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In recent development of communication systems, increasing amount of mobile terminals and multimedia content will require more and more resources to satisfy the need of users. However, there is rare study about the evaluation of large-scale complex network, from which the shortage of the network could be discovered. In this paper, we discuss the AI-based network evaluation method, we propose a novel discovery and ranking system using deep learning to collect and evaluate the network influence factor, and then, the key factors will be discovered to detect the advantages and shortages of network elements, deployments and scale. The AI-based detection and evaluation system is running along with the LTE-A system-level simulation platform, the accuracy and the effectiveness are evaluated, system shortages are successfully discovered within 100 trainings.

The deployment of 5G and its advanced generation wireless personal communication system will greatly affect our daily life. Due to the complexity and scale of the network, a proper evaluation method must be developed to monitor the status of the system and provide executive solution to optimize the network. In this paper, we summarize the state of art in evaluation of large scale cooperative wireless fusion networks, and discovered that there is rarely effective method to make proper estimation and provide precise optimization to network architecture, resource allocation and reform of network elements. So both benefits and challenges are provided to make a clear view of the system, deep learning based method is also proposed as an open discussion problem.