Abstract: An object of the present disclosure is to provide a method capable of estimating the radio quality more accurately. The method includes acquiring first weather information and first geographic information at a first observation point, second weather information and second geographic information at a second observation point, and radio quality information at a radio base station; learning a model for estimating radio quality based on the first weather information and the first geographic information, the second weather information and the second geographic information, and the radio quality information; and estimating the radio quality using the model and at least one of third weather information at the first observation point or fourth weather information at the second observation point.

Abstract: A data processing unit generates device state information based on carrier sensing data and acknowledgement signals received from an access point. A feature extraction and scoring unit extracts features from the device state information and generates scores for each RU representative of possibility of successful transmission based on the extracted features. A reward computation unit computes reward for providing feedback on prediction accuracy of the scores. A controller determines a RU used to transmit data based on the scores. The controller stores experiences including the device state information and the reward in a memory unit. The controller updates parameters of the feature extraction and scoring unit based on the experiences stored in the memory unit.

Abstract: A beam selection system that includes a memory operably connected to processing circuitry. The memory configured to store instructions that request call control information from a device; receive a plurality of user equipment (UE) trajectories and parameters from the device; predict with a first artificial intelligence (AI) engine a plurality of beam patterns within a beam index at a plurality of nodes corresponding with a predicted UE location based on the plurality of UE trajectories and parameters of each UE; transmit the plurality of predicted beam patterns to the plurality of nodes corresponding with a corresponding UE of a plurality of UEs; receive a plurality of UE selected beam patterns from the plurality of nodes; train a second AI engine based the plurality of UE selected beam patterns. The processing circuitry is further configured to update the first AI engine based on learned results from the second AI engine.