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:
Jun. 17, 2025

Filed:

Nov. 09, 2020
Applicant:

Telefonaktiebolaget Lm Ericsson (Publ), Stockholm, SE;

Inventors:

Jaeseong Jeong, Solna, SE;

Filippo Vannella, Stockholm, SE;

Rodrigo Correia, Athlone, IE;

Vladimir Verbulskii, Athlone, IE;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04W 24/10 (2009.01); G06N 3/02 (2006.01); H01Q 1/12 (2006.01); H04L 41/12 (2022.01); H04W 24/02 (2009.01);
U.S. Cl.
CPC ...
H04W 24/10 (2013.01); G06N 3/02 (2013.01); H01Q 1/125 (2013.01); H04L 41/12 (2013.01); H04W 24/02 (2013.01);
Abstract

A method performed by a computer system for a telecommunications network. The computer system can access a network metrics repository to retrieve a baseline dataset collected from a baseline policy deployed in the telecommunications network for controlling a configurable parameter of the telecommunications network. The configurable parameter includes an antenna tilt degree. The baseline dataset includes key performance indicators (KPIs) that include KPIs having a continuous value and a plurality of historical changes made to the configurable parameter. The computer system can train a policy model while offline the telecommunications network using the baseline dataset and inverse propensity scoring on the input KPIs having continuous values to output from the policy model a probability of actions for controlling the configurable parameter. A method performed by network node or network nodes is also provided for using a trained policy model to control the configuration parameter.


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