CN107431495A - Digital pre-distortion bearing calibration and device - Google Patents

Digital pre-distortion bearing calibration and device Download PDF

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CN107431495A
CN107431495A CN201580078331.XA CN201580078331A CN107431495A CN 107431495 A CN107431495 A CN 107431495A CN 201580078331 A CN201580078331 A CN 201580078331A CN 107431495 A CN107431495 A CN 107431495A
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adjustment factor
amplifier
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CN107431495B (en
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肖宇翔
朱尔霓
尤览
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Huawei Technologies Co Ltd
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
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Abstract

The invention discloses a kind of digital pre-distortion bearing calibration and device, belong to the communications field.Methods described includes：Determined to preselect input signal dynamic linear models Dynamic gene in amplifier model according to pre-selection input signal, pre-selection input signal is at least two signals in default input signal group；Determined to preselect the nonlinear dynamic models Dynamic gene of input signal in amplifier model according to pre-selection input signal；Current input signal amplifier model is established according to the nonlinear dynamic models Dynamic gene of the dynamic linear models Dynamic gene of pre-selection input signal, pre-selection input signal；The DPD models of current input signal are obtained according to the amplifier model of current input signal；Digital pre-distortion correction is carried out to current input signal according to DPD models.The present invention solves the problem of model parameter acquisition process is more complicated, and modeling efficiency is relatively low, realizes the acquisition process of simplified model parameter, the effect of correction efficiency is improved, for predistortion correction.

Description

Digital predistortion correction method and device Technical Field
The present invention relates to the field of communications, and in particular, to a digital predistortion correction method and apparatus.
Background
A power amplifier is an important component of a transmitting device in a communication system. In a communication system, to meet transmission requirements, a power amplifier needs to operate at high efficiency while maintaining high linearity, and the efficiency and linearity tend to be contradictory in the design of the power amplifier. The Digital Pre-Distortion (DPD) technique is a key technique specially used for compensating the non-linear characteristic of a power amplifier. The technology establishes a DPD model according to the characteristics of a power amplifier, and carries out predistortion treatment on a current input signal in a digital domain, so that the treated predistortion signal can be offset with the nonlinear characteristics of the power amplifier after entering the power amplifier. By means of the DPD technology, the power amplifier can work in a high-efficiency state, and simultaneously, the linearity of the power amplifier can meet the index requirement.
In practical applications, the power of the output signal of the power amplifier is often dynamically adjusted in real time along with the change of traffic, and the change of the power of the output signal is often accompanied by the change of the characteristics of the power amplifier. In the existing DPD technique, the non-linearity correction for the dynamic power variation of the output signal is usually implemented by building a look-up table model related to the power value. The lookup table model stores the corresponding relationship between the model parameters and the power values of the preset DPD model in a table, and when the predistortion correction of the current input signal is required, the corresponding model parameters can be found according to the power values of the current input signal, the DPD model corresponding to the current input signal is determined according to the obtained model parameters, and the predistortion correction of the current input signal is performed according to the DPD model.
However, since the lookup table model needs to calculate and store the model parameters of the DPD model covering a sufficient power range in order to satisfy the calibration requirements of different input signals, the amount of data calculated and stored is very large. Therefore, the acquisition process of the model parameters is complex, and the correction efficiency is low.
Disclosure of Invention
The invention provides a digital predistortion correction method and device, aiming at solving the problems of complex acquisition process and low correction efficiency of model parameters. The technical scheme is as follows:
in a first aspect, a digital predistortion correction method is provided, the method comprising:
determining an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, wherein the amplifier model is used for indicating the relation of an output signal and a static model of the input signal and a dynamic model of the input signal, the dynamic model comprises a dynamic linear model and a dynamic nonlinear model, the dynamic linear model is used for indicating the linear characteristic in a variable of the input signal, the dynamic nonlinear model is used for indicating the nonlinear characteristic in the variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values;
determining an adjustment factor for a dynamic nonlinear model of the preselected input signal in the amplifier model from the preselected input signal;
establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal;
obtaining a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal;
and carrying out digital predistortion correction on the current input signal according to the DPD model of the current input signal.
With reference to the first aspect, in a first implementable manner, the establishing an amplifier model of a current input signal according to an adjustment factor of a dynamic linear model of the preselected input signal and an adjustment factor of a dynamic nonlinear model of the preselected input signal includes:
according to the adjustment factor of the dynamic linear model of the preselected input signal and the dynamic nonlinear model of the preselected input signalUsing an amplifier model formula to determine model coefficients of a static model of said current input signal
Figure PCTCN2015075606-APPB-000001
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000002
The amplifier model formula is as follows:
Figure PCTCN2015075606-APPB-000003
wherein N represents the number of sampling points of each input signal in the preset input signal set, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal set, r is an integer greater than or equal to 1, and
Figure PCTCN2015075606-APPB-000004
a set of output signals representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000005
A static model representing said set of preset input signals, saidA dynamic model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000007
A dynamic linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000008
A dynamic non-linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000009
An adjustment factor representing a dynamic linear model of the set of preset input signals, the
Figure PCTCN2015075606-APPB-000010
An adjustment factor representing a dynamic non-linear model of the set of preset input signals;
Figure PCTCN2015075606-APPB-000006
model coefficients of a static model to be based on the current input signalAnd model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000012
And substituting the current input signal into the amplifier model formula to establish an amplifier model corresponding to the current input signal.
In combination with the first implementable manner, in a second implementable manner,
determining the model coefficient of the static model of the current input signal by adopting an amplifier model formula according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000013
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000014
The method comprises the following steps:
determining an adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal;
determining an adjustment factor of a dynamic nonlinear model of the preset input signal set according to an adjustment factor of a dynamic nonlinear model of the preselected input signal;
determining the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group by substituting the adjustment factors into the amplifier model formula to obtain the model coefficients of the static model of the preset input signal group and the model coefficients of the dynamic model of the preset input signal group;
taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signal
Figure PCTCN2015075606-APPB-000015
Taking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000016
With reference to the second implementable manner, in a third implementable manner, the preselected input signals are the first input signals with the highest power value and the second input signals with the lowest power value in the preset input signal set,
the determining an adjustment factor for a dynamic linear model of a preselected input signal in an amplifier model from the preselected input signal comprises:
determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula;
determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula;
the linear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000017
wherein, the thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1Parameter value representing a dynamic linear characteristic parameter of the first input signal, said
Figure PCTCN2015075606-APPB-000018
An adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
With reference to the third implementable manner, in a fourth implementable manner,
the dynamic linear characteristic parameter is the average power of the output signals corresponding to the preset input signal group in the power amplifier or the gain of the output signals corresponding to the preset input signal group in the power amplifier.
With reference to the third implementable manner, in a fifth implementable manner,
the determining an adjustment factor for a dynamic non-linear model of the preselected input signal in the amplifier model from the preselected input signal comprises:
determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula is as follows:
Figure PCTCN2015075606-APPB-000019
wherein, theThe above-mentioned
Figure PCTCN2015075606-APPB-000020
A parameter value representing a dynamic non-linear characteristic parameter of said preselected input signal, said x(i)(n) represents the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to said preselected input signal;
determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000021
wherein, the
Figure PCTCN2015075606-APPB-000022
A parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
With reference to the fifth implementable manner, in a sixth implementable manner,
the determining the adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal comprises:
determining the adjustment factor of the dynamic linear model of the preset input signal set by adopting a first interpolation formula according to the adjustment factor of the dynamic linear model of the preselected input signal set
Figure PCTCN2015075606-APPB-000023
The first interpolation formula is:
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal, and the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signalAn adjustment factor representing a dynamic linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000026
An adjustment factor representing a dynamic linear model of the second input signal, w(r)Representing a weight factor w(r)The weight formula is determined according to the weight formula, wherein the weight formula is as follows:
wherein, the PrRepresenting the power level of an input signal of power level r, PMRepresenting a power value of said first input signal having a power magnitude M;
the determining the adjustment factor of the dynamic nonlinear model of the preset input signal set according to the adjustment factor of the dynamic nonlinear model of the preselected input signal comprises:
determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by adopting a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000028
The second interpolation formula is:
Figure PCTCN2015075606-APPB-000029
wherein, the
Figure PCTCN2015075606-APPB-000030
An adjustment factor representing a dynamic non-linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000031
An adjustment factor representing a dynamic non-linear model of the second input signal, w(r)Representing a weighting factor.
With reference to any one of the first aspect to the sixth implementable manner, in a seventh implementable manner, after the performing digital predistortion correction on the current input signal according to the DPD model, the method further includes:
and when the state of the power amplifier changes, updating the DPD model of the current input signal to obtain an updated amplifier model.
With reference to the seventh implementable manner, in an eighth implementable manner,
the state change of the power amplifier is device aging, temperature fluctuation or bias voltage change.
With reference to the seventh or eighth implementation manner, in a ninth implementation manner, the updating the amplifier model of the current input signal to obtain an updated amplifier model includes:
obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal;
obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal;
and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
With reference to the ninth implementable manner, in a tenth implementable manner,
the obtaining of the model coefficient of the dynamic model of the updated amplifier model according to the amplifier model of the current input signal includes:
taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value;
and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
With reference to the ninth implementable manner, in an eleventh implementable manner,
the obtaining of the model coefficient of the updated static model of the amplifier model according to the amplifier model of the current input signal includes:
taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value;
and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the static model of the updated amplifier model.
In a second aspect, there is provided a digital predistortion correction apparatus, comprising:
a first determining unit, configured to determine, according to a preselected input signal, an adjustment factor of a dynamic linear model of the preselected input signal in an amplifier model, where the amplifier model is used to indicate a relationship between an output signal and a static model of the input signal and a dynamic model of the input signal, and the dynamic model includes a dynamic linear model and a dynamic nonlinear model, where the dynamic linear model is used to indicate a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used to indicate a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group includes a plurality of input signals with different power values;
a second determination unit for determining an adjustment factor of a dynamic non-linear model of the preselected input signal in the amplifier model from the preselected input signal;
the establishing unit is used for establishing an amplifier model of the current input signal according to the adjusting factor of the dynamic linear model of the preselected input signal and the adjusting factor of the dynamic nonlinear model of the preselected input signal;
the processing unit is used for obtaining a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal;
and the correcting unit is used for carrying out digital predistortion correction on the current input signal according to the DPD model of the current input signal.
With reference to the second aspect, in a first implementable manner, the establishing unit includes:
a first determining module for determining the model coefficient of the static model of the current input signal by adopting an amplifier model formula according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signalAnd model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000033
The amplifier model formula is as follows:
wherein N represents the number of sampling points of each input signal in the preset input signal set, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal set, r is an integer greater than or equal to 1, and
Figure PCTCN2015075606-APPB-000035
a set of output signals representing said set of preset input signals, saidA static model representing said set of preset input signals, saidA dynamic model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000038
A dynamic linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000039
A dynamic non-linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000040
An adjustment factor representing a dynamic linear model of the set of preset input signals, the
Figure PCTCN2015075606-APPB-000041
An adjustment factor representing a dynamic non-linear model of the set of preset input signals;
Figure PCTCN2015075606-APPB-000037
a first substitution module for substituting model coefficients of the static model of the current input signal
Figure PCTCN2015075606-APPB-000042
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000043
And substituting the current input signal into the amplifier model formula to obtain an amplifier model corresponding to the current input signal.
With reference to the first implementable manner, in a second implementable manner, the first determining module includes:
the first determining submodule is used for determining the adjusting factor of the dynamic linear model of the preset input signal group according to the adjusting factor of the dynamic linear model of the preselected input signal;
the second determining submodule is used for determining the adjusting factor of the dynamic nonlinear model of the preset input signal group according to the adjusting factor of the dynamic nonlinear model of the preselected input signal;
the substituting submodule is used for substituting the adjusting factor of the dynamic linear model of the preset input signal group and the adjusting factor of the dynamic nonlinear model of the preset input signal group into the amplifier model formula to obtain a model coefficient of the static model of the preset input signal group and a model coefficient of the dynamic model of the preset input signal group;
a first processing submodule for using the model coefficients of the static model of the preset input signal set as the model coefficients of the static model of the current input signal
Figure PCTCN2015075606-APPB-000044
Taking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000045
With reference to the second implementable manner, in a third implementable manner, the preselected input signal is a first input signal with a highest power value and a second input signal with a lowest power value in the preset input signal group, and the first determining unit includes:
a second determining module, configured to determine an adjustment factor of a dynamic linear model of the first input signal according to a linear adjustment factor formula and a dynamic linear characteristic parameter of the first input signal;
a third determining module, configured to determine an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula;
the linear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000046
wherein, the thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1Parameter value representing a dynamic linear characteristic parameter of the first input signal, said
Figure PCTCN2015075606-APPB-000047
An adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
With reference to the third implementable manner, in a fourth implementable manner,
the dynamic linear characteristic parameter is the average power of the output signals corresponding to the preset input signal group in the power amplifier or the gain of the output signals corresponding to the preset input signal group in the power amplifier.
With reference to the third implementable manner, in a fifth implementable manner,
the second determination unit includes:
a fourth determining module, configured to determine a parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, where the nonlinear characteristic formula is:
wherein, the
Figure PCTCN2015075606-APPB-000049
A parameter value representing a dynamic non-linear characteristic parameter of said preselected input signal, said x(i)(n) represents the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to said preselected input signal;
a fifth determining module, configured to determine an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, where the nonlinear adjustment factor formula is:
Figure PCTCN2015075606-APPB-000050
wherein, theA parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
With reference to the fifth implementable manner, in a sixth implementable manner,
the first determination submodule is specifically configured to: determining the adjustment factor of the dynamic linear model of the preset input signal set by adopting a first interpolation formula according to the adjustment factor of the dynamic linear model of the preselected input signal set
Figure PCTCN2015075606-APPB-000052
The first interpolation formula is:
Figure PCTCN2015075606-APPB-000053
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal, and the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal
Figure PCTCN2015075606-APPB-000054
An adjustment factor representing a dynamic linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000055
An adjustment factor representing a dynamic linear model of the second input signal, w(r)Representing a weight factor w(r)The weight formula is determined according to the weight formula, wherein the weight formula is as follows:
Figure PCTCN2015075606-APPB-000056
wherein, the PrRepresenting the power level of an input signal of power level r, PMRepresenting a power value of said first input signal having a power magnitude M;
the second determining submodule is specifically configured to: determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by adopting a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000057
The second interpolation formula is:
wherein, the
Figure PCTCN2015075606-APPB-000059
An adjustment factor representing a dynamic non-linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000060
An adjustment factor representing a dynamic non-linear model of the second input signal, w(r)Representing a weighting factor.
With reference to any one of the second aspect to the sixth implementable manner, in a seventh implementable manner, the digital predistortion correction device further includes:
and the updating unit is used for updating the amplifier model of the current input signal to obtain an updated amplifier model when the state of the power amplifier changes.
With reference to the seventh implementable manner, in an eighth implementable manner,
the state change of the power amplifier is device aging, temperature fluctuation or bias voltage change.
With reference to the seventh or eighth implementable manner, in a ninth implementable manner, the updating unit includes:
a first obtaining module, configured to obtain, according to the amplifier model of the current input signal, a model coefficient of a dynamic model of the updated amplifier model;
a second obtaining module, configured to obtain, according to the amplifier model of the current input signal, a model coefficient of a static model of the updated amplifier model;
and the second substituting module is used for substituting the model coefficient of the updated dynamic model of the amplifier model and the model coefficient of the updated static model of the amplifier model into the amplifier model to obtain the updated amplifier model.
With reference to the ninth implementable manner, in a tenth implementable manner, the first obtaining module includes:
a first difference submodule configured to use a difference between a model coefficient of a dynamic model of the input signal after the state of the power amplifier is changed and a model coefficient of a dynamic model of the input signal before the state is changed as a first difference;
and the second processing submodule is used for taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference as the model coefficient of the dynamic model of the updated amplifier model.
With reference to the ninth implementable manner, in an eleventh implementable manner, the second obtaining module includes:
a second difference submodule, configured to use a difference between a model coefficient of a static model of the input signal after the state of the power amplifier is changed and a model coefficient of a static model of the input signal before the state is changed as a second difference;
and the third processing submodule is used for taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the updated static model of the amplifier model.
In a third aspect, a digital predistortion correction apparatus is provided, the digital predistortion correction apparatus comprising:
a processor for determining an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, the amplifier model being used for indicating a relation of an output signal to a static model of the input signal and a dynamic model of the input signal, the dynamic model comprising a dynamic linear model and a dynamic nonlinear model, wherein the dynamic linear model is used for indicating a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used for indicating a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values;
the processor is further configured to determine an adjustment factor for a dynamic nonlinear model of the preselected input signal in the amplifier model from the preselected input signal;
the processor is further used for establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal;
the processor is further configured to obtain a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal;
the processor is further configured to perform digital predistortion correction on the current input signal according to the DPD model of the current input signal.
With reference to the third aspect, in a first implementable manner, the processor is specifically configured to:
determining model coefficients of a static model of the current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of the preselected input signal and adjustment factors of a dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000061
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000062
The amplifier model formula is as follows:
wherein N represents the number of sampling points of each input signal in the preset input signal set, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal set, r is an integer greater than or equal to 1, and
Figure PCTCN2015075606-APPB-000064
a set of output signals representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000065
A static model representing said set of preset input signals, saidA dynamic model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000067
A dynamic linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000068
A dynamic non-linear model representing said set of preset input signals, said
Figure PCTCN2015075606-APPB-000069
An adjustment factor representing a dynamic linear model of the set of preset input signals, theAn adjustment factor representing a dynamic non-linear model of the set of preset input signals;
Figure PCTCN2015075606-APPB-000066
model coefficients of a static model of the current input signalAnd model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000072
And substituting the current input signal into the amplifier model formula to obtain an amplifier model corresponding to the current input signal.
In combination with the first implementable manner, in a second implementable manner,
the processor is specifically configured to:
determining an adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal;
determining an adjustment factor of a dynamic nonlinear model of the preset input signal set according to an adjustment factor of a dynamic nonlinear model of the preselected input signal;
substituting the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group into the amplifier model formula to obtain model coefficients of the static model of the preset input signal group and model coefficients of the dynamic model of the preset input signal group;
taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signal
Figure PCTCN2015075606-APPB-000073
Taking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000074
With reference to the second implementable manner, in a third implementable manner, the preselected input signal is a first input signal with a highest power value and a second input signal with a lowest power value in the preset input signal set, and the processor is specifically configured to:
determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula;
determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula;
the linear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000075
wherein, the thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1Parameter value representing a dynamic linear characteristic parameter of the first input signal, saidAn adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
With reference to the third implementable manner, in a fourth implementable manner,
the dynamic linear characteristic parameter is the average power of the output signals corresponding to the preset input signal group in the power amplifier or the gain of the output signals corresponding to the preset input signal group in the power amplifier.
With reference to the third implementable manner, in a fifth implementable manner,
the processor is specifically configured to:
determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula is as follows:
Figure PCTCN2015075606-APPB-000077
wherein, theA dynamic non-linear characteristic parameter representing said preselected input signalOf the parameter value of (a), said x(i)(n) represents the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to said preselected input signal;
determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000079
wherein, the
Figure PCTCN2015075606-APPB-000080
A parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
With reference to the fifth implementable manner, in a sixth implementable manner,
the processor is specifically configured to:
determining the adjustment factor of the dynamic linear model of the preset input signal set by adopting a first interpolation formula according to the adjustment factor of the dynamic linear model of the preselected input signal set
Figure PCTCN2015075606-APPB-000081
The first interpolation formula is:
Figure PCTCN2015075606-APPB-000082
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal, and the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal
Figure PCTCN2015075606-APPB-000083
An adjustment factor representing a dynamic linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000084
An adjustment factor representing a dynamic linear model of the second input signal, w(r)Representing a weight factor w(r)The weight formula is determined according to the weight formula, wherein the weight formula is as follows:
Figure PCTCN2015075606-APPB-000085
wherein, the PrRepresenting the power level of an input signal of power level r, PMRepresenting a power value of said first input signal having a power magnitude M;
the processor is further specifically configured to determine the adjustment factor of the dynamic nonlinear model of the set of predetermined input signals using a second interpolation formula based on the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000086
The second interpolation formula is:
Figure PCTCN2015075606-APPB-000087
wherein, the
Figure PCTCN2015075606-APPB-000088
An adjustment factor representing a dynamic non-linear model of the first input signal, the
Figure PCTCN2015075606-APPB-000089
An adjustment factor representing a dynamic non-linear model of the second input signal, w(r)Representing a weighting factor.
With reference to any one of the third aspect to the sixth implementable manner, in a seventh implementable manner, the processor is further configured to:
and when the state of the power amplifier changes, updating the amplifier model of the current input signal to obtain an updated amplifier model.
With reference to the seventh implementable manner, in an eighth implementable manner,
the state change of the power amplifier is device aging, temperature fluctuation or bias voltage change.
With reference to the seventh or eighth implementable manner, in a ninth implementable manner, the processor is specifically configured to:
obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal;
obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal;
and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
With reference to the ninth implementable manner, in a tenth implementable manner,
the processor is further specifically configured to:
taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value;
and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
With reference to the ninth implementable manner, in an eleventh implementable manner,
the processor is further specifically configured to:
taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value;
and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the static model of the updated amplifier model.
The technical scheme provided by the invention has the beneficial effects that:
the invention provides a digital predistortion correction method and a device, because the adjustment factor of a dynamic linear model and the adjustment factor of a dynamic nonlinear model of a preselected input signal in an amplifier model can be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then a DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is carried out on the current input signal according to the DPD model, compared with a lookup table model, model parameters of the amplifier model covering enough power range do not need to be calculated and stored, thus the model parameters of the DPD model covering enough power range do not need to be calculated and stored to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a basic operation schematic diagram of a conventional DPD technique according to an embodiment of the present invention;
fig. 2 is a flowchart of a digital predistortion correction method according to an embodiment of the present invention;
fig. 3 is a flow chart of another digital predistortion correction method provided by an embodiment of the invention;
FIG. 4 is a schematic diagram of an amplifier model provided by an embodiment of the invention;
FIG. 5 is a flow chart of a method for determining an adjustment factor for a dynamic linear model of a preselected input signal in an amplifier model based on the preselected input signal according to an embodiment of the present invention;
FIG. 6 is a flow chart of a method for determining an adjustment factor for a dynamic nonlinear model of a preselected input signal in an amplifier model based on the preselected input signal according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of determining model coefficients of a static model and model coefficients of a dynamic model corresponding to a preselected input signal according to an embodiment of the present invention;
FIG. 8 is a flow chart of a method for modeling an amplifier for a current input signal based on adjustment factors for a dynamic linear model of a preselected input signal and adjustment factors for a dynamic nonlinear model of a preselected input signal according to embodiments of the present invention;
FIG. 9 is a flow chart of a method for determining model coefficients of a static model and model coefficients of a dynamic model of a current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of a preselected input signal and adjustment factors of a dynamic nonlinear model of a preselected input signal according to an embodiment of the present invention;
fig. 10 is a schematic diagram illustrating determining an adjustment factor of a dynamic linear model and an adjustment factor of a dynamic nonlinear model corresponding to any untrained input signal in a preset input signal set according to an embodiment of the present invention;
FIG. 11 is a flow chart of a method for updating an amplifier model of a current input signal to obtain an updated amplifier model according to an embodiment of the present invention;
FIG. 12 is a flow chart of a method for obtaining model coefficients for a dynamic model of an updated amplifier model according to an embodiment of the present invention;
FIG. 13 is a flow chart of a method for obtaining model coefficients for a static model of an updated amplifier model according to an embodiment of the present invention;
FIG. 14 is a schematic diagram of model coefficient updating for an amplifier model according to an embodiment of the present invention;
fig. 15 is a schematic structural diagram of a digital predistortion correction apparatus according to an embodiment of the present invention;
fig. 16 is a schematic structural diagram of another digital predistortion correction apparatus provided in the embodiment of the present invention;
fig. 17 is a schematic structural diagram of a building unit of a digital predistortion correction apparatus according to an embodiment of the present invention;
fig. 18 is a schematic structural diagram of a first determining module of a digital predistortion correction apparatus according to an embodiment of the present invention;
fig. 19 is a schematic structural diagram of a first determining unit of a digital predistortion correction device according to an embodiment of the present invention;
fig. 20 is a schematic structural diagram of a second determining unit of the digital predistortion correction device according to the embodiment of the present invention;
fig. 21 is a schematic structural diagram of an updating unit of a digital predistortion correction apparatus according to an embodiment of the present invention;
fig. 22 is a schematic structural diagram of a first obtaining module of the digital predistortion correction apparatus according to the embodiment of the present invention;
fig. 23 is a schematic structural diagram of a second obtaining module of the digital predistortion correction apparatus according to the embodiment of the present invention;
fig. 24 is a schematic structural diagram of another digital predistortion correction apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
The DPD technique is a key technique for compensating the nonlinearity of the power amplifier in the digital domain, so that the power amplifier can be operated in a high-efficiency saturation state without losing the linearity.
As shown in fig. 1, the basic working principle of DPD technique is: a DPD module 01 is established in a digital baseband, predistortion is carried out on an input signal before the input signal enters a Power Amplifier (PA) 02, the model of the DPD module 01 is a DPD model, the model of the PA02 is an Amplifier model, and if the DPD model is an inverse function of the Amplifier model, the input signal is linearly amplified after passing through a DPD module 01 and a PA02 which are cascaded, so that distortion of an output signal of the input signal after passing through the PA02 is avoided. In fig. 1, the abscissa X represents the input power of the input signal, the ordinate Y represents the output power of the input signal, the first power curve from the left represents the power curve of the input signal, the second power curve represents the power curve of the predistortion signal generated by the DPD module 01, and the third power curve represents the power curve of the output signal output from the PA02 after the input signal has been subjected to predistortion correction. It can be seen that the key problem of DPD technique is to create an accurate but simple amplifier model: first, the amplifier model should be accurate because predistortion correction of the input signal can only be performed if the amplifier model is accurately established based on the characteristics of the power amplifier; secondly, the amplifier model should be simple enough, because a complex amplifier model would increase the cost and system complexity of the actual hardware implementation, and cannot be widely applied in practice.
An embodiment of the present invention provides a digital predistortion correction method, as shown in fig. 2, the method includes:
step 101, determining an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, wherein the amplifier model is used for indicating a relation between an output signal and a static model of the input signal and a dynamic model of the input signal, and the dynamic model comprises a dynamic linear model and a dynamic nonlinear model, wherein the dynamic linear model is used for indicating a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used for indicating a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values.
Step 102, determining an adjustment factor of a dynamic nonlinear model of a preselected input signal in an amplifier model according to the preselected input signal.
And 103, establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal.
And step 104, obtaining a DPD model of the current input signal according to the amplifier model of the current input signal.
And 105, performing digital predistortion correction on the current input signal according to the DPD model of the current input signal.
To sum up, in the digital predistortion correction method provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
Further, step 103 specifically includes:
determining model coefficients of a static model of a current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of a preselected input signal and adjustment factors of a dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000090
And model coefficients of the dynamic modelThe amplifier model formula is:
Figure PCTCN2015075606-APPB-000092
wherein N represents a preset input signal groupL1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power level of the input signals in the preset set of input signals, r is an integer greater than or equal to 1,
Figure PCTCN2015075606-APPB-000093
a set of output signals representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000094
is a matrix of N x 1, and the matrix is,
Figure PCTCN2015075606-APPB-000095
a static model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000096
is a matrix of N x L1,a dynamic model representing a set of preset input signals,is a matrix of N x L2,
Figure PCTCN2015075606-APPB-000099
a dynamic linear model representing a set of preset input signals,a dynamic non-linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000101
an adjustment factor representing a dynamic linear model of the set of preset input signals,
Figure PCTCN2015075606-APPB-000102
dynamic nonlinear representing a predetermined set of input signalsThe adjustment factor of the sexual model is,
Figure PCTCN2015075606-APPB-000103
is a matrix of L1 x 1,
Figure PCTCN2015075606-APPB-000104
a matrix of L2 × 1; model coefficients of a static model of a current input signal
Figure PCTCN2015075606-APPB-000105
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000106
Substituting the input signal into an amplifier model formula to obtain an amplifier model corresponding to the current input signal.
Figure PCTCN2015075606-APPB-000097
Figure PCTCN2015075606-APPB-000098
Determining model coefficients of a static model of a current input signal by using an amplifier model formula according to an adjustment factor of a dynamic linear model of a preselected input signal and an adjustment factor of a dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000107
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000108
The method comprises the following steps:
determining an adjustment factor of a dynamic linear model of a preset input signal set according to an adjustment factor of a dynamic linear model of a preselected input signal; according to preselected input informationDetermining the adjustment factor of the dynamic nonlinear model of the preset input signal group by the adjustment factor of the dynamic nonlinear model of the signal; substituting the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group into an amplifier model formula to obtain a model coefficient of the static model of the preset input signal group and a model coefficient of the dynamic model of the preset input signal group; taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signalTaking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000110
It should be noted that the preselected input signal is at least two signals in the preset input signal group. Taking the first input signal with the highest power value and the second input signal with the lowest power value in the preset input signal group as examples, determining the adjustment factor of the dynamic linear model of the preselected input signal in the amplifier model according to the preselected input signal includes:
determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula; determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula, wherein the linear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000111
wherein, thetaiParameter value representing a parameter of a dynamic linearity characteristic of a first input signal or dynamic linearity of a second input signalA parameter value of the characteristic parameter, i representing the power level of the first input signal or the power level of the second input signal, θ1A parameter value representing a dynamic linear characteristic parameter of the first input signal,
Figure PCTCN2015075606-APPB-000112
an adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
It should be noted that the dynamic linear characteristic parameter may be an average power of output signals corresponding to a preset input signal group in the power amplifier or a gain of output signals corresponding to a preset input signal group in the power amplifier.
Accordingly, determining an adjustment factor for a dynamic nonlinear model of a preselected input signal in an amplifier model based on the preselected input signal comprises:
determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula can be as follows:
Figure PCTCN2015075606-APPB-000113
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000114
parameter value, x, representing a dynamic non-linear characteristic parameter of a preselected input signal(i)(n) denotes the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to the preselected input signal, [ theta ]iA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal.
Determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000115
wherein the content of the first and second substances,a parameter value representing a dynamic non-linear characteristic parameter of the first input signal,a parameter value representing a dynamic non-linear characteristic parameter of the preselected input signal,
Figure PCTCN2015075606-APPB-000118
an adjustment factor representing a dynamic non-linear model of the first input signal or an adjustment factor representing a dynamic non-linear model of the second input signal.
Further, determining an adjustment factor of the dynamic linear model of the set of preset input signals according to the adjustment factor of the dynamic linear model of the preselected input signals includes:
determining the adjustment factor of the dynamic linear model of the set of pre-selected input signals using a first interpolation formula based on the adjustment factor of the dynamic linear model of the pre-selected input signals
Figure PCTCN2015075606-APPB-000119
The first interpolation formula may be:
Figure PCTCN2015075606-APPB-000120
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal,
Figure PCTCN2015075606-APPB-000121
an adjustment factor representing a dynamic linear model of the first input signal,
Figure PCTCN2015075606-APPB-000122
adjustment factor, w, of a dynamic linear model representing the second input signal(r)Representing a weight factor, weight factor w(r)The weight is determined according to a weight formula, and the weight formula can be:
Figure PCTCN2015075606-APPB-000123
wherein, PrRepresenting the power level, P, of an input signal of power level rMRepresenting the power level of the first input signal at power level M.
Determining an adjustment factor for the dynamic nonlinear model of the set of preset input signals based on the adjustment factor for the dynamic nonlinear model of the preselected input signals, comprising:
determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by using a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000124
The second interpolation formula may be:
wherein the content of the first and second substances,modulation of a dynamic non-linear model representing a first input signalThe integral factor is obtained by the following steps of,
Figure PCTCN2015075606-APPB-000127
adjustment factor, w, of a dynamic non-linear model representing the second input signal(r)Representing a weighting factor.
After step 105, the method may further comprise: and when the state of the power amplifier changes, updating the amplifier model of the current input signal to obtain an updated amplifier model. The state change of the power amplifier is device aging, temperature fluctuation, or bias voltage change.
Specifically, updating the amplifier model of the current input signal to obtain an updated amplifier model includes:
obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal; obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal; and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
Wherein, according to the amplifier model of the current input signal, obtaining the model coefficient of the dynamic model of the updated amplifier model, includes:
taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value; and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
Obtaining model coefficients of a static model of an updated amplifier model according to an amplifier model of a current input signal, comprising:
taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value; and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the updated static model of the amplifier model.
To sum up, in the digital predistortion correction method provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
An embodiment of the present invention provides another digital predistortion correction method, as shown in fig. 3, where the method includes:
step 201, an amplifier model is established.
The amplifier model formula is:
Figure PCTCN2015075606-APPB-000128
wherein N represents the number of sampling points of each input signal in the preset input signal group, the preset input signal group comprises a plurality of input signals with different power values, L1 represents the number of model coefficients of a static model, L2 represents the number of model coefficients of a dynamic model, r represents the power magnitude of the input signals in the preset input signal group, r is an integer greater than or equal to 1,a set of output signals representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000130
is a matrix of N x 1, and the matrix is,
Figure PCTCN2015075606-APPB-000131
a static model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000132
is a matrix of N x L1,a dynamic model representing a set of preset input signals,is a matrix of N x L2,a dynamic linear model representing a set of preset input signals,a dynamic non-linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000137
an adjustment factor representing a dynamic linear model of the set of preset input signals,
Figure PCTCN2015075606-APPB-000138
an adjustment factor representing a dynamic non-linear model of a set of preset input signals,
Figure PCTCN2015075606-APPB-000139
the model coefficients representing the static model are then,
Figure PCTCN2015075606-APPB-000140
is a matrix of L1 x 1,
Figure PCTCN2015075606-APPB-000141
the model coefficients representing the dynamic model are then,
Figure PCTCN2015075606-APPB-000142
is a matrix of L2 × 1.
Figure PCTCN2015075606-APPB-000133
Figure PCTCN2015075606-APPB-000134
For example, the input signals in the preset input signal group are arranged in the order of power values from large to small, and the sequence is as follows: s1, S2, S3, S4, S5, S6, S7, S8, S9 and S10, then S1, S2, S3, S4, S5, S6, S7, S8, S9 and S10 correspond to power levels r of 1, 2, 3, 4, 5, 6, 7, 8, 9 and 10, respectively.
As shown in FIG. 4, the amplifier model includes three parts, respectively, a static model X of a predetermined set of input signals(r)Dynamic linear model
Figure PCTCN2015075606-APPB-000143
And dynamic nonlinear model
Figure PCTCN2015075606-APPB-000144
It should be noted that the adjustment factor of the dynamic linear model in the amplifier model formula
Figure PCTCN2015075606-APPB-000145
Adjustment factor for dynamic nonlinear model
Figure PCTCN2015075606-APPB-000146
Model coefficients of a static model
Figure PCTCN2015075606-APPB-000147
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000148
Is unknown.
An adjustment factor for a dynamic linear model of a preselected input signal in an amplifier model is determined from the preselected input signal, step 202.
The amplifier model is used for indicating the relation between an output signal and a static model and a dynamic model of an input signal, the dynamic model comprises a dynamic linear model and a dynamic nonlinear model, the dynamic linear model is used for indicating the linear characteristic in the variable of the input signal, the dynamic nonlinear model is used for indicating the nonlinear characteristic in the variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values.
It should be noted that, in order to enable the preselected input signals to cover the power range of the whole preset input signal group, the preselected input signals may be the input signals with the highest power value and the input signals with the lowest power value in the preset input signal group, or may be the input signals with the highest power value, the input signals with the lowest power value and the input signals corresponding to other power values in the preset input signal group. For example, the input signals in the preset input signal group are arranged in the order of power values from large to small, and the sequence is as follows: s1, S2, S3, S4, S5, S6, S7, S8, S9 and S10, the preselected input signals may be S1 and S10, or S1, S4, S7 and S10. The invention does not limit the method for selecting the preselected input signals and the number of the selected preselected input signals, for example, the selecting method can carry out average division according to the power values corresponding to the input signals in the preset input signal group to determine the preselected input signals; the number of the preselected input signals may be two or more.
The preselected input signal is assumed to be the first input signal with the highest power value and the second input signal with the lowest power value in the preset input signal group. Step 202, as shown in fig. 5, may include:
step 2021, determining an adjustment factor of the dynamic linear model of the first input signal according to the dynamic linear characteristic parameter of the first input signal and the linear adjustment factor formula.
The linear adjustment factor is formulated as:
Figure PCTCN2015075606-APPB-000149
wherein, thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1A parameter value representing a dynamic linear characteristic parameter of the first input signal,
Figure PCTCN2015075606-APPB-000150
an adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal. It should be noted that i indicates the power level of the preselected input signal, and the preselected input signal may be a first input signal with the highest power value and a second input signal with the lowest power value in the preset input signal group, or may be an input signal with the highest power value, an input signal with the lowest power value, and an input signal corresponding to another power value in the preset input signal group.
Further, the parameter capable of representing the dynamic linear characteristic of the input signal is a dynamic linear characteristic parameter, for example, the dynamic linear characteristic parameter may be an average power of output signals corresponding to a preset input signal group in the power amplifier or a gain of the output signals corresponding to the preset input signal group in the power amplifier.
Step 2022, determining an adjustment factor of the dynamic linear model of the second input signal according to the parameter value of the dynamic linear characteristic parameter of the second input signal and the linear adjustment factor formula.
The specific process of determining the adjustment factor of the dynamic linear model of the second input signal may refer to the determination process in step 2021.
Step 203, determining an adjustment factor of a dynamic nonlinear model of the preselected input signal in the amplifier model based on the preselected input signal.
In order to quantify the change of the dynamic nonlinear characteristic of the power amplifier, the embodiment of the invention adopts a nonlinear measurement method, namely, a method for representing the residual dynamic nonlinear characteristic by calculating the difference between the dynamic nonlinear characteristic and the optimal dynamic linear characteristic approximation of the characteristic of the power amplifier.
If the preselected input signals in step 202 are the first input signals with the highest power value and the second input signals with the lowest power value in the preset input signal group, step 203 may include, as shown in fig. 6:
step 2031, determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and the nonlinear characteristic formula.
The nonlinear characteristic formula may be:
Figure PCTCN2015075606-APPB-000151
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000152
parameter value, x, representing a dynamic non-linear characteristic parameter of a preselected input signal(i)(n) denotes the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to the preselected input signal, [ theta ]iA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal.
Step 2032, determining the adjustment factor of the dynamic nonlinear model of the preselected input signal according to the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal and the nonlinear adjustment factor formula.
The nonlinear adjustment factor formula is as follows:
wherein the content of the first and second substances,a parameter value representing a dynamic non-linear characteristic parameter of the first input signal,
Figure PCTCN2015075606-APPB-000155
a parameter value representing a dynamic non-linear characteristic parameter of the preselected input signal,
Figure PCTCN2015075606-APPB-000156
an adjustment factor representing a dynamic non-linear model of the first input signal or an adjustment factor representing a dynamic non-linear model of the second input signal.
As shown in steps 202 and 203, the adjustment factor of the dynamic linear model of the first input signal can be determined according to the parameter value of the dynamic linear characteristic parameter of the first input signal, and the adjustment factor of the dynamic linear model of the second input signal can be determined according to the parameter value of the dynamic linear characteristic parameter of the second input signal; the parameter value of the dynamic nonlinear characteristic parameter of the first input signal can be determined according to the parameter value of the dynamic linear characteristic parameter of the first input signal, so that the adjustment factor of the dynamic nonlinear model of the first input signal can be determined, and the parameter value of the dynamic nonlinear characteristic parameter of the second input signal can be determined according to the parameter value of the dynamic linear characteristic parameter of the second input signal, so that the adjustment factor of the dynamic nonlinear model of the second input signal can be determined.
And step 204, establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal.
According to the adjustment factor of the dynamic linear model of the first input signal, the adjustment factor of the dynamic nonlinear model of the first input signal, the adjustment factor of the dynamic linear model of the second input signal and the adjustment factor of the dynamic nonlinear model of the second input signal, the adjustment factor of the dynamic linear model of the preset input signal group and the adjustment factor of the dynamic nonlinear model can be determined, further, according to a least square method, the model coefficient of the static model of the preset input signal group and the model coefficient of the dynamic model of the preset input signal group are determined by adopting an amplifier model formula, and finally the model coefficient of the static model of the current input signal is determined
Figure PCTCN2015075606-APPB-000157
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000158
An amplifier model of the current input signal is established. The amplifier model formula in step 201 can be referred to as an amplifier model formula.
For example, fig. 7 is a solving process for determining model coefficients of a static model and model coefficients of a dynamic model corresponding to preselected input signals according to an adjustment factor of a dynamic linear model and an adjustment factor of a dynamic nonlinear model of the preselected input signals, and as shown in fig. 7, a group of preselected input signals in a preset input signal group is selected, where the preselected input signals may be an input signal with the highest power value and an input signal with the lowest power value in the preset input signal group, or an input signal with the highest power value, an input signal with the lowest power value and an input signal corresponding to other power values in the preset input signal group. And calculating the adjustment factor of the corresponding dynamic linear model and the adjustment factor of the dynamic nonlinear model according to the collected preselected input signals, and then determining the model coefficient of the static model and the model coefficient of the dynamic model corresponding to the preselected input signals by adopting an amplifier model formula according to a least square method. x is the number of(1)(n) to x(R)(n) in the preset set of input signalsInput signal, y(1)(n) to y(R)(n) represents an output signal corresponding to the preset input signal group,
Figure PCTCN2015075606-APPB-000159
toAn adjustment factor representing a dynamic linear model corresponding to an input signal in the set of predetermined input signals,
Figure PCTCN2015075606-APPB-000161
to
Figure PCTCN2015075606-APPB-000162
An adjustment factor representing a dynamic non-linear model corresponding to an input signal in the set of predetermined input signals,
Figure PCTCN2015075606-APPB-000163
model coefficients representing a static model of a set of preset input signals,
Figure PCTCN2015075606-APPB-000164
model coefficients representing a dynamic model of a set of preset input signals.
As shown in fig. 8, step 204 may specifically include:
2041, determining model coefficients of the static model of the current input signal by using an amplifier model formula according to the adjustment factors of the dynamic linear model of the preselected input signal and the adjustment factors of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000165
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000166
As shown in fig. 9, step 2041 may specifically include:
step 2041a, determining the adjustment factor of the dynamic linear model of the preset input signal group according to the adjustment factor of the dynamic linear model of the preselected input signal group.
Specifically, step 2041a may include:
determining the adjustment factor of the dynamic linear model of the set of pre-selected input signals using a first interpolation formula based on the adjustment factor of the dynamic linear model of the pre-selected input signals
Figure PCTCN2015075606-APPB-000167
The first interpolation formula may be:
Figure PCTCN2015075606-APPB-000168
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal (M is 1) and larger than the power level M of the second input signal,
Figure PCTCN2015075606-APPB-000169
an adjustment factor representing a dynamic linear model of the first input signal,
Figure PCTCN2015075606-APPB-000170
adjustment factor, w, of a dynamic linear model representing the second input signal(r)Representing a weight factor, weight factor w(r)The weight is determined according to a weight formula, and the weight formula can be:
wherein, PrRepresenting the power level, P, of an input signal of power level rMRepresents the power value of the first input signal with a power level M (M ═ 1).
When the power value of the input signal in the preset input signal group is smaller than the power value of the first input signal and larger than the power value of the second input signal, the power level of the input signal is considered to be smaller than the power level M of the first input signal (M is 1) and larger than the power level M of the second input signal.
And 2041b, determining an adjustment factor of the dynamic nonlinear model of the preset input signal group according to the adjustment factor of the dynamic nonlinear model of the preselected input signal.
Specifically, step 2041b may include:
determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by using a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000172
The second interpolation formula may be:
Figure PCTCN2015075606-APPB-000173
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000174
an adjustment factor representing a dynamic non-linear model of the first input signal,
Figure PCTCN2015075606-APPB-000175
adjustment factor, w, of a dynamic non-linear model representing the second input signal(r)Representing a weighting factor.
As can be seen from step 2041a and step 2041b, for any input signal in the untrained input signals in the preset input signal group, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model corresponding to the input signal can be obtained through the first interpolation formula and the second interpolation formula. Step 2041a and step 2041b may be executed simultaneously, and the order of the steps is not limited in the embodiment of the present invention.
For example, fig. 10 is a solving process for determining an adjustment factor of a dynamic linear model and an adjustment factor of a dynamic nonlinear model corresponding to any untrained input signal in a preset input signal group through a first interpolation formula and a second interpolation formula, and specific description may refer to step 2041a and step 2041 b. M denotes the power level of the first input signal, M denotes the power level of the second input signal, x(M)(n) denotes a first input signal, (C)M) Model coefficients, y, representing the first input signal(M)(n) represents an output signal corresponding to the first input signal, x(r)(n) denotes an untrained input signal having a power value less than the power level M of the first input signal and greater than the power level M of the second input signal, (C)r) Model coefficients, y, representing the input signal(r)(n) represents an output signal corresponding to the input signal, x(m)(n) represents a second input signal, (C)m) Model coefficients, y, representing the second input signal(m)(n) represents an output signal corresponding to the second input signal, w(r)Representing a weighting factor.
For any input signal which is not trained in a preset input signal set, firstly, the power value of the input signal is judged to be between the power values of two trained input signals, and then the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model corresponding to the input signal are determined through a first interpolation formula and a second interpolation formula. Assuming that the input signals in the preset input signal group are arranged according to the power value from large to small, the sequence is as follows: s1, S2, S3, S4, S5, S6, S7, S8, S9 and S10, if the preselected input signals are S1 and S10, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model corresponding to any one of the input signals of S2, S3, S4, S5, S6, S7, S8 and S9 can be determined by the first interpolation formula and the second interpolation formula according to S1 and S10; if the preselected input signals are S1, S2, S6 and S10, since the power value of S3 is between the power values of S2 and S6, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model corresponding to S3 can be determined by the first interpolation formula and the second interpolation formula according to S2 and S6, and similarly, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model corresponding to any one of S4, S5, S7, S8 and S9 can be determined.
Step 2041c, substituting the adjustment factor of the dynamic linear model of the preset input signal group and the adjustment factor of the dynamic nonlinear model of the preset input signal group into an amplifier model formula to obtain a model coefficient of the static model of the preset input signal group and a model coefficient of the dynamic model of the preset input signal group.
After the adjustment factor of the dynamic linear model of the preset input signal group and the adjustment factor of the dynamic nonlinear model of the preset input signal group are obtained according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, the model coefficient of the static model of the preset input signal group and the model coefficient of the dynamic model of the preset input signal group can be determined by adopting an amplifier model formula according to the adjustment factor of the dynamic linear model of the preset input signal group and the adjustment factor of the dynamic nonlinear model of the preset input signal group and a least square method.
2041d, taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signal
Figure PCTCN2015075606-APPB-000176
Taking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
The model coefficients of the static model of the preset input signal group and the model coefficients of the dynamic model of the preset input signal group are the model coefficients of the static model of the current input signalAnd model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000179
Step 2042, model coefficients of the static model of the current input signal
Figure PCTCN2015075606-APPB-000180
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000181
Substituting the input signal into an amplifier model formula to obtain an amplifier model corresponding to the current input signal.
Knowing the model coefficients of a static model of the current input signal
Figure PCTCN2015075606-APPB-000182
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000183
An amplifier model corresponding to the current input signal can be established.
Therefore, the method for obtaining the model coefficient in the digital predistortion correction method provided by the embodiment of the invention can reduce the number of power values corresponding to different input signals needing to participate in calculation on one hand, thereby reducing the complexity of establishing an amplifier model; on the other hand, the power values corresponding to the rest power values are obtained by means of linear interpolationThe model coefficient mode can be combined with the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model in the amplifier model formula, thereby simply and quickly determining the model coefficient of the static model of the current input signal
Figure PCTCN2015075606-APPB-000184
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000185
Step 205, obtaining a DPD model of the current input signal according to the amplifier model of the current input signal.
Specifically, an inverse function of the amplifier model of the current input signal may be used as the DPD model of the current input signal. As shown in fig. 1, when the DPD model is an inverse function of the amplifier model, the current input signal is linearly amplified after passing through the cascade of DPD module 01 and PA02, so that distortion of the output signal of the current input signal after passing through PA02 is avoided.
And step 206, performing digital predistortion correction on the current input signal according to the DPD model of the current input signal.
And superposing a predistortion signal generated correspondingly by the inverse function of the DPD model of the current input signal on the current input signal, so that the superposed signal passes through the power amplifier module to achieve the aim of carrying out predistortion correction on the current input signal.
And step 207, updating the amplifier model of the current input signal to obtain an updated amplifier model when the state of the power amplifier changes.
Although the steps 201 to 206 may well fit the characteristics of the power amplifier when the output power of the power amplifier changes, since the operating state of the power amplifier may change with the aging of the device, the temperature fluctuation, or the change of the bias voltage, the amplifier model of the current input signal needs to be updated to obtain an updated amplifier model when the state of the power amplifier changes, so as to adapt to the changes. For example, the change in state of the power amplifier may be device aging, temperature fluctuation, or bias voltage change. It should be noted that there may be various ways to detect whether the state of the power amplifier changes, which may specifically refer to the prior art, and the embodiments of the present invention are not described herein again. When the state of the power amplifier changes, the amplifier model of the current input signal is updated according to the specific updating method in step 207 to obtain the updated amplifier model.
As shown in fig. 11, step 207 may specifically include:
step 2071, obtaining a model coefficient of the dynamic model of the updated amplifier model according to the amplifier model of the current input signal.
As shown in fig. 12, step 2071 may specifically include:
step 2071a is to set a difference between a model coefficient of a dynamic model of the input signal after the state of the power amplifier is changed and a model coefficient of a dynamic model of the input signal before the change as a first difference.
Step 2071b, the sum of the model coefficient of the dynamic model of the current input signal and the first difference is used as the model coefficient of the dynamic model of the updated amplifier model.
Step 2072, obtaining a model coefficient of the updated static model of the amplifier model according to the amplifier model of the current input signal.
As shown in fig. 13, step 2072 may specifically include:
step 2072a is to set a difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the change as a second difference value.
And 2072b, taking the sum of the model coefficient of the static model of the current input signal and the second difference as the model coefficient of the updated static model of the amplifier model.
Since the static model and the dynamic linear model in the amplifier model formula may be linearly related or may not be linearly related, updating the model coefficients of the dynamic model and the model coefficients of the static model of the amplifier model may include two aspects:
on the one hand, static model and dynamic line in the amplifier model formulaWhen the sexual model is not related, the model coefficient after the state change can be determined(model coefficients of a static model of the input signal after a change of state
Figure PCTCN2015075606-APPB-000187
Model coefficients with dynamic model
Figure PCTCN2015075606-APPB-000188
) To determine the model coefficients after the state change
Figure PCTCN2015075606-APPB-000189
With the model coefficient C before the state change(r′)Difference between (second difference)
Figure PCTCN2015075606-APPB-000190
And a first difference value
Figure PCTCN2015075606-APPB-000191
)：
Figure PCTCN2015075606-APPB-000192
Then, the model coefficient of the dynamic model of the current input signal is calculatedIs different from the first difference value
Figure PCTCN2015075606-APPB-000194
Sum as updated amplificationModel coefficients of a dynamic model of the machine model; model coefficients of a static model of a current input signalAnd the second difference
Figure PCTCN2015075606-APPB-000196
The sum is taken as the model coefficient of the static model of the updated amplifier model:
Figure PCTCN2015075606-APPB-000197
on the other hand, when the static model and the dynamic linear model in the amplifier model formula are linearly related, only a part of the effective model coefficients are obtained in the training process
Figure PCTCN2015075606-APPB-000198
Namely, the existence of:
Figure PCTCN2015075606-APPB-000199
wherein the content of the first and second substances,
then, the model coefficient of the dynamic model of the current input signal is calculated
Figure PCTCN2015075606-APPB-000201
Is different from the first difference value
Figure PCTCN2015075606-APPB-000202
The sum is used as a model coefficient of the dynamic model of the updated amplifier model; model coefficients of a static model of a current input signal
Figure PCTCN2015075606-APPB-000203
And the second difference
Figure PCTCN2015075606-APPB-000204
The sum is taken as the model coefficient of the static model of the updated amplifier model:
Figure PCTCN2015075606-APPB-000205
and 2073, substituting the updated model coefficients of the dynamic model of the amplifier model and the updated model coefficients of the static model of the amplifier model into the amplifier model to obtain an updated amplifier model.
For example, fig. 14 shows an updating process of model coefficients of an amplifier model, a portion above a dotted line indicates a process of obtaining a first difference between model coefficients of a dynamic model of an input signal after a state change of a power amplifier and model coefficients of a dynamic model of the input signal before the change, and a second difference between model coefficients of a static model of an input signal after the state change of the power amplifier and model coefficients of a static model of the input signal before the change, and specifically, with reference to step 2071a and step 2072a, a portion below a dotted line indicates a process of taking a sum of a model coefficient of a dynamic model of a current input signal and the first difference as a model coefficient of a dynamic model of an updated amplifier model, and a sum of a model coefficient of a static model of a current input signal and the second difference as a model coefficient of a static model of an updated amplifier model, reference may be made specifically to steps 2071b and 2072b, x in FIG. 14(1)(n) to x(R)(n) represents the current input signal.
And step 208, taking the inverse function of the updated amplifier model as the DPD model of the current input signal.
When the state of the power amplifier changes, the amplifier model of the current input signal is updated to obtain an updated amplifier model, and as shown in step 205, the inverse function of the updated amplifier model is used as the DPD model of the current input signal, so as to avoid distortion of the output signal of the current input signal after passing through the PA 02.
And step 209, performing digital predistortion correction on the current input signal according to the DPD model corresponding to the updated inverse function of the amplifier model.
Step 209 may refer to step 206 specifically, and is not described herein again.
It should be noted that, when the amplifier model of the current input signal needs to be updated, an input signal with a higher power value in the preset input signal set may be selected as the input signal of the amplifier module in fig. 1, and then the model coefficient after the state change, the model coefficient before the state change, and the model coefficient of the updated amplifier model are calculated according to the solved model coefficients, and then applied to other power values to obtain a new amplifier model coefficient after the state change of the power amplifier. Therefore, the amplifier model can be updated by occasional one-time and two-time coefficients, quickly adapt to the change of the state of the power amplifier, and timely adjust the model coefficients in the whole power dynamic range to adapt to the change of the power amplifier, so that the amplifier model can better adapt to the dynamic change of the power amplifier in the modern wireless communication system.
Therefore, according to the process of establishing the amplifier model in the digital predistortion correction method provided by the embodiment of the invention, the amplifier model established according to the embodiment of the invention is an accurate and simple amplifier model, and meets the requirement of solving the key problem of the DPD technology in the scene of dynamic change of the power of the output signal of the power amplifier.
It should be noted that, in various embodiments of the present invention, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.
To sum up, in the digital predistortion correction method provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
The embodiments of the present invention provide a digital predistortion correction apparatus 50, and the apparatuses provided in all embodiments of the present invention may be applied to a communication system, for example, the apparatus may be a radio frequency unit or a base station, may also be a part of the radio frequency unit or the base station, and may also be applied to other systems that need digital predistortion correction, such as a part of a radar system or a radar system. As shown in fig. 15, the digital predistortion correction apparatus 50 includes:
a first determination unit 501, a second determination unit 502, a creation unit 503, a processing unit 504 and a correction unit 505.
A first determining unit 501, configured to determine, according to a preselected input signal, an adjustment factor of a dynamic linear model of the preselected input signal in an amplifier model, where the amplifier model is used to indicate a relationship between an output signal and a static model of the input signal and a dynamic model of the input signal, and the dynamic model includes a dynamic linear model and a dynamic nonlinear model, where the dynamic linear model is used to indicate a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used to indicate a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group includes a plurality of input signals with different power values.
A second determining unit 502 for determining an adjustment factor of the dynamic non-linear model of the preselected input signal in the amplifier model from the preselected input signal.
The establishing unit 503 is configured to establish an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal.
And the processing unit 504 is configured to obtain a digital predistortion DPD model of the current input signal according to the amplifier model of the current input signal.
A correcting unit 505, configured to perform digital predistortion correction on the current input signal according to the DPD model of the current input signal.
To sum up, in the digital predistortion correction apparatus provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
An embodiment of the present invention provides another digital predistortion correction apparatus 50, as shown in fig. 16, where the digital predistortion correction apparatus 50 includes:
a first determination unit 501, a second determination unit 502, a creation unit 503, a processing unit 504, a correction unit 505, and an update unit 506.
A first determining unit 501, configured to determine, according to a preselected input signal, an adjustment factor of a dynamic linear model of the preselected input signal in an amplifier model, where the amplifier model is used to indicate a relationship between an output signal and a static model of the input signal and a dynamic model of the input signal, and the dynamic model includes a dynamic linear model and a dynamic nonlinear model, where the dynamic linear model is used to indicate a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used to indicate a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group includes a plurality of input signals with different power values.
A second determining unit 502 for determining an adjustment factor of the dynamic non-linear model of the preselected input signal in the amplifier model from the preselected input signal.
The establishing unit 503 is configured to establish an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal.
And the processing unit 504 is configured to obtain a digital predistortion DPD model of the current input signal according to the amplifier model of the current input signal.
A correcting unit 505, configured to perform digital predistortion correction on the current input signal according to the DPD model of the current input signal.
An updating unit 506, configured to update the amplifier model of the current input signal to obtain an updated amplifier model when the state of the power amplifier changes.
Further, as shown in fig. 17, the establishing unit 503 may include:
a first determination module 5031 and a first generation module 5032.
A first determining module 5031, configured to determine a model coefficient of a static model of a current input signal by using an amplifier model formula according to an adjustment factor of a dynamic linear model of a preselected input signal and an adjustment factor of a dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000206
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000207
The amplifier model formula is:
Figure PCTCN2015075606-APPB-000208
wherein N represents the number of sampling points of each input signal in the preset input signal group, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal group, r is an integer greater than or equal to 1,
Figure PCTCN2015075606-APPB-000209
a set of output signals representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000210
a static model representing a set of preset input signals,a dynamic model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000212
a dynamic linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000213
a dynamic non-linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000214
an adjustment factor representing a dynamic linear model of the set of preset input signals,
Figure PCTCN2015075606-APPB-000215
dynamic nonlinear representing a predetermined set of input signalsAdjustment factors for sexual models.
Figure PCTCN2015075606-APPB-000211
A first generation module 5032 for generating model coefficients of a static model of the current input signal
Figure PCTCN2015075606-APPB-000216
And model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000217
Substituting the input signal into an amplifier model formula to obtain an amplifier model corresponding to the current input signal.
As shown in fig. 18, the first determining module 5031 may include:
a first determination sub-module 50311, a second determination sub-module 50312, an substitution sub-module 50313 and a first processing sub-module 50314.
A first determining submodule 50311, configured to determine an adjustment factor of the dynamic linear model of the preset input signal group according to the adjustment factor of the dynamic linear model of the preselected input signal.
A second determining sub-module 50312 for determining the adjustment factor of the dynamic nonlinear model of the preset input signal group according to the adjustment factor of the dynamic nonlinear model of the preselected input signal.
The substituting sub-module 50313 is configured to substitute the adjustment factor of the dynamic linear model of the preset input signal group and the adjustment factor of the dynamic nonlinear model of the preset input signal group into the amplifier model formula to obtain a model coefficient of the static model of the preset input signal group and a model coefficient of the dynamic model of the preset input signal group.
A first processing submodule 50314 for using the model coefficients of the static model of the preset input signal set as the model coefficients of the static model of the current input signal
Figure PCTCN2015075606-APPB-000218
Dynamic modulus of a preset set of input signalsModel coefficients of the model as model coefficients of a dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000219
As shown in fig. 19, the first determination unit 501 may include:
a second determination module 5011 and a third determination module 5012.
The second determining module 5011 is configured to determine an adjustment factor of the dynamic linear model of the first input signal according to the dynamic linear characteristic parameter of the first input signal and the linear adjustment factor formula.
The third determining module 5012 is configured to determine an adjustment factor of the dynamic linear model of the second input signal according to the parameter value of the dynamic linear characteristic parameter of the second input signal and the linear adjustment factor formula.
The linear adjustment factor is formulated as:
wherein, thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1A parameter value representing a dynamic linear characteristic parameter of the first input signal,
Figure PCTCN2015075606-APPB-000221
an adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
It should be noted that the dynamic linear characteristic parameter is an average power of output signals corresponding to a preset input signal group in the power amplifier or a gain of output signals corresponding to a preset input signal group in the power amplifier.
As shown in fig. 20, the second determining unit 502 may include:
a fourth determination module 5021 and a fifth determination module 5022.
A fourth determining module 5021, configured to determine a parameter value of a dynamic nonlinear characteristic parameter of a preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, where the nonlinear characteristic formula is:
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000223
parameter value, x, representing a dynamic non-linear characteristic parameter of a preselected input signal(i)(n) denotes the signal value of the preselected input signal, y(i)And (n) represents an output signal corresponding to the preselected input signal.
A fifth determining module 5022, configured to determine an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, where the nonlinear adjustment factor formula is:
Figure PCTCN2015075606-APPB-000224
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000225
a parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
Further, the first determining submodule is specifically configured to: determining the adjustment factor of the dynamic linear model of the set of pre-selected input signals using a first interpolation formula based on the adjustment factor of the dynamic linear model of the pre-selected input signals
Figure PCTCN2015075606-APPB-000226
The first interpolation formula is:
Figure PCTCN2015075606-APPB-000227
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal,
Figure PCTCN2015075606-APPB-000228
an adjustment factor representing a dynamic linear model of the first input signal,
Figure PCTCN2015075606-APPB-000229
adjustment factor, w, of a dynamic linear model representing the second input signal(r)Representing a weight factor, weight factor w(r)The weight is determined according to a weight formula, and the weight formula is as follows:
Figure PCTCN2015075606-APPB-000230
wherein, PrRepresenting the power level, P, of an input signal of power level rMRepresenting the power level of the first input signal at power level M.
The second determination submodule is specifically configured to: determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by using a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
Figure PCTCN2015075606-APPB-000231
The second interpolation formula is:
Figure PCTCN2015075606-APPB-000232
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000233
an adjustment factor representing a dynamic non-linear model of the first input signal,
Figure PCTCN2015075606-APPB-000234
adjustment factor, w, of a dynamic non-linear model representing the second input signal(r)Representing a weighting factor.
It should be noted that the state change of the power amplifier may be device aging, temperature fluctuation, or bias voltage change.
As shown in fig. 21, the updating unit 506 may include:
a first acquisition module 5061, a second acquisition module 5062, and a second generation module 5063.
A first obtaining module 5061, configured to obtain a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal.
A second obtaining module 5062 is configured to obtain a model coefficient of the updated static model of the amplifier model according to the amplifier model of the current input signal.
A second generation module 5063, configured to substitute the model coefficients of the dynamic model of the updated amplifier model and the model coefficients of the static model of the updated amplifier model into the amplifier model to obtain an updated amplifier model.
As shown in fig. 22, the first obtaining module 5061 may include:
a first difference sub-module 50611 and a second processing sub-module 50612.
The first difference sub-module 50611 is configured to use a difference between a model coefficient of the dynamic model of the input signal after the state change of the power amplifier and a model coefficient of the dynamic model of the input signal before the change as a first difference.
And the second processing sub-module 50612 is configured to use a sum of the model coefficient of the dynamic model of the current input signal and the first difference as a model coefficient of the updated dynamic model of the amplifier model.
As shown in fig. 23, the second obtaining module 5062 may include:
a second difference sub-module 50621 and a third processing sub-module 50622.
The second difference sub-module 50621 is configured to use a difference between a model coefficient of the static model of the input signal after the state change of the power amplifier and a model coefficient of the static model of the input signal before the change as a second difference.
A third processing submodule 50622 for adding the model coefficient of the static model of the current input signal to the second difference as the model coefficient of the updated static model of the amplifier model.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
To sum up, in the digital predistortion correction apparatus provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
An embodiment of the present invention provides another digital predistortion correction apparatus, as shown in fig. 24, the digital predistortion correction apparatus includes: at least one processor 701, at least one Input-Output (IO) interface 702 or other communication interfaces, a memory 703, and at least one communication bus 704, which are used for implementing connection communication between these devices. The processor 701 is configured to execute a computer execution instruction 7031 in the memory 703, and control the IO interface 702 to perform transceiving. The Memory 703 may include a Random Access Memory (RAM) or a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The digital predistortion correction device is implemented by at least one IO interface 702 (which may be wired or wireless) to receive and transmit data, including a communication connection with at least one other network element. When the processor executes the computer execution instructions in the memory, the steps in the above method embodiments may be executed, which may specifically refer to the description in the above method embodiments and will not be described herein again.
An embodiment of the present invention further provides a digital predistortion correction apparatus, as shown in fig. 24, the digital predistortion correction apparatus includes:
a processor 701 configured to determine an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, the amplifier model being configured to indicate a relationship between an output signal and a static model of the input signal and a dynamic model of the input signal, the dynamic model including a dynamic linear model and a dynamic nonlinear model, wherein the dynamic linear model is configured to indicate a linear characteristic in a variable of the input signal, the dynamic nonlinear model is configured to indicate a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group includes a plurality of input signals with different power values.
The processor 701 is also configured to determine an adjustment factor for a dynamic non-linear model of a preselected input signal in the amplifier model based on the preselected input signal.
The processor 701 is further configured to establish an amplifier model of the current input signal based on the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal.
The processor 701 is further configured to obtain a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal. Alternatively, the inverse function of the amplifier model of the current input signal may be used as the digital predistortion DPD model of the current input signal.
The processor 701 is further configured to perform digital predistortion correction on the current input signal according to the DPD model of the current input signal.
It should be noted that, when the processor in the embodiment of the present invention executes the computer execution instruction in the memory, the steps in the above method embodiment may be executed, and specifically, reference may be made to the description in the above method embodiment.
To sum up, in the digital predistortion correction apparatus provided in the embodiment of the present invention, the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model may be determined according to the preselected input signal, then the amplifier model of the current input signal is established according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then the DPD model of the current input signal is obtained according to the amplifier model of the current input signal, and finally the digital predistortion correction is performed on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to meet the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
Further, the processor 701 is specifically configured to:
determining model coefficients of a static model of a current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of a preselected input signal and adjustment factors of a dynamic nonlinear model of the preselected input signalAnd model coefficients of the dynamic model
Figure PCTCN2015075606-APPB-000236
The amplifier model formula is:
Figure PCTCN2015075606-APPB-000237
wherein N represents the number of sampling points of each input signal in the preset input signal group, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal group, r is an integer greater than or equal to 1,
Figure PCTCN2015075606-APPB-000238
a set of output signals representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000239
a static model representing a set of preset input signals,a dynamic model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000241
a dynamic linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000242
a dynamic non-linear model representing a set of preset input signals,
Figure PCTCN2015075606-APPB-000243
an adjustment factor representing a dynamic linear model of the set of preset input signals,
Figure PCTCN2015075606-APPB-000244
an adjustment factor representing a dynamic nonlinear model of a set of preset input signals; modulo a static model of a current input signalForm factor
Figure PCTCN2015075606-APPB-000245
And model coefficients of the dynamic modelSubstituting the input signal into an amplifier model formula to obtain an amplifier model corresponding to the current input signal.
Figure PCTCN2015075606-APPB-000240
The processor 701 is further specifically configured to:
determining an adjustment factor of a dynamic linear model of a preset input signal set according to an adjustment factor of a dynamic linear model of a preselected input signal; determining an adjustment factor of a dynamic nonlinear model of a preset input signal group according to an adjustment factor of a dynamic nonlinear model of a preselected input signal; substituting the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group into an amplifier model formula to obtain model coefficients of the static model of the preset input signal group and model coefficients of the dynamic model of the preset input signal group; taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signalTaking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
Figure PCTCN2015075606-APPB-000248
It should be noted that the preselected input signals may be a first input signal with the highest power value and a second input signal with the lowest power value in the preset input signal group, and the processor 701 is specifically configured to:
determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula; determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula, wherein the linear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000249
wherein, thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1A parameter value representing a dynamic linear characteristic parameter of the first input signal,an adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
It should be noted that the dynamic linear characteristic parameter may be an average power of output signals corresponding to a preset input signal group in the power amplifier or a gain of output signals corresponding to a preset input signal group in the power amplifier.
The processor 701 is further specifically configured to:
determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula is as follows:
Figure PCTCN2015075606-APPB-000251
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000252
parameter value, x, representing a dynamic non-linear characteristic parameter of a preselected input signal(i)(n) denotes the signal value of the preselected input signal, y(i)And (n) represents an output signal corresponding to the preselected input signal.
Determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
Figure PCTCN2015075606-APPB-000253
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000254
a parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
The processor 701 is further specifically configured to:
determining the adjustment factor of the dynamic linear model of the set of pre-selected input signals using a first interpolation formula based on the adjustment factor of the dynamic linear model of the pre-selected input signals
Figure PCTCN2015075606-APPB-000255
The first interpolation formula is:
Figure PCTCN2015075606-APPB-000256
wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal,
Figure PCTCN2015075606-APPB-000257
adjustment factor for a dynamic linear model representing a first input signal，Adjustment factor, w, of a dynamic linear model representing the second input signal(r)Representing a weight factor, weight factor w(r)The weight is determined according to a weight formula, and the weight formula is as follows:
Figure PCTCN2015075606-APPB-000259
wherein, PrRepresenting the power level, P, of an input signal of power level rMRepresenting the power level of the first input signal at power level M.
The processor 701 is further specifically configured to determine the adjustment factor of the dynamic nonlinear model of the set of predetermined input signals using the second interpolation formula based on the adjustment factor of the dynamic nonlinear model of the preselected input signals
Figure PCTCN2015075606-APPB-000260
The second interpolation formula is:
Figure PCTCN2015075606-APPB-000261
wherein the content of the first and second substances,
Figure PCTCN2015075606-APPB-000262
an adjustment factor representing a dynamic non-linear model of the first input signal,
Figure PCTCN2015075606-APPB-000263
adjustment factor, w, of a dynamic non-linear model representing the second input signal(r)Representing a weighting factor.
It should be noted that the processor 701 is further configured to:
and when the state of the power amplifier changes, updating the amplifier model of the current input signal to obtain an updated amplifier model.
The change in state of the power amplifier may be device aging, temperature fluctuations, or bias voltage changes.
The processor 701 is further specifically configured to: obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal; obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal; and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
The processor 701 is further specifically configured to: taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value; and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
The processor 701 is further specifically configured to: taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value; and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the updated static model of the amplifier model.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
It should be understood that, in the embodiment of the present invention, the processor 701 may be a Central Processing Unit (CPU), and the processor may also be other general purpose processors, Digital Signal Processors (DSP), Application Specific Integrated Circuits (ASIC), Field-Programmable Gate arrays (FPGA) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor, which may also be any conventional processor or the like.
The memory 703 may include both read-only memory and random-access memory, and provides computer-executable instructions and data to the processor 701. The portion of memory may also include non-volatile random access memory. For example, the memory may also store device type information.
In implementation, the steps in the above method embodiments may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 701. The steps of a method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor. To avoid repetition, it is not described in detail here.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a Read-Only Memory (ROM), a RAM, a magnetic disk, or an optical disk.
To sum up, in the digital predistortion correction apparatus provided in the embodiment of the present invention, the processor may determine the adjustment factor of the dynamic linear model and the adjustment factor of the dynamic nonlinear model of the preselected input signal in the amplifier model according to the preselected input signal, then establish the amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal, then obtain the DPD model of the current input signal according to the amplifier model of the current input signal, and finally perform digital predistortion correction on the current input signal according to the DPD model, compared with the look-up table model, it is not necessary to calculate and store the model parameters of the amplifier model covering a sufficient power range, and thus it is not necessary to calculate and store the model parameters of the DPD model covering a sufficient power range to satisfy the correction requirements of different input signals, therefore, the acquisition process of the model parameters is simplified, and the correction efficiency is improved.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (24)

  1. A digital predistortion correction method, characterized in that the method comprises:
    determining an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, wherein the amplifier model is used for indicating the relation of an output signal and a static model of the input signal and a dynamic model of the input signal, the dynamic model comprises a dynamic linear model and a dynamic nonlinear model, the dynamic linear model is used for indicating the linear characteristic in a variable of the input signal, the dynamic nonlinear model is used for indicating the nonlinear characteristic in the variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values;
    determining an adjustment factor for a dynamic nonlinear model of the preselected input signal in the amplifier model from the preselected input signal;
    establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal;
    obtaining a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal;
    and carrying out digital predistortion correction on the current input signal according to the DPD model of the current input signal.
  2. The digital predistortion correction method of claim 1, wherein the establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal comprises:
    determining model coefficients of a static model of the current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of the preselected input signal and adjustment factors of a dynamic nonlinear model of the preselected input signal
    Figure PCTCN2015075606-APPB-100001
    And model coefficients of the dynamic model
    Figure PCTCN2015075606-APPB-100002
    The amplifier model formula is as follows:
    Figure PCTCN2015075606-APPB-100003
    wherein N represents the number of sampling points of each input signal in the preset input signal set, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal set, r is an integer greater than or equal to 1, and
    Figure PCTCN2015075606-APPB-100004
    a set of output signals representing said set of preset input signals, saidA static model representing said set of preset input signals, saidA dynamic model representing said set of preset input signals, saidA dynamic linear model representing said set of preset input signals, said
    Figure PCTCN2015075606-APPB-100008
    A dynamic non-linear model representing said set of preset input signals, said
    Figure PCTCN2015075606-APPB-100009
    An adjustment factor representing a dynamic linear model of the set of preset input signals, the
    Figure PCTCN2015075606-APPB-100010
    An adjustment factor representing a dynamic non-linear model of the set of preset input signals;
    Figure PCTCN2015075606-APPB-100006
    model coefficients of a static model of the current input signalAnd model coefficients of the dynamic model
    Figure PCTCN2015075606-APPB-100012
    Substituting the current input signal into the amplifier model formulaNumber corresponds to the amplifier model.
  3. The digital predistortion correction method of claim 2,
    determining the model coefficient of the static model of the current input signal by adopting an amplifier model formula according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal
    Figure PCTCN2015075606-APPB-100013
    And model coefficients of the dynamic modelThe method comprises the following steps:
    determining an adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal;
    determining an adjustment factor of a dynamic nonlinear model of the preset input signal set according to an adjustment factor of a dynamic nonlinear model of the preselected input signal;
    substituting the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group into the amplifier model formula to obtain model coefficients of the static model of the preset input signal group and model coefficients of the dynamic model of the preset input signal group;
    taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signalTaking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
    Figure PCTCN2015075606-APPB-100016
  4. The digital predistortion correction method of claim 3, wherein the preselected input signals are the first input signal with the highest power value and the second input signal with the lowest power value in the preset input signal set,
    the determining an adjustment factor for a dynamic linear model of a preselected input signal in an amplifier model from the preselected input signal comprises:
    determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula;
    determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula;
    the linear adjustment factor formula is as follows:
    Figure PCTCN2015075606-APPB-100017
    wherein, the thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1Parameter value representing a dynamic linear characteristic parameter of the first input signal, said
    Figure PCTCN2015075606-APPB-100018
    An adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
  5. The digital predistortion correction method of claim 4,
    the dynamic linear characteristic parameter is the average power of the output signals corresponding to the preset input signal group in the power amplifier or the gain of the output signals corresponding to the preset input signal group in the power amplifier.
  6. The digital predistortion correction method of claim 4,
    the determining an adjustment factor for a dynamic non-linear model of the preselected input signal in the amplifier model from the preselected input signal comprises:
    determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula is as follows:
    Figure PCTCN2015075606-APPB-100019
    wherein, the
    Figure PCTCN2015075606-APPB-100020
    A parameter value representing a dynamic non-linear characteristic parameter of said preselected input signal, said x(i)(n) represents the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to said preselected input signal;
    determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
    Figure PCTCN2015075606-APPB-100021
    wherein, theA parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
  7. The digital predistortion correction method of claim 6,
    the determining the adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal comprises:
    determining the adjustment factor of the dynamic linear model of the preset input signal set by adopting a first interpolation formula according to the adjustment factor of the dynamic linear model of the preselected input signal setThe first interpolation formula is:
    Figure PCTCN2015075606-APPB-100024
    wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal, and the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal
    Figure PCTCN2015075606-APPB-100025
    An adjustment factor representing a dynamic linear model of the first input signal, the
    Figure PCTCN2015075606-APPB-100026
    An adjustment factor representing a dynamic linear model of the second input signal, w(r)Representing a weight factor w(r)Is determined according to a weight formula and is obtained,the weight formula is as follows:
    wherein, the PrRepresenting the power level of an input signal of power level r, PMRepresenting a power value of said first input signal having a power magnitude M;
    the determining the adjustment factor of the dynamic nonlinear model of the preset input signal set according to the adjustment factor of the dynamic nonlinear model of the preselected input signal comprises:
    determining the adjustment factor of the dynamic nonlinear model of the preset input signal set by adopting a second interpolation formula according to the adjustment factor of the dynamic nonlinear model of the preselected input signal
    Figure PCTCN2015075606-APPB-100028
    The second interpolation formula is:
    Figure PCTCN2015075606-APPB-100029
    wherein, the
    Figure PCTCN2015075606-APPB-100030
    An adjustment factor representing a dynamic non-linear model of the first input signal, the
    Figure PCTCN2015075606-APPB-100031
    An adjustment factor representing a dynamic non-linear model of the second input signal, w(r)Representing a weighting factor.
  8. The method according to any of claims 1 to 7, wherein after the digital predistortion correction of the current input signal according to the DPD model, the method further comprises:
    and when the state of the power amplifier changes, updating the amplifier model of the current input signal to obtain an updated amplifier model.
  9. The digital predistortion correction method of claim 8,
    the state change of the power amplifier is device aging, temperature fluctuation or bias voltage change.
  10. The digital predistortion correction method of claim 8 or 9, wherein the updating the amplifier model of the current input signal results in an updated amplifier model, comprising:
    obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal;
    obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal;
    and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
  11. The digital predistortion correction method of claim 10,
    the obtaining of the model coefficient of the dynamic model of the updated amplifier model according to the amplifier model of the current input signal includes:
    taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value;
    and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
  12. The digital predistortion correction method of claim 10,
    the obtaining of the model coefficient of the updated static model of the amplifier model according to the amplifier model of the current input signal includes:
    taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value;
    and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the static model of the updated amplifier model.
  13. A digital predistortion correction device, characterized in that the digital predistortion correction device comprises:
    a processor for determining an adjustment factor of a dynamic linear model of a preselected input signal in an amplifier model according to the preselected input signal, the amplifier model being used for indicating a relation of an output signal to a static model of the input signal and a dynamic model of the input signal, the dynamic model comprising a dynamic linear model and a dynamic nonlinear model, wherein the dynamic linear model is used for indicating a linear characteristic in a variable of the input signal, the dynamic nonlinear model is used for indicating a nonlinear characteristic in a variable of the input signal, the preselected input signal is at least two signals in a preset input signal group, and the preset input signal group comprises a plurality of input signals with different power values;
    the processor is further configured to determine an adjustment factor for a dynamic nonlinear model of the preselected input signal in the amplifier model from the preselected input signal;
    the processor is further used for establishing an amplifier model of the current input signal according to the adjustment factor of the dynamic linear model of the preselected input signal and the adjustment factor of the dynamic nonlinear model of the preselected input signal;
    the processor is further used for obtaining a Digital Predistortion (DPD) model of the current input signal according to the amplifier model of the current input signal;
    the processor is further configured to perform digital predistortion correction on the current input signal according to the DPD model of the current input signal.
  14. The digital predistortion correction device of claim 13, wherein the processor is specifically configured to:
    determining model coefficients of a static model of the current input signal using an amplifier model formula based on adjustment factors of a dynamic linear model of the preselected input signal and adjustment factors of a dynamic nonlinear model of the preselected input signal
    Figure PCTCN2015075606-APPB-100032
    And model coefficients of the dynamic model
    Figure PCTCN2015075606-APPB-100033
    The amplifier model formula is as follows:
    Figure PCTCN2015075606-APPB-100034
    wherein N represents the number of sampling points of each input signal in the preset input signal set, L1 represents the number of model coefficients of the static model, L2 represents the number of model coefficients of the dynamic model, r represents the power magnitude of the input signals in the preset input signal set, r is an integer greater than or equal to 1, anda set of output signals representing said set of preset input signals,the above-mentioned
    Figure PCTCN2015075606-APPB-100036
    A static model representing said set of preset input signals, saidA dynamic model representing said set of preset input signals, said
    Figure PCTCN2015075606-APPB-100038
    A dynamic linear model representing said set of preset input signals, said
    Figure PCTCN2015075606-APPB-100039
    A dynamic non-linear model representing said set of preset input signals, saidAn adjustment factor representing a dynamic linear model of the set of preset input signals, the
    Figure PCTCN2015075606-APPB-100041
    An adjustment factor representing a dynamic non-linear model of the set of preset input signals;
    Figure PCTCN2015075606-APPB-100037
    model coefficients of a static model of the current input signal
    Figure PCTCN2015075606-APPB-100042
    And model coefficients of the dynamic model
    Figure PCTCN2015075606-APPB-100043
    And substituting the current input signal into the amplifier model formula to obtain an amplifier model corresponding to the current input signal.
  15. The digital predistortion correction device of claim 14, wherein the processor is specifically configured to:
    determining an adjustment factor of the dynamic linear model of the preset input signal set according to the adjustment factor of the dynamic linear model of the preselected input signal;
    determining an adjustment factor of a dynamic nonlinear model of the preset input signal set according to an adjustment factor of a dynamic nonlinear model of the preselected input signal;
    substituting the adjustment factors of the dynamic linear model of the preset input signal group and the adjustment factors of the dynamic nonlinear model of the preset input signal group into the amplifier model formula to obtain model coefficients of the static model of the preset input signal group and model coefficients of the dynamic model of the preset input signal group;
    taking the model coefficient of the static model of the preset input signal group as the model coefficient of the static model of the current input signal
    Figure PCTCN2015075606-APPB-100044
    Taking the model coefficient of the dynamic model of the preset input signal group as the model coefficient of the dynamic model of the current input signal
    Figure PCTCN2015075606-APPB-100045
  16. The digital predistortion correction device of claim 15, wherein the preselected input signal is a first input signal with a highest power value and a second input signal with a lowest power value in the preset input signal set, and the processor is specifically configured to:
    determining an adjustment factor of a dynamic linear model of the first input signal according to a dynamic linear characteristic parameter of the first input signal and a linear adjustment factor formula;
    determining an adjustment factor of a dynamic linear model of the second input signal according to a parameter value of a dynamic linear characteristic parameter of the second input signal and a linear adjustment factor formula;
    the linear adjustment factor formula is as follows:
    Figure PCTCN2015075606-APPB-100046
    wherein, the thetaiA parameter value representing a dynamic linear characteristic parameter of the first input signal or a parameter value representing a dynamic linear characteristic parameter of the second input signal, i represents a power level of the first input signal or a power level of the second input signal, θ1Parameter value representing a dynamic linear characteristic parameter of the first input signal, saidAn adjustment factor representing a dynamic linear model of the first input signal or an adjustment factor representing a dynamic linear model of the second input signal.
  17. The digital predistortion correction device of claim 16,
    the dynamic linear characteristic parameter is the average power of the output signals corresponding to the preset input signal group in the power amplifier or the gain of the output signals corresponding to the preset input signal group in the power amplifier.
  18. The digital predistortion correction device of claim 16, wherein the processor is specifically configured to:
    determining the parameter value of the dynamic nonlinear characteristic parameter of the preselected input signal according to the parameter value of the dynamic linear characteristic parameter of the preselected input signal and a nonlinear characteristic formula, wherein the nonlinear characteristic formula is as follows:
    Figure PCTCN2015075606-APPB-100048
    wherein, the
    Figure PCTCN2015075606-APPB-100049
    A parameter value representing a dynamic non-linear characteristic parameter of said preselected input signal, said x(i)(n) represents the signal value of the preselected input signal, y(i)(n) represents an output signal corresponding to said preselected input signal;
    determining an adjustment factor of a dynamic nonlinear model of the preselected input signal according to a parameter value of a dynamic nonlinear characteristic parameter of the preselected input signal and a nonlinear adjustment factor formula, wherein the nonlinear adjustment factor formula is as follows:
    Figure PCTCN2015075606-APPB-100050
    wherein, the
    Figure PCTCN2015075606-APPB-100051
    A parameter value representing a dynamic non-linear characteristic parameter of the first input signal.
  19. The digital predistortion correction device of claim 18, wherein the processor is specifically configured to:
    determining the adjustment factor of the dynamic linear model of the preset input signal set by adopting a first interpolation formula according to the adjustment factor of the dynamic linear model of the preselected input signal set
    Figure PCTCN2015075606-APPB-100052
    The first interpolation formula is:
    Figure PCTCN2015075606-APPB-100053
    wherein r represents that the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal and larger than the power level M of the second input signal, and the power level of the input signals in the preset input signal group is smaller than the power level M of the first input signal
    Figure PCTCN2015075606-APPB-100054
    An adjustment factor representing a dynamic linear model of the first input signal, the
    Figure PCTCN2015075606-APPB-100055
    An adjustment factor representing a dynamic linear model of the second input signal, w(r)Representing a weight factor w(r)The weight formula is determined according to the weight formula, wherein the weight formula is as follows:
    Figure PCTCN2015075606-APPB-100056
    wherein, the PrRepresenting the power level of an input signal of power level r, PMRepresenting a power value of said first input signal having a power magnitude M;
    the processor is further specifically configured to determine the adjustment factor of the dynamic nonlinear model of the set of predetermined input signals using a second interpolation formula based on the adjustment factor of the dynamic nonlinear model of the preselected input signal
    Figure PCTCN2015075606-APPB-100057
    The second interpolation formula is:
    Figure PCTCN2015075606-APPB-100058
    wherein, theAn adjustment factor representing a dynamic non-linear model of the first input signal, the
    Figure PCTCN2015075606-APPB-100060
    An adjustment factor representing a dynamic non-linear model of the second input signal, w(r)Representing a weighting factor.
  20. The digital predistortion correction device of any of claims 13 to 19, wherein the processor is further configured to:
    and when the state of the power amplifier changes, updating the amplifier model of the current input signal to obtain an updated amplifier model.
  21. The digital predistortion correction device of claim 20,
    the state change of the power amplifier is device aging, temperature fluctuation or bias voltage change.
  22. The digital predistortion correction device of claim 20 or 21, wherein the processor is specifically configured to:
    obtaining a model coefficient of a dynamic model of the updated amplifier model according to the amplifier model of the current input signal;
    obtaining a model coefficient of a static model of the updated amplifier model according to the amplifier model of the current input signal;
    and substituting the model coefficient of the dynamic model of the updated amplifier model and the model coefficient of the static model of the updated amplifier model into the amplifier model to obtain the updated amplifier model.
  23. The digital predistortion correction device of claim 22, wherein the processor is further specifically configured to:
    taking the difference between the model coefficient of the dynamic model of the input signal after the state of the power amplifier is changed and the model coefficient of the dynamic model of the input signal before the state is changed as a first difference value;
    and taking the sum of the model coefficient of the dynamic model of the current input signal and the first difference value as the model coefficient of the dynamic model of the updated amplifier model.
  24. The digital predistortion correction device of claim 22, wherein the processor is further specifically configured to:
    taking the difference between the model coefficient of the static model of the input signal after the state of the power amplifier is changed and the model coefficient of the static model of the input signal before the state is changed as a second difference value;
    and taking the sum of the model coefficient of the static model of the current input signal and the second difference value as the model coefficient of the static model of the updated amplifier model.
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