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US Patent 10531415 Learning communication systems using channel approximation

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10531415
Date of Patent
January 7, 2020
Patent Application Number
16291936
Date Filed
March 4, 2019
Patent Citations Received
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US Patent 12081646 Adaptively controlling groups of automated machines
3
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US Patent 11928867 Group of neural networks ensuring integrity
4
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US Patent 11949465 Machine learning based channel state information estimation and feedback configuration
5
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US Patent 11991658 Learning communication systems using channel approximation
6
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US Patent 10749594 Learning-based space communications systems
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US Patent 10956807 Adaptive and interchangeable neural networks utilizing predicting information
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US Patent 11259260 Learning communication systems using channel approximation
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US Patent 11677605 Machine learning based uplink coverage enhancement using peak reduction tones
11
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Patent Primary Examiner
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Hoon J Chung
Patent 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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