Unlike prior research works that focus on cell-level coverage analysis and optimization, this letter develops a system-level analysis framework based on stochastic geometry for RIS-assisted cellular networks experiencing Nakagami- m fading. First, we reveal that the passive beamforming gain of RISs for the signal approachs a deterministic value due to the channel hardening effect, while it is approximated as a Gamma distribution for the interference. Then, the tractable closed-form expressions for the signal-to-interference ratio (SIR) coverage probability of each tier and the entire network are derived. The simulation results verify the correctness of the theoretical analysis. Finally, it is shown that given RIS element density, for scenarios with the path loss exponent greater than 4, densely deploying small-size RISs achieves better coverage performance, while for scenarios with the path loss exponent less than 4, sparse deployment of large-size RISs is a better option.

This letter presents an optimal phase shift configuration method for Reconfigurable Intelligent Surfaces (RISs) with discrete phase shifts to maximize the passive beamforming gain. Specifically, based on theoretical analysis, the multi-ary phase shift optimization problem is first transformed into an equivalent binary phase shift problem. Although it is still a non-convex optimization problem, the optimal solution can be found indirectly through the linear search (LS) for the optimal phase of the superimposed channel. Accordingly, the LS algorithm is designed, in which iterative operations are adopted to ensure the linear computational complexity. The simulation results verify that the proposed LS algorithm achieves the globally optimal passive beamforming, which outperforms existing excellent algorithms. Furthermore, it is also revealed that a 3-bit quantized phase shifter can obtain sufficiently good performance relative to the ideal continuous phase shifter.

Reconfigurable intelligent surface (RIS) is emerging as a promising technology to achieve coverage enhancement. This paper develops a tractable analytical framework based on stochastic geometry for performance analysis of RIS-assisted millimeter wave networks. Based on the framework, a two-step cell association criterion is proposed, and the analytical expressions of the user association probability and the coverage probability in general scenarios are derived. In addition, the closed-form expressions of the two performance metrics in special cases are also provided. The simulation results verify the accuracy of the theoretically derived analytical expressions, and reveal the superiority of deploying RISs in millimeter wave networks and the effectiveness of the proposed cell association scheme to improve coverage. Furthermore, the effects of the RIS parameters and the BS density on coverage performance are also investigated.

Intelligent reflecting surface (IRS), as an emerging hardware which could reflect signals towards any direction, is suitable for improving network coverage in urban environments. In this letter, we combine blockages with IRS and design a mechanism for signals to cross blockages, thereby establishing a "base station-blockage-user" cascaded channel. To analyze the network performance, we use stochastic geometry to model urban networks and analyze the access strategies of typical users, along with the access distance and communication success probability under specific access situations. Meanwhile, we introduce caching mechanism in the network to analyze the impact of complex interference caused by different caching situations. Based on numerical results, we find that the more IRS elements there are, the greater the possibility of access through the IRS. Furthermore, we discover that the quality of communication will not always improve with higher base station density due to the enhancement of interference signals. Moreover, under the popularity model adopted in this letter, we find that a more skewed caching policy will achieve better performance.