US 11,990,970 B2
Methods and apparatuses of multi-user multiple-input multiple-output beam selection and user pairing using deep learning
Ian Dexter Garcia, Naperville, IL (US); Igor Filipovich, Chicago, IL (US); Chandrasekar Sankaran, Hoffman Estates, IL (US); Hua Xu, Hawthorn Woods, IL (US); Suresh Kalyanasundaram, Bangalore (IN); Jamil Shihab, Algonquin, IL (US); Rajeev Agrawal, Glenview, IL (US); and Anand Bedekar, Glenview, IL (US)
Assigned to Nokia Technologies Oy, Espoo (FI)
Appl. No. 17/252,966
Filed by Nokia Technologies Oy, Espoo (FI)
PCT Filed Jun. 20, 2019, PCT No. PCT/EP2019/066351
§ 371(c)(1), (2) Date Dec. 16, 2020,
PCT Pub. No. WO2020/002127, PCT Pub. Date Jan. 2, 2020.
Claims priority of application No. 201811024097 (IN), filed on Jun. 28, 2018.
Prior Publication US 2021/0218460 A1, Jul. 15, 2021
Int. Cl. H04W 72/04 (2023.01); G06N 20/00 (2019.01); H04B 7/0452 (2017.01); H04B 7/06 (2006.01)
CPC H04B 7/0695 (2013.01) [G06N 20/00 (2019.01); H04B 7/0452 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
selecting multi-user multiple input multiple output candidate beams using one or more deep neural networks;
selecting, by a single-stage deep neural network beam selector, the candidate beams simultaneously through a single pass of the deep neural network; and
selecting paired users based on the selected beams,
wherein the one or more deep neural networks are trained to maximize a multi-user priority metric or a heuristic of the multi-user priority metric.