Abstract:

The rapid development of new types of services places greater demands on support ability of the personalized service in mobile communication systems.Traditional intelligent pipe carriers only consider limited factors such as current traffic status of the network and number of loading binding quantity,indicating that they don’t take account of the demands and features of wireless customers.Meanwhile,the rule-based method is overwhelmed due to numerous metrics of the wireless network,the complicated correlation among them and heterogeneous requirements of metrics from various users.Therefore,a user-centric intelligent network operation service was proposed,which utilized machine learning and deep learning method.The service had the ability to learn the correlation between user QoS guarantee requirements and wireless network metric status to construct a joint support architecture based on user requirements and wireless network status.The validity of the method on real data was verified.

Key words: intelligent operation, intelligent pipe, resource allocation control