Dynamic model management and post-deployment verification for beam management spatial prediction

A server device, comprising:

• a memory;
• and
• one or more processors configured to, when executing instructions stored in the memory, cause the server device to:
• create and train one or more artificial intelligence (AI)/machine learning (ML) models for beam management spatial prediction;
• determine model configuration information for the one or more AI/ML models;
• communicate the one or more AI/ML models and the model configuration information to a user equipment (UE);
• and
• receive, from the UE, a performance score corresponding to at least one AI/ML model of the one or more AI/ML models.

A method, performed by a user equipment (UE), the method comprising:

• determining measurements for beam pairs associated with a set of transmission (Tx) beams and a Tx beam pattern;
• determining whether conditions associated with deploying one or more artificial intelligence (AI)/machine learning (ML) models are satisfied;
• determining whether a data distribution of output data of each AI/ML model of the one or more AI/ML models is valid, the output data comprising predicted reference signal received powers (RSRPs) of a plurality of beam pairs;
• and
• determining, for the one or more AI/ML models with a valid data distribution, a model validity based on the predicted RSRPs of the plurality of beam pairs and measured RSRPs of the plurality of beam pairs.