SINR Coverage Probability Analysis of THz-mmWave multi-tier 3D Network using Stochastic Geometry

Terahertz (THz) connectivity offers terabits-per-second (tbps) data rates; however, its coverage is limited due to high path losses. Therefore, to overcome this, the optimal deployment of ultra-dense THz small cells is a promising solution. This requires advanced network modelling, especially the integration of a vertical dimension to the channel model, particularly with unmanned aerial vehicles (UAVs) as base stations (BSs) in dense urban environments for enhanced capacity. This paper presents a novel stochastic geometry (SG) based three-dimensional (3D) multi-tier network model of millimeter (mmWave) and THz. Whereas the mmWave macro-cells optimal coverage is modelled by the Poisson Point Process (PPP), the THz small cells are modelled using Thomas Cluster Process (TCP) targeting capacity enhancement in traffic hotspots. To account for the benefits of this approach, a comparative analysis of single-tier, multi-tier two-dimensional (2D) and the 3D network models revealed that the multi-tier models show superior signal-to-interference-plus-noise ratio (SINR) and coverage probability (CP) performance. However, the 3D deployment indicates reduced CP as a consequence of UAV BS height-induced path loss.