Multipath Extraction and Cluster Identification from an Indoor Measurement at 300 GHz

Owing to the unique attributes of the terahertz (THz) band (0.1-10 THz) adoption of millimeter and centimeter wave channel models to characterize THz communication seems unrealistic. In this context, a cluster-based channel model using multipath components extracted from measurement data can serve as a crucial step in understanding the propagation characteristics of THz signals. In cognizance of the prior fact, the current work uses the Subgrid CLEAN algorithm to extract the multipath components (MPCs) using the data from a measurement campaign conducted in a typical conference room at 300 GHz. The extracted MPCs were further clustered based on their temporal and spatial characteristics using the K-Power Means (KPM) technique. The effectiveness of the employed extraction technique is validated by comparing the extracted power spectrums (angle and delay) with the measured ones whereas the efficacy of the clustering algorithm is demonstrated by identifying the interacting objects (IOs) causing the same.