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Nonlinear modeling method of wideband transmitter based on dynamic multi-core bandwidth generalized regression neural network algorithm

A generalized regression and neural network technology, applied in the field of nonlinear distortion modeling and correction of transmitters, can solve problems such as changes in nonlinear characteristics

Active Publication Date: 2021-07-06
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

According to the actual measurement, in this mode, the nonlinear characteristics of the transmitter will change significantly with the change of frequency, and the magnitude of the change does not have a monotonous relationship with the change of frequency, and the wideband work will also bring serious problems. memory effect, so it is difficult to use simple mathematical expressions to describe the nonlinear characteristics of wideband transmitters

Method used

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  • Nonlinear modeling method of wideband transmitter based on dynamic multi-core bandwidth generalized regression neural network algorithm
  • Nonlinear modeling method of wideband transmitter based on dynamic multi-core bandwidth generalized regression neural network algorithm
  • Nonlinear modeling method of wideband transmitter based on dynamic multi-core bandwidth generalized regression neural network algorithm

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Embodiment Construction

[0054] Embodiments of the present invention are described below with reference to the accompanying drawings, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific examples, and various modifications and changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention.

[0055] refer to figure 1 , the method includes the following steps: by building a test platform, measuring and recording the non-linear characteristics of the full operating frequency band of the wide-band transmitter, collecting the input and output amplitude and phase values ​​of the test signal, and the corresponding carrier frequency, and analyzing the signal samples according to the carrier frequency Carry out segmentati...

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Abstract

The invention discloses a nonlinear modeling method of a broadband transmitter based on a dynamic multi-core bandwidth generalized regression neural network algorithm. The input and output amplitude and phase values, as well as the corresponding carrier frequency; according to the carrier frequency, the signal samples are segmented, and the amplitude of the input signal is quantified by using the amplitude non-uniform quantization technology, and the dynamic non-uniform Construction of linear fingerprint sample data set; use dynamic nonlinear fingerprint sample data set to train generalized regression neural network, combined with optimization algorithm to obtain dynamic multi-core bandwidth generalized regression neural network model, and realize full-band nonlinear feature modeling of broadband transmitters.

Description

technical field [0001] The invention relates to the technical field of transmitter design in wireless communication, in particular to the nonlinear distortion modeling and correction technology of the transmitter. By measuring the signal of the wide-band transmitter when it is working in the full frequency band, extracting the characteristic mode to form the training sample data, using the learning algorithm and the neural network model to fit the nonlinear characteristics of the transmitter, for the linearity of the transmitter pre-distortion correction technology provides the basis for the model. Background technique [0002] The nonlinear distortion of the broadband transmitter is mainly caused by the nonlinear characteristics of the RF power amplifier. Mainly manifested as amplitude distortion and phase distortion of the signal: After the signal passes through the nonlinear power amplifier, the gain of the output signal amplitude changes with the input signal amplitude,...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B17/13H04B17/12H04B17/00G06N3/04
CPCH04B17/0087H04B17/12H04B17/13H04B2001/0425G06N3/045
Inventor 陈章张江姚富强魏志虎周强陈剑斌朱蕾何攀峰
Owner NAT UNIV OF DEFENSE TECH
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