摘要
5G网络在快速发展过程中面临着信号覆盖不均、频谱利用率低及负载分布失衡等技术挑战。多源数据融合技术通过整合网络监测数据、用户行为数据以及环境感知数据等异构信息源,为解决这些问题提供新的技术路径。因此,构建基于时空分布特征的多源数据融合框架,设计异构数据兼容性处理算法和动态权重分配策略。在此基础上建立信号覆盖质量预测模型、负载均衡动态调节策略和服务质量自适应控制算法。仿真验证表明,相较于传统方法,提出的优化策略在网络吞吐量、信号覆盖率、用户满意度等关键指标方面均实现显著提升,多源数据融合为5G网络智能化运维提供理论支撑。
In the process of rapid development,5G networks are facing technical challenges such as uneven signal coverage,low spectrum utilization and unbalanced load distribution.Multi-source data fusion technology provides a new technical path to solve the above problems by integrating heterogeneous information sources such as network monitoring data,user behavior data and environmental awareness data.Therefore,a multi-source data fusion framework based on spatio-temporal distribution characteristics is constructed,and a heterogeneous data compatibility processing algorithm and a dynamic weight allocation strategy are designed.On this basis,the prediction model of signal coverage quality,dynamic adjustment strategy of load balance and adaptive control algorithm of service quality are established.Simulation results show that,compared with traditional methods,the proposed optimization strategy has achieved significant improvement in network throughput,signal coverage,user satisfaction and other key indicators,and multi-source data fusion provides theoretical support for intelligent operation and maintenance of 5G networks.
作者
胡可茵
余健庆
王硕然
冼海恒
袁志谋
HU Keyin;YU Jianqing;WANG Shuoran;XIAN Haiheng;YUAN Zhimou(Jiangmen Branch,China Mobile Communications Group Guangdong Co.,Ltd.,Jiangmen 529000,China)
出处
《通信电源技术》
2025年第14期182-184,共3页
Telecom Power Technology
关键词
5G网络
多源数据融合
网络优化
智能预测
性能提升
5G network
multi-source data fusion
network optimization
intelligent prediction
performance improvement
