基于通信网络大模型的智能运维人机交互系统研究与应用

韩赛; 范凤霞; 马家福; 王泽林; 徐博华; 王光全; 唐雄燕

doi:10.11959/j.issn.1000-0801.2026020

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基于通信网络大模型的智能运维人机交互系统研究与应用

工程与应用 | 更新时间：2026-03-02

- 基于通信网络大模型的智能运维人机交互系统研究与应用
- Research and application of intelligent operation and maintenance human-computer interaction system based on large language models for communication networks
- 电信科学 2026年42卷第1期页码：199-210
- 作者机构：
  
  中国联合网络通信有限公司研究院，北京 100044
- 作者简介：
  
  [ "韩赛（1988- ），女，博士，中国联合网络通信有限公司研究院高级工程师，主要研究方向为网络智能、自智网络等。" ]
  [ "范凤霞（1986- ），女，中国联合网络通信有限公司研究院工程师，主要研究方向为网络智能、自智网络等。" ]
  [ "马家福（1999- ），男，中国联合网络通信有限公司研究院助理工程师，主要研究方向为网络智能、网络大模型等。" ]
  王泽林（1983- ），男，中国联合网络通信有限公司研究院高级工程师，主要研究方向为IP、云网、白盒、SDN技术等。
  徐博华（1989- ），男，中国联合网络通信有限公司研究院高级工程师，主要研究方向为数据中心网络、宽带城域网、下一代互联网等。
  王光全（1968- ），男，博士，中国联合网络通信有限公司研究院正高级工程师，主要研究方向为通信网络的规划、新技术演进、标准制定等。
  唐雄燕（1967- ），男，博士，中国联合网络通信有限公司研究院副院长、首席科学家、正高级工程师，主要研究方向为宽带通信、光纤传输、互联网、物联网、新一代网络等。
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2026020
  中图分类号： TP393;TN915.07
- 收稿：2025-07-01，
  
  修回：2025-08-25，
  
  录用：2025-09-19，
  
  纸质出版：2026-01-20
- 稿件说明：
移动端阅览
韩赛,范凤霞,马家福等.基于通信网络大模型的智能运维人机交互系统研究与应用[J].电信科学,2026,42(01):199-210.

Han Sai,Fan Fengxia,Ma Jiafu,et al.Research and application of intelligent operation and maintenance human-computer interaction system based on large language models for communication networks[J].Telecommunications Science,2026,42(01):199-210.
韩赛,范凤霞,马家福等.基于通信网络大模型的智能运维人机交互系统研究与应用[J].电信科学,2026,42(01):199-210. DOI： 10.11959/j.issn.1000-0801.2026020.

Han Sai,Fan Fengxia,Ma Jiafu,et al.Research and application of intelligent operation and maintenance human-computer interaction system based on large language models for communication networks[J].Telecommunications Science,2026,42(01):199-210. DOI： 10.11959/j.issn.1000-0801.2026020.

摘要

随着网络规模的扩大和5G应用的爆发式增长，网络管理运营面临新的需求和挑战。运营效率直接影响网络使用效能和服务质量，亟须通过智能化手段提升网络管理运营水平，减少传统低效、重复性工作。随着AI技术和通信网络的深度融合，引入通信网络大模型成为提升网络管理运营效率的关键路径。对此，研发了一套基于大语言模型的智能运维人机交互系统。该系统通过大小模型协同机制，集成了知识问答、人机交互、数据分析与方案生成等功能。该系统在现网的部署应用表明，其不仅能够显著提升运维效率，降低运维成本，还能通过预测性维护减少网络故障的发生，提升用户体验，增强企业竞争力。该系统具备高度可复制性与推广适应性，具有广泛的应用前景与实用价值。

Abstract

With the continuous expansion of network scale and the explosive growth of 5G applications

new demands and challenges are encountered in network management and operations. Since operational efficiency directly influences network utilization and service quality

it becomes imperative to enhance the level of network management through intelligent means and reduce traditional inefficient and repetitive tasks. As AI technology becomes deeply integrated with communication networks

the introduction of large-scale communication network models is recognized as a key pathway to promote network management and operations. In response

an intelligent operational human-computer interaction system based on large language models (LLMs) was developed. This system integrated capabilities such as knowledge-based question answering

human-computer interaction

data analysis

and solution generation through a collaboration mechanism between large and small models. Deployment and application of the system in live networks demonstrated that it not only significantly improved operational efficiency and reduced maintenance costs

but also minimized network failures through predictive maintenance

thereby enhancing user experience and strengthening corporate competitiveness. The system was designed with high replicability and adaptability

indicating broad application prospects and practical value.

关键词

Keywords

references

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