- Patent Title: Machine learning based digital pre-distortion for power amplifiers
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Application No.: US17331145Application Date: 2021-05-26
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Publication No.: US11431300B2Publication Date: 2022-08-30
- Inventor: Oana-Elena Barbu , Benny Vejlgaard , Johannes Harrebek
- Applicant: Nokia Technologies Oy
- Applicant Address: FI Espoo
- Assignee: Nokia Technologies Oy
- Current Assignee: Nokia Technologies Oy
- Current Assignee Address: FI Espoo
- Agency: Harrington & Smith
- Priority: FI20205611 20200612
- Main IPC: H03F1/32
- IPC: H03F1/32 ; H03F3/24 ; H04B1/04

Abstract:
Example embodiments relate to machine learning based digital pre-distortion for power amplifiers. A device may amplify a signal with a power amplifier and transmit the signal. The signal may be received by an internal feedback receiver of the device. The device may further comprise a first machine learning model configured to emulate an external feedback receiver and to generate an emulated feedback signal based on the internal feedback signal. The device may further comprise a second machine learning model configured to determine digital pre-distortion parameters for the power amplifier based on the emulated feedback signal. Apparatuses, methods, and computer programs are disclosed.
Public/Granted literature
- US20210391832A1 MACHINE LEARNING BASED DIGITAL PRE-DISTORTION FOR POWER AMPLIFIERS Public/Granted day:2021-12-16
Information query
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