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Paper Abstract and Keywords
Presentation 2026-05-14 09:40
Subcarrier Selection Method Based on CSI Correlation for Reducing Computational Cost in Wi-Fi Indoor Localization
Tastsunari Sakai, Liuyi Yang, Zhiyi Zhu, Patrick Finnerty, Chikara Ohta (Kobe Univ.) SeMI2026-2
Abstract (in Japanese) (See Japanese page) 
(in English) Indoor localization using Wi‑Fi Channel State Information (CSI) and machine learning typically exploits all subcarriers to achieve high positioning accuracy. However, the resulting high input dimensionality leads to large computational cost during training and inference. This study focuses on the effectiveness of subcarrier reduction and proposes a method for selecting subcarriers effective for localization based on CSI features derived from the unbiased autocorrelation function. By eliminating redundant subcarriers, the proposed method reduces learning cost. Real‑world experiments using a deep learning–based indoor positioning system evaluated localization accuracy and computation time. The results show that the proposed method reduces computation time while maintaining positioning accuracy, enabling efficient indoor localization.
Keyword (in Japanese) (See Japanese page) 
(in English) CSI / Auto Correlation / Indoor Localization / Subcarrier Selection / Machine Learning / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 15, SeMI2026-2, pp. 7-12, May 2026.
Paper # SeMI2026-2 
Date of Issue 2026-05-07 (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)
Download PDF SeMI2026-2

Conference Information
Committee SeMI IPSJ-MBL IPSJ-ITS IPSJ-DPS  
Conference Date 2026-05-13 - 2026-05-15 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SeMI 
Conference Code 2026-05-SeMI-MBL-ITS-DPS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Subcarrier Selection Method Based on CSI Correlation for Reducing Computational Cost in Wi-Fi Indoor Localization 
Sub Title (in English)  
Keyword(1) CSI  
Keyword(2) Auto Correlation  
Keyword(3) Indoor Localization  
Keyword(4) Subcarrier Selection  
Keyword(5) Machine Learning  
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1st Author's Name Tastsunari Sakai  
1st Author's Affiliation Kobe University (Kobe Univ.)
2nd Author's Name Liuyi Yang  
2nd Author's Affiliation Kobe University (Kobe Univ.)
3rd Author's Name Zhiyi Zhu  
3rd Author's Affiliation Kobe University (Kobe Univ.)
4th Author's Name Patrick Finnerty  
4th Author's Affiliation Kobe University (Kobe Univ.)
5th Author's Name Chikara Ohta  
5th Author's Affiliation Kobe University (Kobe Univ.)
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Speaker Author-1 
Date Time 2026-05-14 09:40:00 
Presentation Time 25 minutes 
Registration for SeMI 
Paper # SeMI2026-2 
Volume (vol) vol.126 
Number (no) no.15 
Page pp.7-12 
#Pages 6 
Date of Issue 2026-05-07 (SeMI) 

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