Sub-THz Channel Characterization and Antenna Array Design for 6G Smart Factory Environments at 140 GHz

The ultra-high data rate and ultra-reliable low-latency communication (URLLC) requirements of Industry 4.0 and smart factory applications have made the evaluation of Sub-Terahertz (Sub-THz) frequencies, especially the 140 GHz band, in sixth-generation (6G) wireless networks a considerable research area. Nevertheless, modern literature often makes isotropic assumptions that do not account for the extreme free-space path loss and highly metallic obstacles associated with sub-THz frequencies. To solve this problem, this paper suggests a comprehensive framework combining high-gain directional antenna design with deterministic 3D ray-tracing channel characterization in a realistic industrial environment. Principally, an optimized 140 GHz 4 × 4 high-gain antenna array system was designed and numerically modeled using CST Studio Suite, and its active element pattern (AEP)-based synthesized 3D radiation pattern was then incorporated into a MATLAB-based Shooting and Bouncing Ray (SBR) tool for a more realistic simulation of the antenna system. Procedural generation of a 3D synthetic model of a smart factory, containing metallic obstacles like Computer Numerical Control (CNC) machines, shelving units, and autonomous guided vehicles (AGVs), was conducted to represent the deterministic multipath environment. Path loss, Power Delay Profile (PDP), RMS Delay Spread, and angular dispersion (Angle of Arrival (AoA) and Angle of Departure (AoD)) analysis prove effective for spatial filtering. Despite significant non-line-of-sight (NLoS) obstructions, leading to 106.5 dB of path loss and a high azimuth angle of arrival spread of 82.9°, the design provides a zero outage in the targeted sector of operation. At the same time, directional beamforming tightly controls the azimuth angle of departure spread to 6.5° and RMS delay spread of 21.5 ns. The results demonstrate that using a realistic antenna radiation pattern is critically important. Furthermore, they reveal multipath behavior in complex industrial scenarios and provide vital insights for the deployment of 6G industrial Internet of Things (IIoT) networks.