US 12,075,346 B2
Determining a machine-learning architecture for network slicing
Jibing Wang, San Jose, CA (US); and Erik Richard Stauffer, Sunnyvale, CA (US)
Assigned to Google LLC, Mountain View, CA (US)
Appl. No. 17/753,816
Filed by Google LLC, Mountain View, CA (US)
PCT Filed Oct. 31, 2019, PCT No. PCT/US2019/059094
§ 371(c)(1), (2) Date Mar. 15, 2022,
PCT Pub. No. WO2021/086369, PCT Pub. Date May 6, 2021.
Prior Publication US 2022/0353803 A1, Nov. 3, 2022
Int. Cl. H04W 48/18 (2009.01); G06F 18/20 (2023.01); H04L 41/16 (2022.01); H04W 8/08 (2009.01); H04W 24/10 (2009.01); H04W 64/00 (2009.01)
CPC H04W 48/18 (2013.01) [G06F 18/285 (2023.01); H04L 41/16 (2013.01); H04W 8/08 (2013.01); H04W 24/10 (2013.01); H04W 64/003 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method performed by a user equipment, the method comprising:
executing a first application associated with a first requested quality-of-service level;
selecting a first machine-learning architecture based on the first requested quality of-service level;
transmitting, to a network-slice manager of a wireless network, a first machine-learning architecture request message to request permission to use the first machine-learning architecture;
receiving, from the network-slice manager, a first machine-learning architecture response message that grants permission to use the first machine-learning architecture based on a first network slice; and
wirelessly communicating data for the first application using the first machine learning architecture.