Invention Grant
- Patent Title: Learning communication systems using channel approximation
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Application No.: US17674020Application Date: 2022-02-17
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Publication No.: US11991658B2Publication Date: 2024-05-21
- Inventor: Timothy J. O'Shea , Ben Hilburn , Tamoghna Roy , Nathan West
- Applicant: DeepSig Inc.
- Applicant Address: US VA Arlington
- Assignee: DeepSig Inc.
- Current Assignee: DeepSig Inc.
- Current Assignee Address: US VA Arlington
- Agency: Fish & Richardson P.C.
- The original application number of the division: US16291936 2019.03.04
- Main IPC: H04W56/00
- IPC: H04W56/00 ; G06N3/044 ; G06N3/08 ; G06N3/084 ; G06N20/00 ; H04B17/391 ; H04L5/00 ; H04L41/14 ; H04W16/22 ; H04W72/0453

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.
Public/Granted literature
- US20220174634A1 LEARNING COMMUNICATION SYSTEMS USING CHANNEL APPROXIMATION Public/Granted day:2022-06-02
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