Techniques for machine learning scheme changing based at least in part on dynamic network changes

Abstract

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a first network node may receive assistance information indicating an occurrence of at least one dynamic network change, wherein the at least one dynamic network change corresponds to a change from a first network state to a second network state, wherein a first machine learning scheme is associated with the first network state, and wherein the first machine learning scheme includes a machine learning model for generating a prediction associated with a first serving cell and/or a machine tearning parameter associated with the machine tearning model. The first network node may identify, based at least in part on the assistance information, a second machine learning scheme associated with the second network state, and may perform a wireless communication based at least in part on the second machine learning scheme. Numerous other aspects are described.