Performance Evaluation of Reconfigurable Intelligent Surfaces-Assisted Millimeter-Wave Network Using Stochastic Geometry-Based Model

Abstract

Millimeter-wave (mm-wave) bands have received significant attention due to their large bandwidth and high frequency. However, mm-wave signals experience high attenuation primarily as a result of their high directivity and vulnerability to blockage, leading to non-line-of-sight (NLOS) conditions and signal outages. Buildings, structures, and natural obstacles can cause signal blockage, which increases connection challenges and creates coverage gaps. A reconfigurable intelligent surface (RIS) is a potential technique that can improve the coverage of mm-wave networks by intelligently reconfiguring the wireless propagation environment. RIS offers novel solutions to blockage issues by passively reflecting and rerouting mm-wave signals in desired directions. This paper presents a simulation-based evaluation of the signal-to-interference ratio coverage probability in RIS-assisted mm-wave networks based on stochastic geometry. We will use random shape theory to represent the blockages within the network. Furthermore, the impact of increasing the density of RIS and the number of reflective elements on network performance will be examined. The results show that RIS can enhance network coverage and decrease the effects of blockages, with considerable increases in coverage probability when compared to networks without RISs.