A Non-Stationary Geometry-Based MIMO Channel Model for Terahertz UAV-Based Wireless Communication Systems

Area of Science:

• Wireless Communications
• Channel Modeling
• Terahertz (THz) Technology

Background:

• Unmanned Aerial Vehicle (UAV)-assisted communication is crucial for next-generation Space-Air-Ground Integrated Networks (SAGINs).
• Integrated Sensing and Communication (ISAC) demands accurate channel modeling, especially for Terahertz (THz) frequencies offering high data rates and security.
• Existing models struggle with the heterogeneous reflection and scattering mechanisms in THz UAV channels, leading to prediction errors.

Purpose of the Study:

• To propose a novel 3D non-stationary geometry-based stochastic model (GBSM) for THz UAV communication channels.
• To address the physical heterogeneity and non-stationarity challenges in THz UAV channel modeling.
• To provide a robust framework for designing reliable THz UAV-ISAC systems.

Main Methods:

• Developed a 3D non-stationary GBSM using an ellipse-sphere hierarchical geometric framework.
• Modeled reflection paths on ground-plane ellipses and scattering paths on spatial spheres.
• Incorporated atmospheric absorption, multipath fading, and non-stationarity from 3D UAV trajectories.
• Introduced a cluster birth-death mechanism for time-varying scattering evolution.

Main Results:

• Derived and analyzed key statistical properties: Temporal Auto-Correlation Function (T-ACF), Spatial Cross-Correlation Function (S-CCF), and Doppler Power Spectral Density (DPSD).
• Simulation results demonstrated strong agreement with theoretical derivations.
• The proposed model effectively captures the complex channel characteristics.

Conclusions:

• The proposed 3D non-stationary GBSM accurately models THz UAV channels, overcoming limitations of conventional approaches.
• The model provides a validated framework for understanding and designing THz UAV-ISAC systems.
• Offers practical guidance for enhancing the performance and reliability of future SAGINs.