Coverage Analysis of Aerial Users in Intelligent Reflecting Surface-Aided Cellular Networks

Due to the down-tilt of BS antennas to serve ground users in existing networks, aerial user equipments (AUEs) are only supported through the side lobes, which leads to insufficient aerial coverage. Fortunately, intelligent reflecting surfaces (IRSs) possess the remarkable ability to offer extra signal power to enhance AUEs’ coverage. However, to fully realize the potential of the IRS, its deployment is contingent upon the radiation pattern of the BS which substantially modifies the network topology. This paper proposes a novel IRS-based network model to serve AUEs by constructing the virtual LoS air-to-ground links to provide targeted signal for AUEs, where IRSs are practically distributed in the BS main lobe to effectively utilize the BS radiation power. Specifically, the distribution of IRSs is modeled by a variant of the Matérn cluster process (MCP), based on which the correlated interference from BSs and IRSs introduced by their location correlation is theoretically characterized. Furthermore, based on a concise two-lobe model for BS antenna gain, the effective distribution area of IRSs is derived as a ring concentric with the cell, which exhibits tunability in accordance with the beamwidth and the tilt angle of the BS antenna. In addition, the framework is characterized for analyzing the correlated interference from BSs and IRSs through the accurate integration of the power correlation associated with both direct paths and IRS-reflected paths. Leveraging stochastic geometry, theoretical expressions of network metrics are derived on the IRS-assisted AUE networks. Numerical results demonstrate the effectiveness of the proposed scheme, as manifested by the significant elevation in the coverage probability of AUEs by 67% when the number of elements per IRS hitsN= 2000.