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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
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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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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)  
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
Date of Issue 2022-07-06 (SeMI) 


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