论文标题
大规模和XL-MIMO系统的随机通道模型
Stochastic Channel Models for Massive and XL-MIMO Systems
论文作者
论文摘要
在本文中，描述，评估和系统地比较了大规模MIMO（M-MIMO）和极大的MIMO（XL- MIMO）系统应用的随机通道模型。这项工作旨在以全面有系统的方式涵盖大型MIMO随机渠道模型的新方面。为此，我们比较了不同的模型，并以图形方式和直观地介绍了每个模型的行为。每个大规模的MIMO通道模型都使用不同的方法和属性模拟环境。使用诸如容量，SINR，单数值分解（SVD）和条件编号之类的指标，人们可以理解每个特征对建模的影响及其与其他模型的区别。此外，在新的XL-MIMO场景中，近场和可见区域（VR）效应出现了，我们的发现表明，对于两个假定的群集分布方案，簇位置影响了由于谱图效应而导致的模型，这些模型是由循环效应分析的，该杂物均分析了与循环效应，该循环效应的表现。
In this paper, stochastic channel models for massive MIMO (M-MIMO) and extreme large MIMO (XL- MIMO) system applications are described, evaluated and systematically compared. This work aims to cover new aspects of massive MIMO stochastic channel models in a comprehensive and systematic way. For that, we compare different models, presenting graphically and intuitively the behavior of each model. Each massive MIMO channel model emulates the environment using different methodologies and properties. Using metrics such as capacity, SINR, singular values decomposition (SVD), and condition number, one can understand the influence of each characteristic on the modelling and how it differentiates from other models. Moreover, in new XL-MIMO scenarios, where the near-field and visible region (VR) effects arise, our finding demonstrate that for the two assumed schemes of clusters distribution, the clusters location influences the performance of the conjugate beamforming and zero-forcing (ZF) precoding due to the correlation effect, which have been analysed from the geometric massive MIMO channel models.
