Abstract: Aspects of the subject disclosure may include, for example, determining that one or more tests are to be executed for a core network of a telecommunications system, based on the determining, transmitting one or more test initiation commands to a set of user equipment (UEs) of a plurality of UEs communicatively coupled to the core network, wherein the one or more test initiation commands cause the set of UEs to execute the one or more tests, obtaining, from the set of UEs, results associated with the one or more tests, analyzing the results based on one or more machine learning (ML) models to identify a network issue, and responsive to the analyzing, performing one or more actions to address the network issue. Other embodiments are disclosed.

Abstract: A method and an apparatus for using fuzzy logic to determine when handovers are desirable and the extent to which the radio transmission power in a cellular telephone network should be adjusted. The mobile phone and the base transceiver station measure certain system parameters, including rate of handover, quality, distance, level, call duration, and power. These measurements are input to a fuzzifier. The fuzzifier applies standard fuzzy-set-theory membership functions to the measurements, and the fuzzifier outputs a set of fuzzy variables corresponding to the measurements. The fuzzifier outputs are input to an inference engine. The inference engine contains a set of rules that, when applied to the inference engine inputs, indicate: when a handover should be performed; when a handover should not be performed; and the amount by which, if any, the transmission power should be adjusted.