Stochastic Characterization of outdoor Terahertz Channels Through Mixture Gaussian Processes

Evangelos N. Papasotiriou*, Alexandros Apostolos A. Boulogeorgos, Mar Francis De Guzman, Katsuyuki Haneda, Angeliki Alexiou

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

68 Downloads (Pure)

Abstract

This contribution aims at experimentally validating the suitability of Gaussian mixture (GM) distributions to capture the stochastic characteristics of outdoor terahertz (THz) wireless channels. In this direction, we employ a machine learning enabled approach, based on the expectation maximization algorithm, in order to identify the suitable number of Gaussian distributions as well as their corresponding parameters that result to an acceptable fit. The fitting accuracy of the GMs to the empirical distributions is evaluated by means of the Kolmogorov-Smirnov (KS), Kullback-Leibler (KL), root-mean-square-error (RMSE) and R2 fitting accuracy tests. These tests verify the suitability of GMs to model the small-scale fading channel amplitude of outdoor THz wireless links. In addition, the fitting accuracy results indicate that as the number of mixtures increases the resulting GMs achieve a better fit to the empirical data.

Original languageEnglish
Title of host publication2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2022
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-6654-8053-6
DOIs
Publication statusPublished - 2022
MoE publication typeA4 Conference publication
EventIEEE International Symposium on Personal, Indoor and Mobile Radio Communications - Virtual, Online, Japan
Duration: 12 Sept 202215 Sept 2022

Publication series

NameIEEE International Symposium on Personal, Indoor, and Mobile Radio Communications
ISSN (Print)2166-9570
ISSN (Electronic)2166-9589

Conference

ConferenceIEEE International Symposium on Personal, Indoor and Mobile Radio Communications
Abbreviated titlePIMRC
Country/TerritoryJapan
CityVirtual, Online
Period12/09/202215/09/2022

Fingerprint

Dive into the research topics of 'Stochastic Characterization of outdoor Terahertz Channels Through Mixture Gaussian Processes'. Together they form a unique fingerprint.

Cite this