QUALCOMM Incorporated
ARCHITECTURE FOR MACHINE LEARNING (ML) ASSISTED COMMUNICATIONS NETWORKS

Abstract:

An apparatus for wireless communications has a first component and a second component. The first component is within an application layer and configured to control machine learning modules in different nodes. The second component is within the application layer and configured to control data flow between the different nodes. A method of wireless communications, by a first node, comprises collecting measurements related to wireless communications and transmitting the measurements to a second node for machine learning processing. The method also includes transmitting the measurements to a third node for neural network training. A method by a user equipment (UE) includes reporting a UE capability to a server, and configuring neural network parameters in response to server feedback. The method further includes executing a neural network with the configured neural network parameters to determine a wireless communications analysis, and reporting the analysis to the server.