Statistical Analysis of Primary and Random Clusters in 318 GHz Terahertz Channels for Industrial IoT

Abstract

The ultra-high data rates enabled by terahertz (THz) communications pave the way for the demanding requirements of industrial Internet of Things (IIoT) applications, making the investigation of THz channels in industrial environments a critical research topic. This paper presents a comprehensive statistical analysis of the propagation channel at 318\,GHz in an industrial environment. In particular, a new clustering scheme is proposed for the sparsity observed in the multipath components (MPCs) of the measured channel. Furthermore, statistical analyses are conducted separately for the group of strong reflections, defined as primary clusters, and other propagation phenomena, defined as random clusters, in a rich-scattering environment. The results demonstrate that the large-scale parameters are predominantly influenced by these strong reflections. This study provides reliable support and guidance for subsequent THz stochastic channel modeling.