Multi-THz Bands Large-Scale Fading Characterization and Path Loss Prediction Based on Environment Features


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Terahertz (THz) communications are envisioned as one of the promising technologies to enable ultra-broadband 6G systems. One fundamental challenge when moving to new spectrum is to understand the science of radio propagation and propose an accurate and effective channel prediction method for predicting the signal coverage. In this paper, we first conduct extensive VNA-based wideband radio propagation measurements at 220 GHz in indoor hallway and lobby environments and at 280 GHz in an indoor laboratory environment. Omnidirectional and best directional path loss are analyzed and modeled by empirical single-band and multi-band path loss models. Besides, propagation statistics such as Rician K-factor (KF) and root mean square (RMS) delay spread (DS) are modeled by Weibull distribution and lognormal distribution, respectively, and two-slope model is proposed to analyze the relationship of the KF, RMS DS and distance in various scenarios. Numerical results demonstrate that large-scale close-in model in this paper is simpler and more physically-based compared to floating-intercept model. In particular, path loss prediction method based on environment features is proposed, which can predict path loss directly by utilizing random forest method, and the propagation environment are defined and extracted by scatterer features and related features of Tx and Rx. The performance of the proposed model is better than that of empirical path loss models. The measured results not only enrich the datasets of indoor THz channel propagation, also can guide communication systems, network planning and deployment for 6G and beyond.
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