Reconfigurable Intelligent Surfaces (RIS) technology are a promising physical-layer candidate for sixth-generation (6G) cellular networks. This paper provides a system-level performance assessment of RIS-assisted multi-input multi-output (MIMO) cellular networks in terms of downlink coverage probability and ergodic rate. To capture the inherent randomness in the spatial deployments of both Base Stations (BSs) and RISs, we propose a new stochastic geometry model for such systems based on the Matern Cluster Process (MCP). This model consists in randomly distributed RISs around BSs, whose placement is according to a Poisson Point Process (PPP). The RISs provide the multipath diversity and the multiple antenna receiver provide the antenna diversity. The system is assumed to use the orthogonal frequency division multiplexing (OFDM) technique to modulate the former and employ the maximal ratio combining (MRC) technique at the receiver to exploit the latter. We show that the coverage probability and the ergodic rate can be evaluated when considering RISs operate as batched powerless beamformers. The resulting analytical expressions provide a generic methodology to evaluate the impact of key RIS-related parameters, such as the size of RIS and the density of nodes, on system level performance. Numerical evaluations of the analytical expressions and Monte-Carlo simulations jointly validate the proposed analytical approach and provide valuable insights into the design of future RIS-assisted radio cellular networks.

翻译：可重构智能表面（RIS）技术是第六代（6G）蜂窝网络中有前景的物理层候选技术。本文从下行覆盖概率和遍历速率角度，对RIS辅助的多输入多输出（MIMO）蜂窝网络进行了系统级性能评估。为捕捉基站和RIS空间部署的固有随机性，我们提出了一种基于Matern簇过程（MCP）的新随机几何模型。该模型假设RIS围绕服从泊松点过程（PPP）分布的基站随机分布。RIS提供多径分集，而多天线接收机提供天线分集。系统采用正交频分复用（OFDM）技术对前者进行调制，并在接收端采用最大比合并（MRC）技术以利用后者。我们证明，当考虑RIS作为无源波束成形器时，可以评估覆盖概率和遍历速率。所得分析表达式提供了一种通用方法，用于评估RIS关键参数（如RIS尺寸和节点密度）对系统级性能的影响。分析表达式的数值评估与蒙特卡洛仿真共同验证了所提出的分析方法，并为未来RIS辅助蜂窝无线网络的设计提供了有价值的见解。