Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing
This study realizes firmware-agnostic line-of-sight (LOS) identification to extend the range of WiFi-sensing applications. We developed a beamforming feedback (BFF)-based LOS identification algorithm. BFF frames are transmitted for multiple-input multiple-output (MIMO) communications. They can be ob...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Open Journal of Vehicular Technology |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10631655/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832582290173067264 |
|---|---|
| author | Hiroki Shimomura Koji Yamamoto Takayuki Nishio Akihito Taya |
| author_facet | Hiroki Shimomura Koji Yamamoto Takayuki Nishio Akihito Taya |
| author_sort | Hiroki Shimomura |
| collection | DOAJ |
| description | This study realizes firmware-agnostic line-of-sight (LOS) identification to extend the range of WiFi-sensing applications. We developed a beamforming feedback (BFF)-based LOS identification algorithm. BFF frames are transmitted for multiple-input multiple-output (MIMO) communications. They can be obtained by capturing frames without custom firmware or specific chipsets and contain a beamforming feedback matrix (BFM) and subcarrier-averaged stream gain (SSG). These provide partial channel state information (CSI), and there are two major calculation steps involved from the CSI to the BFF: unquantized BFF (UQBFF) calculation and quantization. Focusing on the relationship between singular value decomposition and principal component analysis, we numerically demonstrated that the first column vectors of the BFM reflect the LOS/NLOS conditions. Therefore, the proposed BFF-based method extracts features from the first-column vectors of the BFM. In addition, SSGs were leveraged to improve the accuracy. To demonstrate the feasibility of the proposed method, we conducted experiments using commodity off-the-shelf devices compliant with the IEEE 802.11ac standard. In the experimental evaluation, the proposed BFF-based method achieved an identification accuracy of 75.0%, whereas the CSI-based method achieved an accuracy of 81.2%. Accuracy comparisons revealed that the accuracy degradation of the BFF-based identification from the CSI-based identification was primarily caused by UQBFF calculations rather than quantization. |
| format | Article |
| id | doaj-art-2295fe2e53364885ba3f65af465e6ec6 |
| institution | Kabale University |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-2295fe2e53364885ba3f65af465e6ec62025-01-30T00:04:04ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-0151024103510.1109/OJVT.2024.344040010631655Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi SensingHiroki Shimomura0https://orcid.org/0009-0008-7119-745XKoji Yamamoto1https://orcid.org/0000-0003-4106-3983Takayuki Nishio2https://orcid.org/0000-0003-1026-319XAkihito Taya3https://orcid.org/0000-0001-9074-9709Graduate School of Informatics, Kyoto University, Kyoto, JapanFaculty of Information and Human Sciences, Kyoto Institute of Technology, Kyoto, JapanSchool of Engineering, Tokyo Institute of Technology, Tokyo, JapanInstitute of Industrial Science, The University of Tokyo, Tokyo, JapanThis study realizes firmware-agnostic line-of-sight (LOS) identification to extend the range of WiFi-sensing applications. We developed a beamforming feedback (BFF)-based LOS identification algorithm. BFF frames are transmitted for multiple-input multiple-output (MIMO) communications. They can be obtained by capturing frames without custom firmware or specific chipsets and contain a beamforming feedback matrix (BFM) and subcarrier-averaged stream gain (SSG). These provide partial channel state information (CSI), and there are two major calculation steps involved from the CSI to the BFF: unquantized BFF (UQBFF) calculation and quantization. Focusing on the relationship between singular value decomposition and principal component analysis, we numerically demonstrated that the first column vectors of the BFM reflect the LOS/NLOS conditions. Therefore, the proposed BFF-based method extracts features from the first-column vectors of the BFM. In addition, SSGs were leveraged to improve the accuracy. To demonstrate the feasibility of the proposed method, we conducted experiments using commodity off-the-shelf devices compliant with the IEEE 802.11ac standard. In the experimental evaluation, the proposed BFF-based method achieved an identification accuracy of 75.0%, whereas the CSI-based method achieved an accuracy of 81.2%. Accuracy comparisons revealed that the accuracy degradation of the BFF-based identification from the CSI-based identification was primarily caused by UQBFF calculations rather than quantization.https://ieeexplore.ieee.org/document/10631655/Channel state informationbeamforming feedbackfirmware-agnostic WiFi sensingline-of-sight identificationwireless local area networks |
| spellingShingle | Hiroki Shimomura Koji Yamamoto Takayuki Nishio Akihito Taya Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing IEEE Open Journal of Vehicular Technology Channel state information beamforming feedback firmware-agnostic WiFi sensing line-of-sight identification wireless local area networks |
| title | Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing |
| title_full | Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing |
| title_fullStr | Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing |
| title_full_unstemmed | Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing |
| title_short | Beamforming Feedback-Based Line-of-Sight Identification Toward Firmware-Agnostic WiFi Sensing |
| title_sort | beamforming feedback based line of sight identification toward firmware agnostic wifi sensing |
| topic | Channel state information beamforming feedback firmware-agnostic WiFi sensing line-of-sight identification wireless local area networks |
| url | https://ieeexplore.ieee.org/document/10631655/ |
| work_keys_str_mv | AT hirokishimomura beamformingfeedbackbasedlineofsightidentificationtowardfirmwareagnosticwifisensing AT kojiyamamoto beamformingfeedbackbasedlineofsightidentificationtowardfirmwareagnosticwifisensing AT takayukinishio beamformingfeedbackbasedlineofsightidentificationtowardfirmwareagnosticwifisensing AT akihitotaya beamformingfeedbackbasedlineofsightidentificationtowardfirmwareagnosticwifisensing |