Coverage Analysis of IRS-Aided Millimeter-Wave Networks: A Practical Approach


Etcibasi A. Y., AKTAŞ E.

IEEE Transactions on Wireless Communications, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1109/twc.2023.3310664
  • Journal Name: IEEE Transactions on Wireless Communications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Analytical models, Buildings, Computational modeling, coverage, Intelligent reflecting surfaces (IRSs), Millimeter wave communication, mmWave networks, Numerical models, Signal to noise ratio, SNR, stochastic geometry, Surface waves
  • Hacettepe University Affiliated: Yes

Abstract

Intelligent reflecting surfaces (IRSs) have become a popular topic in recent years for their great potential for controlling the radio link environment of wireless networks. With this controlled environment, the coverage can be increased. This paper examines the coverage analysis of IRS-aided networks, considering both two-dimensional buildings and the product-distance path loss model for the first time. Leveraging the tools from stochastic geometry, the locations of base stations (BSs), buildings, and IRSs are modeled with a homogeneous Poisson point process (PPP). A Gamma approximation for the distribution of the nearest line-of-sight (LoS)-neighbor distance is proposed, leading to a closed-form expression for the distribution of the product-distance. Feasible BSs are defined as BSs which are reachable via an IRS deployed on a specific facade of a building, and the ratio of feasible BSs is derived. Simulations are performed, which confirm the proposed analytical methods. In the numerical results, it is observed that the IRSs can introduce up to a 45% coverage boost, and the effect of the IRS length on the coverage probability is limited beyond 1.2 meters at 60 GHz.