Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Digital pre-distortion training method and device and storage medium

A technology of digital pre-distortion and training method, applied in synchronization/start-stop system, advanced technology, climate sustainability, etc., can solve the problems of single pre-distortion technology structure, inability to meet, poor flexibility of neural network, etc., to reduce training Weight parameters, ensure model convergence, and improve the effect of generality

Pending Publication Date: 2022-06-07
CHINA MOBILE COMM LTD RES INST +1
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The present invention provides a digital pre-distortion training method, device and storage medium, which are used to solve the problems that the existing neural network-based pre-distortion technology has a single structure, poor flexibility, and cannot meet the needs of future intelligent and open networks

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Digital pre-distortion training method and device and storage medium
  • Digital pre-distortion training method and device and storage medium
  • Digital pre-distortion training method and device and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0066] During the process of the invention, the inventors noticed:

[0067] The traditional digital predistortion technology is realized by the polynomial method. The basic realization principle is to find a polynomial that can approximate the inverse function of the complex gain characteristic curve of the power amplifier. After obtaining the inverse function, the predistortion value of the original input signal is obtained by calculation.

[0068] The higher the order of the digital predistortion model of the polynomial method, the higher the modeling accuracy, but the calculation amount of parameter estimation increases exponentially with the increase of the polynomial order. Most of the polynomial models only consider the amplitude model, ignoring the phase compensation of the signal, which affects the accuracy of the digital predistortion model. In addition, the polynomial method uniformly establishes the digital predistortion model based on polynomials. The model is fixed a...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a digital pre-distortion training method and device and a storage medium. The method comprises the following steps: performing digital pre-distortion training on a first input parameter by adopting a first digital pre-distortion training model to obtain a first training result; and adopting a second digital pre-distortion training model to carry out digital pre-distortion training on the second input parameter and the first training result. According to the invention, the accuracy of the trained digital pre-distortion model can be ensured through joint optimization, the network structure is simplified, and training weight parameters are reduced. The pre-distortion model can be trained for multiple PAs, the modeling precision is improved, and the universality of the model architecture is improved. Different neural network models or combined models can be adopted according to requirements, the structure is flexible, model convergence can be guaranteed, different RRU power amplifier requirements are met, and resource sharing is achieved.

Description

technical field [0001] The present invention relates to the technical field of wireless communication, and in particular, to a digital predistortion training method, device and storage medium. Background technique [0002] Power amplifiers are an important part of wireless communication systems. The nonlinear characteristics of power amplifiers lead to in-band nonlinear distortion and out-of-band spectral leakage, so the linearization technology of power amplifiers has attracted much attention. [0003] In order to suppress the nonlinear distortion of the power amplifier and maintain high output power to improve the efficiency of the amplifier, digital predistortion technology has been widely used. Digital predistortion technology is to generate an opposite predistortion signal by estimating the nonlinear model of the power amplifier in the digital domain. After the predistortion signal is nonlinearly amplified by the power amplifier, the nonlinear distortion signal compone...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H04L25/49H04L41/14
CPCH04L25/49H04L41/145Y02D30/70
Inventor 林英超王桂珍鄢凯
Owner CHINA MOBILE COMM LTD RES INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com