Methods for enhanced sidelink communications with clustered or peer-to-peer federated learning

Abstract

Aspects are provided which allow a UE to achieve sidelink parameter coordination through various signaling in clustered FL or peer-to-peer FL. The UE provides a first ML model information update and a measurement associated with the update. The UE obtains an aggregated ML model information update aggregating the first update with a second ML model information update of either a first network node in a FL cluster including the UE or a second network node in a second FL cluster. The UE provides a sidelink communication parameter in SCI to a network node, which parameter is an output of an ML model associated with the aggregated ML model information update. As a result, UEs may derive common SCI parameters from their updated ML models to apply in sidelink communications, thereby leading to maximized packet reception rate, maximized throughput, or minimized latency in communication.