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AssigneeNokia Solutions and Networks Oy
InventorsIstván Zsolt KOVÁCS, Muhammad Majid BUTT, Jian SONG, Klaus Ingemann PEDERSEN
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The present disclosure relates to a machine-learning (ML) orchestrator entity that provides distributed, flexible, and efficient parameter initialization for ML agents installed on network nodes operating under similar radio conditions. For this end, the ML orchestrator entity instructs two or more of the network nodes to run two or more ML agents in a training mode, which results in generating two or more sets of parameters. Then, the ML orchestrator entity uses the sets of parameters to derive a common set of parameters for the network nodes. The common set of parameters is to be used in an inference mode of the ML agent at each of the network nodes. The transmission of the common set of parameters to the network nodes may be subsequently initiated by the ML orchestrator entity itself or by each of the network nodes independently.
A machine-learning (ML) orchestrator entity in a wireless communication network, comprising:
A method for operating a machine-learning (ML) orchestrator entity in a wireless communication network, said method comprising:
Dependencies are inferred from the claim text.