Machine learning based digital pre-distortion for power amplifiers

A power amplifier and digital pre-distortion technology, applied in power amplifiers, improved amplifiers to reduce nonlinear distortion, amplifiers, etc., can solve problems such as error vector magnitude degradation, violation of out-of-band transmission standards, bit error rate data throughput degradation, etc.

Pending Publication Date: 2021-12-17
NOKIA TECHNOLOGLES OY
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

For example, nonlinearities in power amplifiers can generate spectral re-growth, which can cause adjacent channel interference or violate out-of-band transmission standards set by t

Method used

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  • Machine learning based digital pre-distortion for power amplifiers
  • Machine learning based digital pre-distortion for power amplifiers
  • Machine learning based digital pre-distortion for power amplifiers

Examples

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Embodiment Construction

[0032] Reference will be made in detail in example embodiments, examples of which are illustrated in the accompanying drawings. The detailed description provided below with respect to the figures is intended as a description of the presented examples and is not intended to represent the only forms in which the examples may be constructed or utilized. The description sets forth the functionality of the example and a possible sequence of steps for the construction and operation of the example. However, the same or equivalent functions and sequences can be implemented by other examples.

[0033] Nonlinear power amplifiers can have various side effects. To reduce non-linearities, the power amplifier can be operated at low power, for example in a back-off mode within the linear part of its operating curve. However, some transmission systems such as Wideband Code Division Multiple Access (WCDMA) systems and Orthogonal Frequency Division Multiplexing (OFDM) systems such as Wireless...

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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.

Description

technical field [0001] This application relates generally to power amplifiers. In particular, some example embodiments of the invention relate to machine learning based digital predistortion for power amplifiers. Background technique [0002] Power amplifiers affect the performance and throughput of communication systems. For example, nonlinearities in power amplifiers can generate spectral re-growth that can cause adjacent channel interference or violate out-of-band transmission standards set by regulatory bodies. Furthermore, non-linearities can cause in-band distortions that degrade the magnitude of the error vector and ultimately the bit error rate (BER) and data throughput. Machine learning (ML) or other automated processes can be used for different applications in different types of devices such as, for example, mobile phones. In general, machine learning enables computational models, such as neural networks, to be trained to perform specific tasks on input data. ...

Claims

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Application Information

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IPC IPC(8): H03F1/32
CPCH03F1/32H03F1/3247H03F3/19H03F3/245H03F2201/3227H03F2201/3231H03F2200/451G06N3/08G06N3/047G06N3/045H03F1/3258H03F3/24H03F2201/3233H04B1/04H04B2001/0425
Inventor O-E·巴尔布B·维杰尔加德J·哈雷贝克
Owner NOKIA TECHNOLOGLES OY
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