As the superior improvement on wireless network coverage, spectrum efficiency and energy efficiency, Intelligent reflecting surface (IRS) has received more and more attention. In this work, we consider a large-scale IRS-assisted heterogeneous cellular network (HCN) consisting of $K$ ($K \geq 2$) tiers of base stations (BSs) and one tier of passive IRSs. With tools from stochastic geometry, we analyze the coverage probability and network spatial throughput of the downlink IRS-assisted $K$-tier HCN. Compared with the conventional HCN, we observe the significant gain achieved by IRSs in coverage probability and network spatial throughput. The proposed analytical framework can be used to understand the limit of gain achieved by IRSs in HCN.

翻译：随着无线网络覆盖范围、频谱效率和能量效率的显著提升，智能反射面（IRS）受到越来越多的关注。本文考虑一个由$K$层（$K \geq 2$）基站（BS）和一层无源IRS组成的大规模IRS辅助异构蜂窝网络（HCN）。借助随机几何工具，我们分析了下行链路IRS辅助$K$层HCN的覆盖概率和网络空间吞吐量。与传统HCN相比，我们观察到IRS在覆盖概率和网络空间吞吐量方面带来的显著增益。所提出的分析框架可用于理解IRS在HCN中实现增益的极限。