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US Patent 11303041 Machine learning-based antenna array validation, prototyping and optimization

Patent 11303041 was granted and assigned to Cypress Semiconductor on April, 2022 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
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Patent attributes

Patent Applicant
Cypress Semiconductor
Cypress Semiconductor
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Current Assignee
Cypress Semiconductor
Cypress Semiconductor
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
113030410
Patent Inventor Names
Aidan Smyth0
Zhuohui Zhang0
Victor Simileysky0
Kiran Uln0
Date of Patent
April 12, 2022
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Patent Application Number
165843830
Date Filed
September 26, 2019
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Patent Citations
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US Patent 10312587 Designing an antenna array to meet specified performance criteria
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US Patent 10127412 Location estimation and tracking for passive RFID and wireless sensor networks using MIMO systems
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US Patent 10142909 Artificial intelligence-augmented, ripple-diamond-chain shaped rateless routing in wireless mesh networks with multi-beam directional antennas
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US Patent 10275707 Systems and methods for training multipath filtering systems
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US Patent 10302743 Systems and methods for antenna analysis and validation
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US Patent 10327159 Autonomous, closed-loop and adaptive simulated annealing based machine learning approach for intelligent analytics-assisted self-organizing-networks (SONs)
Patent Citations Received
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US Patent 12132262 Machine learning-based antenna array validation, prototyping and optimization
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Patent Primary Examiner
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Hasan Islam
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CPC Code
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H04L 27/36
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H01Q 21/24
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H01Q 3/26
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An example method of estimating the angular resolution of antenna array comprises: receiving a plurality of values of magnitude and phase of a radio frequency (RF) signal for each antenna element of a plurality of antenna elements comprised by an antenna array; performing, by a machine learning model, a feature extraction operation to transform the plurality of values of magnitude and phase into a plurality of data points in a reduced-dimension space; clustering, by the machine learning model, the plurality of data points into a plurality of clusters; and computing, based on the clustered data points, an angular resolution value for the antenna array.

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