Performance monitoring for ai/ml models in wireless communication systems

A user equipment (UE) comprising at least one processor and at least one memory storing instructions that, when executed by the at least one processor, cause the UE to:

• receive a configuration identifying a monitoring window comprising a plurality of monitoring resource instants;
• obtain measurements of reference signals transmitted at the monitoring resource instants;
• associate each of the monitoring resource instants with at least one inference result produced by an artificial-intelligence (AI) or machine-learning (ML) model;
• determine a performance metric by comparing information based on the inference result with information based on the measurements;
• and
• transmit the performance metric in a performance monitoring report.

A system comprising a network node configured to:

• provide a configuration identifying a monitoring window comprising a plurality of monitoring resource instants to a user equipment (UE);
• receive measurements of reference signals obtained by the UE at the monitoring resource instants;
• receive at least one inference result produced by an artificial-intelligence (AI) or machine-learning (ML) model executed at the UE;
• receive a performance monitoring report containing a performance metric determined by the UE based on comparing information based on the inference result with information based on the measurements;
• and
• process the performance metric to evaluate performance of the AI or ML model.