Intelligent Representation of Wireless Network States: A Multi-Layer Correlation Approach

Knowing the network states in time has become an indispensable part of network management. However, as users put forward higher requirements for service experience, only focusing on key performance indicators (KPIs) cannot guarantee the quality of user experience. Key quality indicators (KQIs) can reflect the service performance experienced by users and are considered to be an essential factor in optimizing the network. However, it is an urgent problem to represent the network states with different network indicators. In this paper, we propose a novel intelligent representation scheme by exploring the indepth correlation among multi-layer network indicators. Experiments are carried out using the real dataset of the 5G network, and the simulation results demonstrate the feasibility and accuracy of the proposed scheme.