US 12,081,412 B2
Federated learning across UE and RAN
Ziyi Li, Beijing (CN); Alexander Sirotkin, Tel-Aviv (IL); Youn Hyoung Heo, Seoul (KR); Shu-ping Yeh, Campbell, CA (US); and Yi Guo, Shanghai (CN)
Assigned to Intel Corporation, Santa Clara, CA (US)
Filed by Intel Corporation, Santa Clara, CA (US)
Filed on Oct. 19, 2021, as Appl. No. 17/504,711.
Claims priority of provisional application 63/093,666, filed on Oct. 19, 2020.
Prior Publication US 2022/0038349 A1, Feb. 3, 2022
Int. Cl. H04L 41/16 (2022.01); G06N 20/00 (2019.01); H04B 17/391 (2015.01); H04W 24/02 (2009.01)
CPC H04L 41/16 (2013.01) [G06N 20/00 (2019.01); H04B 17/3913 (2015.01); H04W 24/02 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An apparatus for a 5th generation NodeB (gNB), the apparatus comprising:
processing circuitry to configure the gNB to:
transmit, to a user equipment (UE), Artificial Intelligence/Machine Learning (AI/ML) service information via at least one of a system information block (SIB) or dedicated radio resource control (RRC) signaling;
receive, from the UE after transmission of the AI/ML service information, a service request for an AI/ML model and local AI/ML capability of the UE;
determine whether the AI/ML model meets pre-defined performance criteria of an AI/ML use case;
in response to a determination that the AI/ML model meets the pre-defined performance criteria, transmit, to the UE, the AI/ML model;
receive, from the UE, training model updated parameters based on local training by the UE after reception of the AI/ML model;
aggregate the training model updated parameters from a plurality of UEs; and
update the AI/ML model based on the aggregated training model updated parameters; and
a memory configured to store the AI/ML model.