| Presentation | 2021-09-09 [Invited Talk] Deep Learning based position estimation method using WLAN CSI feedback Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Thanks to the great advances in wireless communication systems, many types of the wireless terminals are available. It is expected that various novel services emerge in Society 5.0 that is based on Internet of Things (IoT) by a high degree of convergence between cyberspace (virtual space) and physical space (real space). This report proposes that the deep learning baesd position estimation using the channel state information (CSI) feedback in wireless LAN systems. The proposed position estimation is based on a finger print method and requires only single access point (AP). The indoor environment is considered to be as a target. In the proposed model, recurrent neural network (RNN) was used to utilize the time domain characteristics and the input features for the model was provided based on the angle of arrival (AoA) estimation algorithms. To evaluate the estimation accuracy, we developed the autonomous locomotion robot and measured the wireless LAN feedbacks and position information of the robot. The accuracy of the position estimation and lifetime of the model are discussed in this report. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Position estimation / Wireless LAN / Machine learning / Mobility robot |
| Paper # | CQ2021-45 |
| Date of Issue | 2021-09-02 (CQ) |
| Conference Information | |
| Committee | CQ |
|---|---|
| Conference Date | 2021/9/9(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Wireless Communications Quality, 6G, IoT, Resource Management, Wireless Transmission, Cross layer Technologies, etc. |
| Chair | Jun Okamoto(NTT) |
| Vice Chair | Takefumi Hiraguri(Nippon Inst. of Tech.) / Gou Hasegawa(Tohoku Univ.) |
| Secretary | Takefumi Hiraguri(NTT) / Gou Hasegawa(Ritsumeikan Univ.) |
| Assistant | Yoshiaki Nishikawa(NEC) / Ryoichi Kataoka(KDDI Research) / Kimiko Kawashima(NTT) |
| Paper Information | |
| Registration To | Technical Committee on Communication Quality |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Invited Talk] Deep Learning based position estimation method using WLAN CSI feedback |
| Sub Title (in English) | |
| Keyword(1) | Position estimation |
| Keyword(2) | Wireless LAN |
| Keyword(3) | Machine learning |
| Keyword(4) | Mobility robot |
| 1st Author's Name | Riichi Kudo |
| 1st Author's Affiliation | NTT(NTT) |
| 2nd Author's Name | Kahoko Takahashi |
| 2nd Author's Affiliation | NTT(NTT) |
| 3rd Author's Name | Tomoki Murakami |
| 3rd Author's Affiliation | NTT(NTT) |
| 4th Author's Name | Tomoaki Ogawa |
| 4th Author's Affiliation | NTT(NTT) |
| Date | 2021-09-09 |
| Paper # | CQ2021-45 |
| Volume (vol) | vol.121 |
| Number (no) | CQ-173 |
| Page | pp.pp.40-45(CQ), |
| #Pages | 6 |
| Date of Issue | 2021-09-02 (CQ) |