Network controlled machine learning in user equipment

Abstract

Embodiments include methods for managed machine learning (ML) in a communication network, such as by one or more first network functions (NFs) of the communication network. Such methods include determining whether processing of an ML model in the communication network should be distributed to one or more user equipment (UEs) operating in the communication network, based on characteristics of the respective UEs. Such methods also include, based on determining that the processing of the ML model should be distributed to the one or more UEs, establishing trusted execution environments (TEEs) in the respective UEs and distributing the ML model for processing in the respective TEEs. Other embodiments include complementary methods for UEs, as well as UEs and NFs (or communication networks) configured to perform such methods.

Dependencies are inferred from the claim text.