Channel Scenario Extensions, Identifications, and Adaptive Modeling for 6G Wireless Communications.

To provide customized high-quality services for all users in the sixth generation (6G) wireless communication systems, it is fundamental to study all 6G channel scenarios and establish accurate channel models for these scenarios correspondingly. However, the absence of comprehensive 6G scenario categorization and the difficulties of modeling the channels for all scenarios bring huge challenges. In this paper, we aim to give a thorough overview of channel scenarios, identification algorithms, and intelligent channel modeling theories. First, different standardized scenario categorization principles are reviewed. A unified and exclusive scenario categorization method is elaborated with detailed 6G scenario definitions. Second, scenario features, feature selection principles, machine learning based identification algorithms, as well as data pre-processing methods are surveyed for the benefit of accurate scenario identification. Third, the intelligent scenario adaptive channel modeling theory based on 6G pervasive channel model is specified. Statistical properties for industrial Internet of Things and high speed train scenarios are simulated and compared with those from measurements. Finally, future research directions and challenges are addressed.