University of Oulu

S. Itahara, S. Kondo, K. Yamashita, T. Nishio, K. Yamamoto and Y. Koda, "Beamforming Feedback-Based Model-Driven Angle of Departure Estimation Toward Legacy Support in WiFi Sensing: An Experimental Study," in IEEE Access, vol. 10, pp. 59737-59747, 2022, doi: 10.1109/ACCESS.2022.3180178

Beamforming feedback-based model-driven angle of departure estimation toward legacy support in WiFi sensing : an experimental study

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Author: Itahara, Sohei1; Kondo, Sota1; Yamashita, Kota1;
Organizations: 1Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan
2School of Engineering, Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo 152-8550, Japan
3Centre of Wireless Communications, University of Oulu, 90014 Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022071451678
Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-07-14
Description:

Abstract

In this study, we experimentally validated the possibility of estimating the angle of departure (AoD) using multiple signal classification (MUSIC) with only WiFi control frames for beamforming feedback (BFF), defined in IEEE 802.11ac/ax. The examined BFF-based MUSIC is a model-driven algorithm that does not require a pre-obtained database. This is in contrast with most existing BFF-based sensing techniques, which are data-driven and require a pre-obtained database. Moreover, BFF-based MUSIC affords an alternative AoD estimation method without requiring access to the channel state information (CSI). Extensive experimental and numerical evaluations demonstrate that BFF-based MUSIC can successfully estimate the AoDs for multiple propagation paths. Moreover, the evaluations performed in this study reveal that BFF-based MUSIC, where BFF is a highly compressed version of CSI in IEEE 802.11ac/ax, achieves an error of AoD estimation that is comparable to that of CSI-based MUSIC.

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Series: IEEE access
ISSN: 2169-3536
ISSN-E: 2169-3536
ISSN-L: 2169-3536
Volume: 10
Pages: 59737 - 59747
DOI: 10.1109/access.2022.3180178
OADOI: https://oadoi.org/10.1109/access.2022.3180178
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This work was supported in part by the Research and Development through the Ministry of Internal Affairs and Communications/Strategic Information and Communications R&D Promotion Programme (MIC/SCOPE) under Grant JP196000002, and in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI under Grant JP18H01442.
Copyright information: © The Author(s) 2022. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/