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:
Oct. 01, 2024

Filed:

Aug. 31, 2022
Applicant:

Hughes Network Systems, Llc, Germantown, MD (US);

Inventors:

Amit Arora, Clarksburg, MD (US);

Kartik Seshadri, Boyds, MD (US);

Sairaj Amberkar, Rockville, MD (US);

Sonia Thakur, Germantown, MD (US);

Namrata Walanj, Germantown, MD (US);

Assignee:

Hughes Network Systems, LLC, Germantown, MD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 43/04 (2022.01); G06F 18/214 (2023.01); G06N 3/02 (2006.01); G06N 20/00 (2019.01); H04B 7/185 (2006.01); H04L 41/16 (2022.01); H04L 43/02 (2022.01); H04L 43/062 (2022.01); H04W 24/04 (2009.01);
U.S. Cl.
CPC ...
H04L 43/04 (2013.01); G06F 18/214 (2023.01); G06N 3/02 (2013.01); G06N 20/00 (2019.01); H04B 7/18519 (2013.01); H04L 41/16 (2013.01); H04L 43/02 (2013.01); H04L 43/062 (2013.01); H04W 24/04 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for using machine learning to detect and correct satellite terminal performance limitations. In some implementations, a system retrieves data indicating labels for clusters of network performance anomalies. The system generates a set of training data to train a machine learning model, the set of training data being generated by assigning the labels for the clusters to sets of performance indicators used to generate the clusters. The system trains a machine learning model to predict classifications for communication devices based on input of performance indicators for the communication devices. The system determines a classification for the communication device based on output that the trained machine learning model generates.


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