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Context-Aware Channel Sounder for AI-Assisted Radio-Frequency Channel Modeling

Published

Author(s)

Camillo Gentile, Jelena Senic, Anuraag Bodi, Samuel Berweger, Raied Caromi, Nada Golmie

Abstract

We describe a context-aware channel sounder that consists of three separate systems: a radio-frequency system to extract multipaths scattered from the surrounding environment in the 3D geometrical domain, a Lidar system to generate a point cloud of the environment in the same domain as the multipaths - providing a geometrical means to associate the multipaths to the environment scatterers - and a camera system to identify and classify the scatterers. With the assistance of artificial intelligence (AI), the data acquired by the three systems can be automatically reduced into a scatter-specific channel model. Two such applications are presented.
Proceedings Title
18th European Conference on Antennas and Propagation
Conference Dates
March 17-22, 2024
Conference Location
Glasgow, GB

Citation

Gentile, C. , Senic, J. , Bodi, A. , Berweger, S. , Caromi, R. and Golmie, N. (2024), Context-Aware Channel Sounder for AI-Assisted Radio-Frequency Channel Modeling, 18th European Conference on Antennas and Propagation, Glasgow, GB, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956785 (Accessed October 1, 2025)

Issues

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Created April 26, 2024, Updated July 13, 2025
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