Paper Abstract and Keywords |
Presentation |
2022-07-15 11:55
Vision-Aided Frame-Capture-Based CSI Recomposition for WiFi Sensing: A Multimodal Approach Hiroki Shimomura, Takamochi Kanda, Koji Yamamoto (Kyoto Univ.), Takayuki Nishio (Kyoto Univ./Tokyo Tech.), Akihito Taya (Kyoto Univ./Aoyama Gakuin Univ.) SeMI2022-42 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recompositing channel state information (CSI) from the beamforming feedback matrix (BFM), which is a compressed version of CSI and can be captured because of its lack of encryption, is an alternative way of implementing firmware-agnostic WiFi sensing. In this study, we propose the use of camera images toward the accuracy enhancement of CSI recomposition from BFM. The key motivation for this vision-aided CSI recomposition is to draw a first-hand insight that the BFM does not fully involve spatial information to recomposite CSI and that this could be compensated by camera images. To leverage the camera images, we use multimodal deep learning, where the two modalities, i.e., images and BFMs, are integrated to recomposite the CSI.
We conducted experiments using IEEE 802.11ac devices.
The experimental results confirmed that the recomposition accuracy of the proposed multimodal framework is improved compared to the single-modal framework only using images or BFMs. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Channel state information / Beamforming feedback matrix / multimodal learning / IEEE 802.11ac / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 108, SeMI2022-42, pp. 98-102, July 2022. |
Paper # |
SeMI2022-42 |
Date of Issue |
2022-07-06 (SeMI) |
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) |
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SeMI2022-42 |
Conference Information |
Committee |
NS SR RCS SeMI RCC |
Conference Date |
2022-07-13 - 2022-07-15 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
The Kanazawa Theatre + Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Distributed Wireless Network, M2M (Machine-to-Machine),D2D (Device-to-Device),IoT(Internet of Things), etc |
Paper Information |
Registration To |
SeMI |
Conference Code |
2022-07-NS-SR-RCS-SeMI-RCC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Vision-Aided Frame-Capture-Based CSI Recomposition for WiFi Sensing: A Multimodal Approach |
Sub Title (in English) |
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Keyword(1) |
Channel state information |
Keyword(2) |
Beamforming feedback matrix |
Keyword(3) |
multimodal learning |
Keyword(4) |
IEEE 802.11ac |
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1st Author's Name |
Hiroki Shimomura |
1st Author's Affiliation |
Kyoto University (Kyoto Univ.) |
2nd Author's Name |
Takamochi Kanda |
2nd Author's Affiliation |
Kyoto University (Kyoto Univ.) |
3rd Author's Name |
Koji Yamamoto |
3rd Author's Affiliation |
Kyoto University (Kyoto Univ.) |
4th Author's Name |
Takayuki Nishio |
4th Author's Affiliation |
Kyoto University/Tokyo Institute of Technology (Kyoto Univ./Tokyo Tech.) |
5th Author's Name |
Akihito Taya |
5th Author's Affiliation |
Kyoto University/Aoyama Gakuin University (Kyoto Univ./Aoyama Gakuin Univ.) |
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Speaker |
Author-1 |
Date Time |
2022-07-15 11:55:00 |
Presentation Time |
25 minutes |
Registration for |
SeMI |
Paper # |
SeMI2022-42 |
Volume (vol) |
vol.122 |
Number (no) |
no.108 |
Page |
pp.98-102 |
#Pages |
5 |
Date of Issue |
2022-07-06 (SeMI) |
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