Method and apparatus for setting barring factor for controlling access of user equipment based on machine learning

摘要

The present invention provides a method and a device for setting a barring factor based on machine learning in an access control technique of an access class barring manner. According to an embodiment of the present invention, the method performs learning according to a Q-learning algorithm by putting connection success probability as a state, putting increase of the barring factor, maintenance of the barring factor and reduction of the barring factor as a selective behavior, and putting collision probability and an average access delay time as a compensation. When an actual barring factor is set, optical behavior in a current state derived from a training result is performed. According to an embodiment of the present invention, the barring factor suitable for an environment in which a base station and terminals are faced can be set through the machine learning, thereby reducing overload and congestion of a communication network.