Systems and methods for machine learning based slice modification, addition, and deletion

A method, comprising:

• receiving time data, traffic data, and quality of service (QoS) data;
• determining a predicted radio resource usage of a base station based on the time data, the traffic data, and the QoS data, wherein the base station includes at least one baseband unit (BBU), one or more radio units communicatively coupled to the at least one BBU, and one or more antennas communicatively coupled to the one or more radio units, wherein each respective radio unit of the one or more radio units is communicatively coupled to a respective subset of the one or more antennas, wherein the at least one BBU, the one or more radio units, and the one or more antennas are configured to implement a base station for wirelessly communicating with user equipment;
• and
• dynamically modifying, adding, or deleting one or more network slices based on the predicted radio resource usage of the base station.

A system, comprising:

• a distributed antenna system including:
• a master unit communicatively coupled to a base station;
• one or more remote antenna units communicatively coupled to the master unit, wherein the one or more remote antenna units are located remotely from the master unit, wherein the one or more remote antenna units are configured to communicate wireless signals with user equipment in one or more coverage zones;
• and
• a machine learning computing system configured to:
• receive time data, traffic data, and quality of service (QoS) data;
• and
• determine a predicted radio resource usage of the base station based on the time data, the traffic data, and the QoS data;
• wherein the system is configured to dynamically modify, add, or delete a network slice based on the predicted radio resource usage of the base station.