基于多模态数据分析的NR网络质量优化方法研究

A Study on NR Network Quality Optimization Method Based on Multimodal Data Analysis

随着5G技术的发展和应用,NR网络作为5G的核心组成部分,其网络质量的优化成为了通信行业的重要课题。本文以NR网络为例,基于路测、互联网拨测等测试数据和MR、MDT等网络数据以及投诉、DPI等网络测评感知等众测数据分析,开展多模态的网络质量优化方法。文章提出了一种利用大数据分析对不同来源的网络性能和用户体验数据进行关联、挖掘和应用的方法。首先介绍了NR网络的特点和挑战,然后分析了各种数据源的特征和价值,接着阐述了多模态数据分析的框架和流程,最后通过一些应用案例和实验结果展示了其有效性和优势。

With the development and application of 5G technology,NR network,as the core component of 5G,its network qual-ity optimization has become an important issue in the communication industry.Taking NR network as an example,this paper carries out multimodal network quality optimization methods based on test data such as road test,internet dial test and network data such as MR,MDT and network evaluation perception data such as complaint,DPI.This paper proposes a method that uses big data analysis to correlate,mine and apply network performance and user experience data from different sources.This paper first introduces the characteristics and challenges of NR network,then analyzes the features and values of various data sources,then elaborates the framework and process of multimodal data analysis,and finally shows the effectiveness and advantages of this method through some application cases and experimental results.