Scenario Classification and Channel Modeling for MIMO Communications in Dense Urban Street Scenarios

As one of the most typical wireless communication scenarios, urban communication scenarios draw significant attention in recent years. The full-coverage vision of sixth generation (6G) wireless communications requires a more accurate scenario classification. However, the classification of urban communication scenarios in the existing standard channel models is still rough, which can not meet the requirements of 6G wireless communications. In this paper, based on the physical environmental factors, e.g., building height and density, we classify urban dense street scenarios into three individual sub-scenarios, i.e., major streets, minor streets, and branch streets. Specifically, by optimizing the model parameters, we transform the pervasive channel model into customized channel models for each sub-scenario. The proposed channel models are validated by using the channel data collected from practical communication networks. Furthermore, we analyse the impact of physical environmental factors on channel characteristics.