Abstract:

In the 6G network,due to the variety of business types and different requirements,the three major business scenarios divided in the 5G network can no longer meet the granularity requirements,which brings great challenges to the realization of the goal of 6G on-demand services.Aiming at the massive and messy 6G scenarios and the huge amount of business data and data missing in the classification of 6G scenarios,this paper proposes a set of multi-dimensional scenario clustering analytical schemes based on business key performance indicators.The scheme is based on the incomplete multi-view clustering technology,and uses the elbow method and the silhouette coefficient method to perform parameter tuning clustering under thousands of parameter combinations.Clustering results show that the scheme proposed in this paper can guarantee convergence in incomplete scene datasets and achieve high silhouette coefficient values.In addition,by comparing the missing data clustering experiments with different proportions,the proposed 6G scene clustering scheme can effectively complete the multi-dimensional clustering for different degrees of missing data.Finally,this paper combines the original data and clustering labels,analyzes and refines the clustering to obtain the scene knowledge of 11 types of scenarios and the characteristics of key performance indicators of each scenario,so as to provide the method basis and theoretical reference for emerging scenarios and services in the future 6G network.

Key words: 6G, scene clustering, KPI, incomplete multi-view clustering