Stochastic Geometry Modeling and Analysis for THz-mmWave Hybrid IoT Networks (2103.11674v2)

Abstract: Terahertz (THz) band contains abundant spectrum resources that can offer ultra-high data rates. However, due to the THz band's inherent characteristics, i.e., low penetrability, high path loss, and non-negligible molecular absorption effect, THz communication can only provide limited coverage. To overcome these fundamental obstacles and fully utilize the THz band, we consider a hybrid Internet-of-Things (IoT) network consisting of THz and millimeter wave (mmWave) cells. A hybrid IoT network can dynamically switch between mmWave and THz links to ensure reliable and ultra-fast data connection. We use a stochastic geometric framework to evaluate the proposed hybrid IoT network's coverage probability and spectral efficiency and validate the analysis through numerical simulation. In this paper, we derive a closed-form expression of the Laplace transform of the interference while considering an accurate multi-level Flat-top (MLFT) antenna pattern. We observed that a large antenna array with a strong bias to the THz base station (TBS) improves the end-to-end network performance through numerical results. Furthermore, we recognized a fundamental trade-off relation between the TBS's node density and the bias to mmWave/THz; e.g., high TBS density with a strong bias to the TBS may degrade the network performance.