Geometrical-Empirical Channel Propagation Model for Human Presence at 60 GHz

Published

March 2, 2021

Author(s)

Camillo Gentile, Anmol Bhardwaj, Derek Caudill, Peter B. Papazian, Jack Chuang, David Michelson

Abstract

Previous efforts to develop simulation and/or measurement-based channel propagation models for the effect of human blockage on millimeter-wave communication systems have yielded important results, but lack either accuracy, generality, or simplicity. To fill that void, in this paper we propose a hybrid geometrical-empirical model for human presence; we refer to it as human presence because reflection from the body before and after blockage occurs in addition to diffraction around the body during blockage (as in previous efforts) is incorporated. Specifically, propagation is modeled as the superposition of the main transmission path and reflected and/or diffracted paths from the body; the geometrical component of the model accounts for the phase of each path while the empirical component accounts for its amplitude. To validate the proposed model and extract its empirical parameters, an exhaustive measurement campaign with 60 blockage scenarios, comprising varying human subjects and transmitter-human-receiver configurations, was conducted; a total of 90,000 channel acquisitions was recorded with our precision, state-of the-art 60-GHz channel sounder. The overall model is shown to be computationally efficient yet general enough to accurately represent a wide range of scenarios.

Citation

IEEE Transactions on Antennas and Propagation

Volume

9

Pub Type

Journals

Download Paper

https://dx.doi.org/10.1109/ACCESS.2021.3063655

Local Download

Keywords

Reflection, diffraction, mmWave, blockage, shadowing event, Doppler

Citation

Gentile, C. , Bhardwaj, A. , Caudill, D. , Papazian, P. , Chuang, J. and Michelson, D. (2021), Geometrical-Empirical Channel Propagation Model for Human Presence at 60 GHz, IEEE Transactions on Antennas and Propagation, [online], https://dx.doi.org/10.1109/ACCESS.2021.3063655, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=928491 (Accessed December 6, 2024)