Stochastic channel models for massive and extreme large multiple-input multiple-output systems

In this article, stochastic channel models for massive multiple-input multiple-output (M-MIMO) and extreme large MIMO (XL-MIMO) system applications are described, evaluated, and systematically compared. This work aims to cover new aspects of M-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 M-MIMO channel model emulates the environment using different methodologies and properties. Using metrics such as capacity, SINR, singular values decomposition, and condition number, one can understand the influence of each characteristic on the modeling and how it differentiates from other models. Moreover, in new XL-MIMO scenarios, where the near-field and visibility region 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 precoding due to the correlation effect, which have been analyzed from the geometric M-MIMO channel models.