Abstract: Systems, devices, and methods related to allocating cellular wireless network resources and providing access on-demand (AoD) to the cellular wireless network resources are provided. An example method includes: obtaining tenant information and historical tenant data of multiple tenants, predicting an anticipated/optimized demand of a resource of a cellular network for each tenant, determining aa anticipated/optimized unit price of the resource, providing the anticipated/optimized unit price to each tenant, receiving an actual demand from each tenant, determining that a deviation of the actual demand from the anticipated/optimized demand is of or below a predetermined threshold, allocating the resource to the tenants based on the actual demand received from each one of the plurality of tenants, and providing access to the allocated resource to one of the plurality of tenants for one or more user equipment (UE) connected to a tenant network of the tenant to use the allocated resource.

Abstract: A market parameter optimization system identifies optimized parameters for software associated with a telecommunication network market and causes the software to be configured based on the optimized parameters. The market parameter optimization system receives an indication of a telecommunication network market and one or more attributes of the telecommunication network market. The market parameter optimization system identifies one or more optimized parameters for software associated with the telecommunication network market based on the attributes of the telecommunication network market. The market parameter optimization system causes at least a portion of the software associated with the telecommunication network market to be configured based on the one or more attributes.

Abstract: A disclosed method may include (i) building, based on telemetry data from an open radio access network, a machine learning model that predicts when a candidate distributed unit within the open radio access network will experience a failure, (ii) detect, by applying the machine learning model that predicts when the candidate distributed unit will shut down, that a specific distributed unit will experience a specific failure, and (iii) perform, in response to detecting that the specific distributed unit will experience the specific failure, a remedial action that addresses the specific failure. Related systems and computer-readable mediums are further disclosed.

Abstract: A disclosed method may include (i) building, based on telemetry data from an open radio access network, a machine learning model that predicts when a candidate distributed unit within the open radio access network will experience a failure, (ii) detect, by applying the machine learning model that predicts when the candidate distributed unit will shut down, that a specific distributed unit will experience a specific failure, and (iii) perform, in response to detecting that the specific distributed unit will experience the specific failure, a remedial action that addresses the specific failure. Related systems and computer-readable mediums are further disclosed.

Abstract: A disclosed method may include (i) building, based on telemetry data from an open radio access network, a machine learning model that predicts when a candidate distributed unit within the open radio access network will experience a failure, (ii) detect, by applying the machine learning model that predicts when the candidate distributed unit will shut down, that a specific distributed unit will experience a specific failure, and (iii) perform, in response to detecting that the specific distributed unit will experience the specific failure, a remedial action that addresses the specific failure. Related systems and computer-readable mediums are further disclosed.

Abstract: Various arrangements for performing cellular network slice assignment are detailed herein. A cellular network can be used to provide cellular network service to user equipment (UE) using a first slice of the cellular network. The cellular network can receive from the UE a request to transition to a different slice of the cellular network that provides a quality of service (QoS) parameter that is greater than the QoS on an original slice. The cellular network can determine that the UE is eligible to be moved to the different slice based on a location of the UE. Based on receiving the request to transition and the location of the UE, the UE can be reassigned to the different slice of the cellular network.

Abstract: Various arrangements for updating a radio unit (RU) of a cellular network are presented. A volume of cellular signals being handled by a first programmable processor of the RU and a second programmable processor of the RU may be analyzed. A determination can be made that one of the processors has sufficient available resources to handle the analyzed volume of cellular signals. The RU can cause cellular signals to be rerouted to one of the programmable processors while the other processor is taken offline for updating. The update process is performed such that UE in communication with the RU experience uninterrupted cellular network access.

Abstract: Various arrangements for updating a radio unit (RU) of a cellular network are presented. A volume of cellular signals being handled by a first programmable processor of the RU and a second programmable processor of the RU may be analyzed. A determination can be made that one of the processors has sufficient available resources to handle the analyzed volume of cellular signals. The RU can cause cellular signals to be rerouted to one of the programmable processors while the other processor is taken offline for updating. The update process is performed such that UE in communication with the RU experience uninterrupted cellular network access.

Abstract: A market parameter optimization system identifies optimized parameters for software associated with a telecommunication network market and causes the software to be configured based on the optimized parameters. The market parameter optimization system receives an indication of a telecommunication network market and one or more attributes of the telecommunication network market. The market parameter optimization system identifies one or more optimized parameters for software associated with the telecommunication network market based on the attributes of the telecommunication network market. The market parameter optimization system causes at least a portion of the software associated with the telecommunication network market to be configured based on the one or more attributes.

Abstract: Systems, methods, and machine-readable media facilitate adaptive beamforming in a cellular network. One or more signals indicative of one or more locations of a first set of one or more radio units and/or a first set of user equipment may be processed. A first set of beamforming specifications may be determined based at least in part on the one or more locations of the first set of one or more radio units and/or the first set of user equipment. The first set of beamforming specifications may correspond to a first set of one or more beamforming patterns. The first set of beamforming specifications may be communicated to instruct the first set of one or more radio units to direct signal transmission in conformance with the first set of one or more beamforming patterns.

Abstract: Various arrangements for performing cellular network slice assignment are detailed herein. A cellular network can be used to provide cellular network service to user equipment (UE) using a first slice of the cellular network. The cellular network can receive from the UE a request to transition to a different slice of the cellular network that provides a quality of service (QoS) parameter that is greater than the QoS on an original slice. The cellular network can determine that the UE is eligible to be moved to the different slice based on a location of the UE. Based on receiving the request to transition and the location of the UE, the UE can be reassigned to the different slice of the cellular network.

Abstract: Various arrangements for updating a radio unit (RU) of a cellular network are presented. A volume of cellular signals being handled by a first programmable processor of the RU and a second programmable processor of the RU may be analyzed. A determination can be made that one of the processors has sufficient available resources to handle the analyzed volume of cellular signals. The RU can cause cellular signals to be rerouted to one of the programmable processors while the other processor is taken offline for updating. The update process is performed such that UE in communication with the RU experience uninterrupted cellular network access.