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| Presentation | 2021-09-09 14:05 [Invited Talk] Deep Learning based position estimation method using WLAN CSI feedback Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa (NTT)  CQ2021-45 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (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) |
| (in English) | Position estimation / Wireless LAN / Machine learning / Mobility robot / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 173, CQ2021-45, pp. 40-45, Sept. 2021. | |
| Paper # | CQ2021-45 | |
| Date of Issue | 2021-09-02 (CQ) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| Download PDF | CQ2021-45 |
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| Conference Information | |
| Committee | CQ MIKA |
| Conference Date | 2021-09-09 - 2021-09-10 |
| 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. |
| Paper Information | |
| Registration To | CQ |
| Conference Code | 2021-09-CQ-MIKA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | 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 |
| Keyword(5) | |
| Keyword(6) | |
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| Keyword(8) | |
| 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) |
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| Speaker | Author-1 |
| Date Time | 2021-09-09 14:05:00 |
| Presentation Time | 35 minutes |
| Registration for | CQ |
| Paper # | CQ2021-45 |
| Volume (vol) | vol.121 |
| Number (no) | no.173 |
| Page | pp.40-45 |
| #Pages | 6 |
| Date of Issue | 2021-09-02 (CQ) |
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