In order to seamlessly provide high quality communication services, mobile network operators (MNOs) tackle to promptly respond to a degradation of the communication quality when it occurs. MNOs are facing a difficulty to detect the degradation without any error messages or nonconformity. For the first step of the study, we implemented a Self-Organizing Map (SOM)-based visualization system to analyze the users’ behavior in evolved packet core based on state transitions estimated by capturing LTE C-Plane signals. We show a case study of analyzing actual LTE signals using the implemented system, which demonstrates that we can intuitively see the unexpected characteristic of users’ behavior from the results.