US 12,231,184 B2
Processing communications signals using a machine-learning network
Timothy James O'Shea, Arlington, VA (US); Nathan West, Washington, DC (US); and Johnathan Corgan, San Jose, CA (US)
Assigned to DeepSig Inc., Arlington, VA (US)
Filed by DeepSig Inc., Arlington, VA (US)
Filed on Feb. 13, 2023, as Appl. No. 18/108,798.
Application 18/108,798 is a continuation of application No. 17/084,685, filed on Oct. 30, 2020, granted, now 11,581,965.
Application 17/084,685 is a continuation of application No. 16/856,760, filed on Apr. 23, 2020, granted, now 10,833,785, issued on Nov. 10, 2020.
Claims priority of provisional application 63/005,599, filed on Apr. 6, 2020.
Claims priority of provisional application 62/837,631, filed on Apr. 23, 2019.
Prior Publication US 2023/0299862 A1, Sep. 21, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. H04B 17/391 (2015.01); G06N 3/047 (2023.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); H04L 27/00 (2006.01)
CPC H04B 17/3911 (2015.01) [G06N 3/047 (2023.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); H04B 17/3912 (2015.01); H04L 27/0008 (2013.01)] 29 Claims
OG exemplary drawing
 
1. A method to process a received communication signal using at least one machine-learning network, the method comprising:
obtaining, at a first device, a received communication signal that includes data information, wherein one or more elements of the data information each correspond to a particular time and a particular frequency in a time-frequency spectrum, the received communication signal corresponding to a transmitted communication signal having been modified by transmission over a communications channel, the transmitted communication signal generated by a second device that is communicably coupled to the first device;
generating, by the first device, data extracted from the received communication signal, the extracted data corresponds to both time and frequency in the time-frequency spectrum;
processing, by the first device, the data extracted from the received communication signal using a machine-learning network that is trained to process communication signals;
in response to processing the data extracted from the received communication signal using the machine-learning network, obtaining, by the first device from the machine-learning network, an output result corresponding to the data extracted from the received communication signal, wherein the output result represents at least one of (i) an estimate of the communications channel communicably connecting the first device and the second device or (ii) an estimate of symbols transmitted in the received communication signal transmitted through the communications channel; and
updating, by the first device, the machine-learning network based on the output result and the received communication signal.