Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects

Ankit Regmi; Praneeth Susarla; Peize Zhang; Nuutti Tervo; Miguel Bordallo Lopez; Olli Silven; Pekka Kyösti; Marko E. Leinonen; Aarno Pärssinen

doi:10.23919/EuCAP60739.2024.10501593

Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects

Ankit Regmi, Praneeth Susarla, Peize Zhang, Nuutti Tervo, Miguel Bordallo Lopez, Olli Silven, Pekka Kyösti, Marko E. Leinonen, Aarno Pärssinen

Not published at VTT

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Abstract

To enable a wide range of joint communications and sensing applications, future channel models must support dynamic variations of the propagation environment. Moreover, when discovering sensing applications, it is essential to connect physical objects and actions to the radio channel characteristics. In this paper, we perform computer vision (CV) aided automatic mapping and showcase that channel measurements can be linked to the dynamic actions and objects in the environment, thus supporting sensing applications. The proposed method employs a vector network analyzer-based channel measurement system operating at 300 GHz and a camera to enable CV for tracking the object in the radio link. Using human hand as the blockage object, the CV-extracted coordinates and the measured channel responses are combined to generate radio channel footprints for different hand movements.

Original language	English
Title of host publication	18th European Conference on Antennas and Propagation, EuCAP 2024
Publisher	IEEE Institute of Electrical and Electronic Engineers
ISBN (Electronic)	9788831299091
DOIs	https://doi.org/10.23919/EuCAP60739.2024.10501593
Publication status	Published - 2024
MoE publication type	A4 Article in a conference publication
Event	18th European Conference on Antennas and Propagation, EuCAP 2024 - Glasgow, United Kingdom Duration: 17 Mar 2024 → 22 Mar 2024

Conference

Conference	18th European Conference on Antennas and Propagation, EuCAP 2024
Country/Territory	United Kingdom
City	Glasgow
Period	17/03/24 → 22/03/24

Funding

This research was supported by the Business Finland project RFSampo (3071/31/2021), in part by the Research Council of Finland (former Academy of Finland) 6G Flagship Pro-gramme (Grant Number: 346208), and the Horizon Europe CONVERGE project (Grant 101094831). The authors would like to thank Keysight Inc. for the measurement equipment donation.

Keywords

6G
Blockage
channel measurements
computer vision
Doppler
sensing
upper millimeter-wave

Access to Document

10.23919/EuCAP60739.2024.10501593

Cite this

Regmi, A., Susarla, P., Zhang, P., Tervo, N., Lopez, M. B., Silven, O., Kyösti, P., Leinonen, M. E., & Pärssinen, A. (2024). Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects. In 18th European Conference on Antennas and Propagation, EuCAP 2024 IEEE Institute of Electrical and Electronic Engineers. https://doi.org/10.23919/EuCAP60739.2024.10501593

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title = "Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects",

abstract = "To enable a wide range of joint communications and sensing applications, future channel models must support dynamic variations of the propagation environment. Moreover, when discovering sensing applications, it is essential to connect physical objects and actions to the radio channel characteristics. In this paper, we perform computer vision (CV) aided automatic mapping and showcase that channel measurements can be linked to the dynamic actions and objects in the environment, thus supporting sensing applications. The proposed method employs a vector network analyzer-based channel measurement system operating at 300 GHz and a camera to enable CV for tracking the object in the radio link. Using human hand as the blockage object, the CV-extracted coordinates and the measured channel responses are combined to generate radio channel footprints for different hand movements.",

keywords = "6G, Blockage, channel measurements, computer vision, Doppler, sensing, upper millimeter-wave",

author = "Ankit Regmi and Praneeth Susarla and Peize Zhang and Nuutti Tervo and Lopez, {Miguel Bordallo} and Olli Silven and Pekka Ky{\"o}sti and Leinonen, {Marko E.} and Aarno P{\"a}rssinen",

note = "Publisher Copyright: {\textcopyright} 2024 18th European Conference on Antennas and Propagation, EuCAP 2024. All Rights Reserved.; 18th European Conference on Antennas and Propagation, EuCAP 2024 ; Conference date: 17-03-2024 Through 22-03-2024",

year = "2024",

doi = "10.23919/EuCAP60739.2024.10501593",

language = "English",

booktitle = "18th European Conference on Antennas and Propagation, EuCAP 2024",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

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Regmi, A, Susarla, P, Zhang, P, Tervo, N, Lopez, MB, Silven, O, Kyösti, P, Leinonen, ME & Pärssinen, A 2024, Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects. in 18th European Conference on Antennas and Propagation, EuCAP 2024. IEEE Institute of Electrical and Electronic Engineers, 18th European Conference on Antennas and Propagation, EuCAP 2024, Glasgow, United Kingdom, 17/03/24. https://doi.org/10.23919/EuCAP60739.2024.10501593

Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects. / Regmi, Ankit; Susarla, Praneeth; Zhang, Peize et al.
18th European Conference on Antennas and Propagation, EuCAP 2024. IEEE Institute of Electrical and Electronic Engineers, 2024.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects

AU - Regmi, Ankit

AU - Susarla, Praneeth

AU - Zhang, Peize

AU - Tervo, Nuutti

AU - Lopez, Miguel Bordallo

AU - Silven, Olli

AU - Kyösti, Pekka

AU - Leinonen, Marko E.

AU - Pärssinen, Aarno

PY - 2024

Y1 - 2024

N2 - To enable a wide range of joint communications and sensing applications, future channel models must support dynamic variations of the propagation environment. Moreover, when discovering sensing applications, it is essential to connect physical objects and actions to the radio channel characteristics. In this paper, we perform computer vision (CV) aided automatic mapping and showcase that channel measurements can be linked to the dynamic actions and objects in the environment, thus supporting sensing applications. The proposed method employs a vector network analyzer-based channel measurement system operating at 300 GHz and a camera to enable CV for tracking the object in the radio link. Using human hand as the blockage object, the CV-extracted coordinates and the measured channel responses are combined to generate radio channel footprints for different hand movements.

AB - To enable a wide range of joint communications and sensing applications, future channel models must support dynamic variations of the propagation environment. Moreover, when discovering sensing applications, it is essential to connect physical objects and actions to the radio channel characteristics. In this paper, we perform computer vision (CV) aided automatic mapping and showcase that channel measurements can be linked to the dynamic actions and objects in the environment, thus supporting sensing applications. The proposed method employs a vector network analyzer-based channel measurement system operating at 300 GHz and a camera to enable CV for tracking the object in the radio link. Using human hand as the blockage object, the CV-extracted coordinates and the measured channel responses are combined to generate radio channel footprints for different hand movements.

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KW - Blockage

KW - channel measurements

KW - computer vision

KW - Doppler

KW - sensing

KW - upper millimeter-wave

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BT - 18th European Conference on Antennas and Propagation, EuCAP 2024

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 18th European Conference on Antennas and Propagation, EuCAP 2024

Y2 - 17 March 2024 through 22 March 2024

ER -

Computer Vision Enabled Sub-THz Radio Channel Characterization of Dynamic Objects

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