estimation by using Environmental Features Inocent Calist, Zhiqiang Li, Minseok Kim, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Recent developments in the next generation of mobile communication and the application of the Internet of things has raised the need to develop more accurate channel models. This work presents the development of a supervised based machine learning (ML) prediction model for large scale channel parameters (LSCPs) estimation by analyzing the reflected multipath ray's information. The reflected rays varies with the morphology structure of the propagation environment, hence a dynamic LSCPs predictive model can be realized. The input parameters to the prediction model are transmitter (TX) and receiver (RX) positional coordinates, and the reflected rays' information such as the delay, angle of arrival, angle of departure, elevation angle of arrival, elevation angle of departure, and power gain. The proposed model was implemented using Random Forest (RF) which can predict both linear and nonlinear data. Ray tracing (RT) simulation was performed to calculate the input measurement dataset of the LSCPs, and the input information of the reflected rays. Cross validation was then utilized to validate the model. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Machine learning / parameter estimation / channel / rays information / prediction model |
| Paper # | AP2021-106 |
| Date of Issue | 2021-11-03 (AP) |
| Conference Information | |
| Committee | AP / RCS |
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| Conference Date | 2021/11/10(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | NBC-Bekkan (Nagasaki) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Adaptive Antenna, Equalization, Interference Canceler, MIMO, Wireless Communications, etc. |
| Chair | Hiroshi Yamada(Niigata Univ.) / Eiji Okamoto(Nagoya Inst. of Tech.) |
| Vice Chair | Mitoshi Fujimoto(Fukui Univ) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) / Fumihide Kojima(NICT) |
| Secretary | Mitoshi Fujimoto(NTT DOCOMO) / Toshihiko Nishimura(National Defense Academy) / Tomoya Tandai(NEC) / Fumihide Kojima(Panasonic) |
| Assistant | Dr. Kim(Niigata 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 Antennas and Propagation / Technical Committee on Radio Communication Systems |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Channel Parameter Estimation by using Environmental Features |
| Sub Title (in English) | |
| Keyword(1) | Machine learning |
| Keyword(2) | parameter estimation |
| Keyword(3) | channel |
| Keyword(4) | rays information |
| Keyword(5) | prediction model |
| 1st Author's Name | Inocent Calist |
| 1st Author's Affiliation | Niigata University(Niigata Univ.) |
| 2nd Author's Name | Zhiqiang Li |
| 2nd Author's Affiliation | Niigata University(Niigata Univ.) |
| 3rd Author's Name | Minseok Kim |
| 3rd Author's Affiliation | Niigata University(Niigata Univ.) |
| Date | 2021-11-10 |
| Paper # | AP2021-106 |
| Volume (vol) | vol.121 |
| Number (no) | AP-233 |
| Page | pp.pp.34-38(AP), |
| #Pages | 5 |
| Date of Issue | 2021-11-03 (AP) |