基于OTT数据的5G端网协同智能优化研究与实践

Research and Practice of 5G Terminal-network Collaborative Intelligent Optimization Based on OTT Data

针对当前5G MR不携带用户位置信息无法实现用户网络感知精细化分析的问题,引入OTT大数据通过使用神经网络算法、DBSCAN算法等机器学习算法,建立5G用户位置预测和5G弱覆盖小区分布聚类模型,开展精细化的5G用户感知保障。研究结果表明,基于OTT数据的5G端网协同智能优化能有效提升5G优化效率,节省网络运营成本。

Aiming at the problem that the current 5G MR can not carry user location information to achieve user network awareness fine analysis,by introducing OTT big data and using machine learning algorithms such as neural network algorithm and DBSCAN algorithm,5G user location prediction and 5G weak coverage cell distribution clustering model are established to carry out refined 5G user perception guarantee.The results show that 5G termina-network collaborative intelligent optimization based on OTT data can effectively improve the efficiency of 5G optimization and save network operating costs.