Machine learning at a wireless device

Abstract

Various aspects of the present disclosure relate to machine learning at a wireless device. An apparatus, such as a node (e.g., a user equipment (UE) and / or a network entity (NE)), receives a set of data samples associated with a wireless channel from at least one second node. The first node obtains subsets of data samples from the set of data samples, where the subsets of data samples include at least a first subset of data samples and a second subset of data samples. The first node determines one or more parameters for a machine learning model of a wireless device associated with the first node from the subsets of data samples. In some examples, the first node transmits the parameters for the machine learning model to a second node for implementing at a machine learning model of a wireless device associated with the second node.

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