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US Patent 11032014 Processing of communications signals using machine learning

Patent 11032014 was granted and assigned to Virginia Tech Intellectual Properties on June, 2021 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
Virginia Tech Intellectual Properties
Virginia Tech Intellectual Properties
Current Assignee
Virginia Tech Intellectual Properties
Virginia Tech Intellectual Properties
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11032014
Date of Patent
June 8, 2021
Patent Application Number
16744369
Date Filed
January 16, 2020
Patent Citations
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US Patent 10541765 Processing of communications signals using machine learning
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US Patent 10396919 Processing of communications signals using machine learning
Patent Citations Received
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US Patent 12137350 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
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US Patent 11553353 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
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US Patent 11570627 System, method, and apparatus for providing optimized network resources
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US Patent 11576050 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
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US Patent 11582613 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
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US Patent 12133084 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
0
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US Patent 12137349 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
0
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US Patent 11490262 System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
...
Patent Primary Examiner
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Nguyen T Vo
Patent abstract

One or more processors control processing of radio frequency (RF) signals using a machine-learning network. The one or more processors receive as input, to a radio communications apparatus, a first representation of an RF signal, which is processed using one or more radio stages, providing a second representation of the RF signal. Observations about, and metrics of, the second representation of the RF signal are obtained. Past observations and metrics are accessed from storage. Using the observations, metrics and past observations and metrics, parameters of a machine-learning network, which implements policies to process RF signals, are adjusted by controlling the radio stages. In response to the adjustments, actions performed by one or more controllers of the radio stages are updated. A representation of a subsequent input RF signal is processed using the radio stages that are controlled based on actions including the updated one or more actions.

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