The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 22, 2020

Filed:

Aug. 23, 2017
Applicant:

Futurewei Technologies, Inc., Plano, TX (US);

Inventors:

Ying Li, Hillsborough, NJ (US);

Jin Yang, Bridgewater, NJ (US);

Xin Li, Xian, CN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H04L 12/24 (2006.01); H04L 12/26 (2006.01); G06N 20/00 (2019.01); H04W 24/02 (2009.01); H04W 24/08 (2009.01);
U.S. Cl.
CPC ...
H04L 41/0816 (2013.01); G06N 20/00 (2019.01); H04L 41/0823 (2013.01); H04L 43/022 (2013.01); H04W 24/02 (2013.01); H04L 41/145 (2013.01); H04L 41/147 (2013.01); H04L 41/16 (2013.01); H04L 43/08 (2013.01); H04L 43/16 (2013.01); H04W 24/08 (2013.01);
Abstract

The disclosure relates to technology for configuring parameters in a wireless communications network. Parameter configurations resulting in a change to key quality indicator (KQI) and key performance indicator (KPI) measurements are determined based on collected data samples. The data samples are divided into subsets including a first subset including the data samples associated with the parameter configurations failing to result in the change to the KQI and KPI measurements, and a second subset including the data samples associated with the parameter configurations resulting in the change to the KQI and KPI measurements dependent upon satisfying conditions in the wireless communications network. The subsets of the data samples are then determined for using machine learning to optimize the parameter configurations, and subsets of the data samples are provided as an input to machine learning for the parameter configurations to optimize the wireless communications network.


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