Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Within the functionality of self-healing in self-organizing networks, automatic root cause analysis is typically focused on identifying problems at the cell level, based on the statistics gathered by the operation, administration, and maintenance system. Therefore, mobile operators lose visibility of the problems that directly affect users’ performance. Conversely, this article presents a complete strategy to systematically identify, on the basis of information at the user level (by means of mobile traces), why user disconnection occurs (i.e., the cause of the connection’s release). The proposed automatic root cause analysis is characterized by a top-down model and provides a comprehensive classification of faults when they are caused by radio-related problems. First, it classifies the connections according to the type of release, and subsequently, it determines the specific fault cause based on the event information for those connections abnormally released. The proposed method for identification of the radio-related cause has been applied in both an LTE simulator and a real LTE network, illustrating the usefulness of the approach.
['Ana Gómez-Andrades', 'Raquel Barco', 'I. Serrano', 'Patricia Delgado', 'Patricia Caro-Oliver', 'Pablo Muñoz']
I am writing a research paper on a idea Automatic root cause analysis based on traces for LTE self-organizing networks
[{"from": "human", "value": "I am writing a research paper on a idea Automatic root cause analysis based on traces for LTE self-organizing networks"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Within the functionality of self-healing in self-organizing networks, automatic root cause analysis is typically focused on identifying problems at the cell level, based on the statistics gathered by the operation, administration, and maintenance system. Therefore, mobile operators lose visibility of the problems that directly affect users\u2019 performance. Conversely, this article presents a complete strategy to systematically identify, on the basis of information at the user level (by means of mobile traces), why user disconnection occurs (i.e., the cause of the connection\u2019s release). The proposed automatic root cause analysis is characterized by a top-down model and provides a comprehensive classification of faults when they are caused by radio-related problems. First, it classifies the connections according to the type of release, and subsequently, it determines the specific fault cause based on the event information for those connections abnormally released. The proposed method for identification of the radio-related cause has been applied in both an LTE simulator and a real LTE network, illustrating the usefulness of the approach."}]