Intelligent reflecting surfaces (IRSs) are promising enablers for high-capacity wireless communication systems by constructing favorable channels between the transmitter and receiver. However, general, accurate, and tractable outage analysis for IRS-aided multiple-input-multiple-output (MIMO) systems is not available in the literature. In this paper, we first characterize the mutual information (MI) of IRS-aided MIMO systems by capitalizing on large random matrix theory (RMT). Based on this result, a closed-form approximation for the outage probability is derived and a gradient-based algorithm is proposed to minimize the outage probability with statistical channel state information (CSI). We also investigate the diversity-multiplexing tradeoff (DMT) with the finite signal-to-noise ratio (SNR). Based on these theoretical results, we further study the impact of the IRS size on system performance. In the high SNR regime, we provide closed-form expressions for the ergodic mutual information (EMI) and outage probability as a function of the IRS size, which analytically reveal that the benefit of increasing the IRS size saturates quickly. Simulation results validate the accuracy of the theoretical analysis and confirm the increasing cost for deploying larger IRSs to improve system performance. For example, for an IRS-aided MIMO system with 20 antennas at both the transmitter and receiver, we need to double the size of the IRS to increase the throughout from 90% to 95% of its maximum value.

翻译：智能反射表面(IRS)通过在发报机和接收器之间建立有利的频道,为高容量无线通信系统提供了有希望的助推器。然而,文献中没有关于IRS辅助的多输入-多输出(MSIMO)系统的一般性、准确和可移动的断流分析。在本文中,我们首先利用大型随机矩阵理论(RMT)来描述IRS辅助的MSIMO系统的相互信息(MI)。根据这一结果,我们为ERGodic 共同信息(EMI)提供了封闭式近似值,并提出了一种基于梯度的算法,以通过统计频道国家信息来最大限度地减少误差概率。我们还调查了IRS辅助的多倍倍翻(DMMT)系统(MIMT),并用有限的信号-噪音比率(SNRM)系统(DM)对多样性-多倍交换(DMM)系统(DM)系统(DMRIS)的多式交换(DRIS)系统(MI)的多式交换,以便快速地确认IMRS(IMRS)系统(IMRS)90%(IML)的升级(IML)的准确性分析结果。