Intelligent infrastructure management in a cloud radio access network

A method comprising:

• obtaining, from a plurality of baseband units of a radio access network, a plurality of data sets, wherein respective ones of the plurality of data sets correspond to operational statistics of respective ones of the plurality of baseband units;
• generating, for each of at least a subset of the plurality of baseband units, a forecasted data set corresponding to one or more predicted operational statistics of the baseband unit, wherein the forecasted data set is generated using a first machine learning model;
• analyzing, for each of the at least a subset of the plurality of baseband units, the forecasted data set to predict a future occurrence of a technical issue and to determine at least one corrective action for the predicted future occurrence of the technical issue, wherein the analysis is performed using a second machine learning model;
• and
• causing initiation of the at least one corrective action;
• wherein the obtaining, generating, analyzing, and causing steps are performed by a processing platform comprising at least one processor coupled to at least one memory executing program code.

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device cause the at least one processing device to:

• obtain, from a plurality of baseband units of a radio access network, a plurality of data sets, wherein respective ones of the plurality of data sets correspond to operational statistics of respective ones of the plurality of baseband units;
• generate, for each of at least a subset of the plurality of baseband units, a forecasted data set corresponding to one or more predicted operational statistics of the baseband unit, wherein the forecasted data set is generated using a first machine learning model;
• analyze, for each of the at least a subset of the plurality of baseband units, the forecasted data set to predict a future occurrence of a technical issue and to determine at least one corrective action for the predicted future occurrence of the technical issue, wherein the analysis is performed using a second machine learning model;
• and
• cause initiation of the at least one corrective action.