Research on Quality Optimization of NR Networks Using Multimodal Data
The development of 5G NR networks has brought unprecedented high-speed and low latency experiences to users,but with the increase in network complexity and the expansion of business scope,ensuring network quality has become a challenge.Multimodal data provides new perspectives and methods for optimizing network quality.This article explores how to utilize multimodal data capture and preprocessing techniques,and integrate machine learning and deep learning models to improve the performance of NR networks.Firstly,the concept of multimodal data and its importance in network optimization were introduced.Then,the data capture,preprocessing,and modeling were described in detail,until the optimization objective and utility function were defined.Finally,the research results were reviewed and future research directions were discussed.
multimodal data5G NR networkdata preprocessingnetwork quality optimization
NETL
NSTL
万方数据
