Outdoor THz fading modeling by means of Gaussian Mixture Distribution

Terahertz (THz) band offers a vast amount of bandwidth and is envisioned to become a key enabler for a number of nextgeneration wireless applications. In this direction, appropriate channel models, encapsulating the large and small-scale fadingphenomena, need to be developed for both indoor and outdoor communications environments. The THz large-scale fadingcharacteristics has been extensively investigated for both indoor and outdoor scenarios. The study of indoor THz small-scalefading has recently gained the momentum, while the small-scale fading of outdoor THz wireless channels has not yet beeninvestigated. Motivated by this, this contribution introduces Gaussian mixture (MG) distribution as a suitability small-scalefading model for outdoor THz wireless links. In more detail, multiple outdoor THz wireless measurements recorded at differenttransceiver separation distance are feed to an expectation-maximization (EM) fitting algorithm, which returns the parameters ofthe MG probability density function. The fitting accuracy of the analytical GMs is evaluated in terms of the Kolmogorov-Smirnov,Kullback-Leibler (KL) and root-mean-square-error (RMSE) tests. The results reveal that as the number of mixtures increasesthe resulting analytical GMs perform a better fit to the empirical distributions. In addition, the KL and RMSE metrics indicatethat the increase of mixtures beyond a particular number result to no significant improvement of the fitting accuracy.