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:
Mar. 11, 2025

Filed:

Jan. 27, 2023
Applicant:

Qualcomm Incorporated, San Diego, CA (US);

Inventors:

Gaurang Naik, San Diego, CA (US);

Sai Yiu Duncan Ho, San Diego, CA (US);

George Cherian, San Diego, CA (US);

Yanjun Sun, San Diego, CA (US);

Abhishek Pramod Patil, San Diego, CA (US);

Alfred Asterjadhi, San Diego, CA (US);

Abdel Karim Ajami, Lakeside, CA (US);

Xiaolong Huang, Santee, CA (US);

Qiang Fan, Plainsboro, NJ (US);

Srinivas Katar, Fremont, CA (US);

Nitin Ravinder, San Diego, CA (US);

Venkata Savitri Pravallika Tallapragada, San Diego, CA (US);

Varshini Rajesh, New York, NY (US);

Raamkumar Balamurthi, San Diego, CA (US);

Assignee:

QUALCOMM Incorporated, San Diego, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 47/2441 (2022.01); H04L 43/08 (2022.01); H04L 43/16 (2022.01); H04L 47/10 (2022.01); H04W 28/08 (2023.01);
U.S. Cl.
CPC ...
H04L 47/2441 (2013.01); H04L 43/08 (2013.01); H04L 43/16 (2013.01); H04L 47/29 (2013.01); H04W 28/0908 (2020.05);
Abstract

Methods, systems, and devices for wireless communications are described. A first device may receive signaling associated with a traffic class from a second device. The first device may determine that the traffic class is included in a set of known traffic classes based on a set of features associated with the signaling. In response to determining that the traffic class is included in the set of known traffic classes, the first device may use a machine learning model to obtain a prediction of an application associated with the signaling. The prediction may be based on the set of features. The machine learning model may be trained at the first device or the second device. The first device may receive information associated with the machine learning model from the second device.


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