Invention Grant
- Patent Title: Spectral sensing and allocation using deep machine learning
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Application No.: US15973003Application Date: 2018-05-07
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Publication No.: US11190944B2Publication Date: 2021-11-30
- Inventor: James Michael Shima
- Applicant: Ball Aerospace & Technologies Corp.
- Applicant Address: US CO Boulder
- Assignee: Ball Aerospace & Technologies Corp.
- Current Assignee: Ball Aerospace & Technologies Corp.
- Current Assignee Address: US CO Boulder
- Agency: Sheridan Ross P.C.
- Main IPC: H04W16/10
- IPC: H04W16/10 ; H04B7/0413 ; G06N3/06 ; G06N3/04 ; G06N3/08 ; H04W16/14 ; H04W24/02

Abstract:
Methods and systems for identifying occupied areas of a radio frequency (RF) spectrum, identifying areas within that RF spectrum that are unusable for further transmissions, and identifying areas within that RF spectrum that are occupied but that may nonetheless be available for additional RF transmissions are provided. Implementation of the method then systems can include the use of multiple deep neural networks (DNNs), such as convolutional neural networks (CNN's), that are provided with inputs in the form of RF spectrograms. Embodiments of the present disclosure can be applied to cognitive radios or other configurable communication devices, including but not limited to multiple inputs multiple output (MIMO) devices and 5G communication system devices.
Public/Granted literature
- US20180324595A1 SPECTRAL SENSING AND ALLOCATION USING DEEP MACHINE LEARNING Public/Granted day:2018-11-08
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