Abstract: This disclosure provides systems, methods, devices, and apparatuses, including computer programs encoded on computer storage media, for network slice feasibility assessment for a latency-based service level agreement (SLA). Some aspects relate to providing on-demand approval or rejection of a network slice request at a device in accordance with a latency threshold associated with an SLA of the requested network slice. In some implementations, the device may receive load information associated with the requested network slice. The device may select, in accordance with the latency threshold and the load information, a resource allocation for the network slice. In some implementations, the device may output an indication to accept or reject the network request according to the resource allocation. In some implementations, the device may use one or more machine learning (ML) models to select the acceptance or rejection of the network slice request, to select the resource allocation, or both.

Abstract: This disclosure provides systems, methods, and apparatus for energy saving using predicted performance indicators. The described techniques may enable a service management and orchestration framework (SMO) to determine one or more cells to deactivate based on one or more predicted key performance indicators (KPIs) associated with deactivating the cells. For example, the SMO may use a machine learning (ML) model, a neural network (NN), and the like to predict how a throughput associated with the one or more cells may change based on deactivating a first cell for a first period of time. In some aspects, the SMO may therefore predict a first time period or a threshold load for to deactivate the first cell that may result in a throughput of one or more other cells decreasing an amount that is less than a threshold throughput decrease.

Abstract: This disclosure provides systems, methods, devices, and apparatuses, including computer programs encoded on computer storage media, for network slice feasibility assessment for a latency-based service level agreement (SLA). Some aspects relate to providing on-demand approval or rejection of a network slice request at a device in accordance with a latency threshold associated with an SLA of the requested network slice. In some implementations, the device may receive load information associated with the requested network slice. The device may select, in accordance with the latency threshold and the load information, a resource allocation for the network slice. In some implementations, the device may output an indication to accept or reject the network request according to the resource allocation. In some implementations, the device may use one or more machine learning (ML) models to select the acceptance or rejection of the network slice request, to select the resource allocation, or both.