LEARNED SCHEDULER FOR FLEXIBLE RADIO RESOURCE ALLOCATION TO APPLICATIONS

Aspects include a machine learning based resource block scheduler configured to meet service level requirements of applications. Aspects include receiving a plurality of scheduling requests each associated with a respective application of a plurality of applications on a plurality of wireless devices, identifying a plurality of current channel state information each associated with one of the plurality of wireless devices, and identifying a plurality of different types of service level requirements each associated with one of the plurality of applications. Further, the aspects include determining, by a machine learning based scheduler based on each of the plurality of current channel state information, a sequence of resource assignments expected to meet the plurality of different types of service level requirements, the sequence of resource assignments including a plurality of grants of a scheduled assignment of a resource, and transmitting respective grants for the respective applications to the wireless devices.