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:
May. 21, 2024

Filed:

Feb. 17, 2022
Applicant:

Deepsig Inc., Arlington, VA (US);

Inventors:

Timothy J. O'Shea, Arlington, VA (US);

Ben Hilburn, Reston, VA (US);

Tamoghna Roy, Arlington, VA (US);

Nathan West, Washington, DC (US);

Assignee:

DeepSig Inc., Arlington, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04W 56/00 (2009.01); G06N 3/044 (2023.01); G06N 3/08 (2023.01); G06N 3/084 (2023.01); G06N 20/00 (2019.01); H04B 17/391 (2015.01); H04L 5/00 (2006.01); H04L 41/14 (2022.01); H04W 16/22 (2009.01); H04W 72/0453 (2023.01);
U.S. Cl.
CPC ...
H04W 56/0035 (2013.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G06N 3/084 (2013.01); G06N 20/00 (2019.01); H04B 17/3912 (2015.01); H04L 5/0005 (2013.01); H04L 41/145 (2013.01); H04W 16/22 (2013.01); H04W 72/0453 (2013.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels. In some implementations, information is obtained. An encoder network is used to process the information and generate a first RF signal. The first RF signal is transmitted through a first channel. A second RF signal is determined that represents the first RF signal having been altered by transmission through the first channel. Transmission of the first RF signal is simulated over a second channel implementing a machine-learning network, the second channel representing a model of the first channel. A simulated RF signal that represents the first RF signal having been altered by simulated transmission through the second channel is determined. A measure of distance between the second RF signal and the simulated RF signal is calculated. The machine-learning network is updated using the measure of distance.


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