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6G业务场景的不完全多视图聚类分析

张茹倩 承楠 陈文 李长乐

西安电子科技大学学报(自然科学版)2024,Vol.51Issue(3):76-87,12.
西安电子科技大学学报(自然科学版)2024,Vol.51Issue(3):76-87,12.DOI:10.19665/j.issn1001-2400.20230703

6G业务场景的不完全多视图聚类分析

Incomplete multi-view clustering analysis of 6G business scenarios

张茹倩 1承楠 1陈文 2李长乐1

作者信息

  • 1. 西安电子科技大学 通信工程学院,陕西 西安 710071
  • 2. 上海交通大学 电子工程系,上海 200240
  • 折叠

摘要

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.

关键词

6G/场景聚类/关键性能指标/不完全多视图聚类

Key words

6 G/scene clustering/KPI/incomplete multi-view clustering

分类

信息技术与安全科学

引用本文复制引用

张茹倩,承楠,陈文,李长乐..6G业务场景的不完全多视图聚类分析[J].西安电子科技大学学报(自然科学版),2024,51(3):76-87,12.

基金项目

国家重点研发计划(2020YFB1807700) (2020YFB1807700)

西安电子科技大学学报(自然科学版)

OA北大核心CSTPCD

1001-2400

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