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

doi:10.19665/j.issn1001-2400.20230703

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6G业务场景的不完全多视图聚类分析

信息与通信工程 | 更新时间：2024-07-23

- 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
- 西安电子科技大学学报 2024年51卷第3期页码：76-87
- 作者机构：
  
  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
- 作者简介：
  
  [ "张茹倩(1999—),女,西安电子科技大学硕士研究生,E-mail:[email protected]" ]
  [ "承楠(1987—),男,教授,博士,E-mail:[email protected]" ]
  [ "陈文(1967—),男,教授,博士,E-mail:[email protected]" ]
  [ "李长乐(1976—),男,教授,博士,E-mail:[email protected]" ]
- 基金信息：
  
  国家重点研发计划(2020YFB1807700)
- DOI：10.19665/j.issn1001-2400.20230703
  中图分类号： TN92
- 纸质出版日期：2024-06-20，
  
  网络出版日期：2023-09-14，
  
  收稿日期：2023-06-12，
- 稿件说明：
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张茹倩, 承楠, 陈文, 等. 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, 2024,51(3):76-87.

Ruqian ZHANG, Nan CHENG, Wen CHEN, et al. Incomplete multi-view clustering analysis of 6G business scenarios[J]. Journal of Xidian University, 2024,51(3):76-87.
张茹倩, 承楠, 陈文, 等. 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, 2024,51(3):76-87. DOI： 10.19665/j.issn1001-2400.20230703.

Ruqian ZHANG, Nan CHENG, Wen CHEN, et al. Incomplete multi-view clustering analysis of 6G business scenarios[J]. Journal of Xidian University, 2024,51(3):76-87. DOI： 10.19665/j.issn1001-2400.20230703.

摘要

在6G网络中

由于业务种类繁杂且需求各不相同

5G网络中划分的三大业务场景已无法满足其粒度上的要求

这给6G按需服务目标的实现带来了巨大挑战。针对海量杂乱的6G场景和6G场景分类中业务数据量庞大以及数据缺失问题

提出了一套基于业务关键性能指标的多维度场景聚类分析方案。该方案基于不完全多视图聚类技术

在上千种参数组合下使用肘部法和轮廓系数法进行调参聚类。聚类结果表明

提出的方案能在不完整的场景数据集中保证收敛

并达到较高的轮廓系数值。此外

通过对比不同比例的缺失数据聚类实验

所提出的6G场景聚类方案能够有效完成对于不同程度缺失数据的多维度聚类。最后

结合原始数据和聚类标签

分析并提炼聚类得到了11类场景的场景知识及各场景的关键性能指标特征

从而为未来6G网络中的新兴场景及业务提供方法基础和理论参考。

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

Keywords

6Gscene clusteringKPIincomplete multi-view clustering

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