CN116455709A - Digital predistortion method, device, electronic equipment and storage medium - Google Patents

Abstract

The present application provides a digital pre-distortion method, device, electronic equipment, and storage medium, the method comprising: acquiring a signal to be transmitted; performing a process on the signal to be transmitted according to a first digital pre-distortion lookup table within a first time period Digital pre-distortion, determining a first digital pre-distortion output of the signal to be transmitted within the first time period; within a second time period, performing digital pre-distortion on the signal to be transmitted according to a second digital pre-distortion lookup table Distortion, determining a second digital predistortion output of the signal to be transmitted within the second time period. The digital pre-distortion method is used to implement a high-precision digital pre-distortion solution in a Wi‑Fi time-division duplex mode, thereby improving dynamic EVM performance.

Description

Digital predistortion method, device, electronic equipment and storage medium

technical field

The present application relates to the field of signal predistortion, in particular, to a digital predistortion method, device, electronic equipment and storage medium.

Background technique

A power amplifier (Power Amplifier, PA) is widely used in various electronic fields. However, since the PA circuit has a nonlinear gain characteristic, after the signal is amplified by the PA circuit, nonlinear distortion will occur, which will cause error vector magnitude (Error Vector Magnitude, EVM) to deteriorate. Therefore, it is necessary to compensate the signal to reduce the nonlinear distortion introduced by the PA circuit. Currently, a digital pre-distortion (Digital Pre-Distortion, DPD) technology is usually used to implement linearization of the PA.

With the development of Wi-Fi technology, the requirements for EVM are also more stringent. At the same time, because Wi-Fi generally adopts the time-division duplex mode, when the device needs to transmit, it opens the transmission path (including PA) and closes the reception path; when it does not need to transmit, it remains in the receiving state, closes the transmission path, and opens the reception path. In this mode, when the device sends a packet, it needs to switch from RX (Receive, receive) to TX (Transport, send), and turn on the PA at the same time. After the device sends packets, close the PA. When the device needs to send packets again, restart the PA.

It takes a certain amount of time for the PA to reach a stable operating point from being turned on. During this period of time, the working state of the PA changes, which will cause a certain degree of deterioration of the dynamic EVM. In the Wi-Fi TDD mode, the PA on the Wi-Fi transmitter will constantly switch between on and off, and the non-linear characteristics of the PA are different in the turn-on phase and the stable phase. Therefore, the existing DPD scheme has the problem of low accuracy.

Contents of the invention

The purpose of the embodiments of the present application is to provide a digital pre-distortion method, device, electronic equipment, and storage medium to implement a high-precision digital pre-distortion solution in Wi-Fi time-division duplex mode, thereby improving dynamic EVM performance .

In a first aspect, the present application provides a digital pre-distortion method, including: acquiring a signal to be transmitted; performing digital pre-distortion on the signal to be transmitted according to a first digital pre-distortion lookup table within a first time period, and determining the The first digital pre-distortion output of the signal to be transmitted within the first time period; within the second time period, perform digital pre-distortion on the signal to be transmitted according to the second digital pre-distortion lookup table, and determine the signal to be transmitted A second digital predistortion output of the signal within the second time period.

In the above implementation process, considering that the power amplifier has different nonlinear characteristics in different time periods, the first digital pre-distortion look-up table and the second digital pre-distortion look-up table are set. During the digital pre-distortion process, the first digital pre-distortion look-up table Select the first digital pre-distortion look-up table for digital pre-distortion in the time period to compensate the nonlinear characteristics introduced by the power amplifier in the first time period, and select the second digital pre-distortion look-up table in the second time period for digital pre-distortion to compensate power The non-linear characteristic introduced by the amplifier in the first time period realizes a high-precision digital pre-distortion scheme.

In an optional implementation manner, before the acquisition of the signal to be sent, the method further includes: training the first digital predistortion model according to the data of the training signal in the first time period, and determining the first digital predistortion model A digital pre-distortion look-up table; the second digital pre-distortion model is trained according to the data of the training signal in the second time period, and the second digital pre-distortion look-up table is determined.

In an optional implementation manner, the training of the first digital predistortion model according to the data of the training signal in the first time period, and determining the first digital predistortion lookup table include: obtaining the first digital predistortion lookup table A training data and first feedback data; wherein, the first training data is the output data obtained after the data of the training signal is input into the digital predistorter within the first time period, and the first feedback data is the The output data obtained after the first training data is input into the power amplifier; the first digital pre-distortion model is trained according to the first training data and the first feedback data, and the corresponding first digital pre-distortion model after training is obtained first model coefficients; generating a first digital predistortion lookup table according to the first model coefficients.

In an optional implementation manner, the training of the second digital predistortion model according to the data of the training signal in the second time period, and determining the second digital predistortion lookup table include: Obtaining second training data and second feedback data; wherein, the second training data is the output data obtained after the data of the training signal is input into the digital predistorter within the second time period, and the second feedback data is The output data obtained after the second training data is input into the power amplifier; the second digital pre-distortion model is trained according to the second training data and the second feedback data to obtain the trained second digital pre-distortion second model coefficients corresponding to the model; generating a second digital predistortion lookup table according to the second model coefficients.

In an optional embodiment, the first time period is the time period between the start time of the signal to be transmitted and the time when the power amplifier reaches the working stable state, and the second time period is the time period when the power amplifier reaches the working state. The time period between the moment of the steady state and the end moment of the signal to be sent.

In the embodiment of the present application, in order to eliminate the nonlinear characteristics of the working state of the power amplifier before reaching the stable working state and after reaching the stable working state, the first time period is set from the initial moment of the signal to be sent to the arrival of the power amplifier. The time period between the moments of the stable state of work, the second time period is set as the time period between the moment when the power amplifier reaches the stable state of work and the end moment of the signal to be sent, when performing digital pre-distortion, at the first time The first digital pre-distortion look-up table is selected for digital pre-distortion in the first period, and the second digital pre-distortion look-up table is selected for digital pre-distortion in the second period, thereby realizing a high-precision digital pre-distortion solution.

In an optional implementation manner, within the first time period, digital predistortion is performed on the signal to be transmitted according to a first digital predistortion lookup table, and it is determined that the signal to be transmitted is within the first time period The first DPD output consists of:

Determine the first digital predistortion output according to the following formula:

Wherein, y ₁ (n) is the first digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT1 _m,k (|x(nk)| is the first digital A predistortion lookup table, M and K are memory depths, t _d is the end moment of the first time period, and Fs is a sampling rate.

In an optional implementation manner, within the second time period, digital predistortion is performed on the signal to be transmitted according to a second digital predistortion lookup table, and it is determined that the signal to be transmitted is within the second time period The second DPD output consists of:

The second digital predistortion output is determined according to the following formula:

Wherein, y ₂ (n) is the second digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT2 _m,k (|x(nk)| is the second digital A predistortion lookup table, M and K are the memory depth, _td is the end moment of the first time period, T is the duration of the signal to be sent, and Fs is the sampling rate.

In a second aspect, the present application provides a digital pre-distortion device, including: an acquisition module, configured to acquire a signal to be transmitted; a first pre-distortion module, configured to perform a pair of performing digital pre-distortion on the signal to be transmitted, and determining a first digital pre-distortion output of the signal to be transmitted within the first time period; The digital predistortion lookup table performs digital predistortion on the signal to be transmitted, and determines a second digital predistortion output of the signal to be transmitted within the second time period.

In an optional implementation manner, the digital pre-distortion device further includes: a first training module, configured to train the first digital pre-distortion model according to the data of the training signal in the first time period, and determine the A first digital pre-distortion look-up table; a second training module, configured to train a second digital pre-distortion model according to the data of the training signal in the second time period, and determine the second digital pre-distortion look-up table .

In an optional implementation manner, the first training module is specifically configured to acquire first training data and first feedback data; wherein, the first training data is data input of training signals within the first time period The output data obtained after the digital predistorter, the first feedback data is the output data obtained after the first training data is input into the power amplifier; according to the first training data and the first feedback data, the first feedback data is A digital predistortion model is trained to obtain first model coefficients corresponding to the trained first digital predistortion model; a first digital predistortion lookup table is generated according to the first model coefficients.

In an optional implementation manner, the second training module is specifically configured to acquire second training data and second feedback data; wherein, the second training data is the data input of the training signal within the second time period The output data obtained after the digital predistorter, the second feedback data is the output data obtained after the second training data is input into the power amplifier; according to the second training data and the second feedback data, the first Two digital pre-distortion models are trained to obtain second model coefficients corresponding to the trained second digital pre-distortion model; a second digital pre-distortion lookup table is generated according to the second model coefficients.

In an optional embodiment, the first time period is the time period between the start time of the signal to be transmitted and the time when the power amplifier reaches the working stable state, and the second time period is the time period when the power amplifier reaches the working state. The time period between the moment of the steady state and the end moment of the signal to be sent.

In an optional implementation manner, the first pre-distortion module is specifically configured to determine the first digital pre-distortion output according to the following formula:

Wherein, y ₁ (n) is the first digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT1 _m,k (|x(nk)| is the first digital A predistortion lookup table, M and K are memory depths, _td is the end moment of the first time period, and Fs is a sampling rate.

In an optional implementation manner, the second pre-distortion module is specifically configured to determine the second digital pre-distortion output according to the following formula:

Wherein, y ₂ (n) is the second digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT2 _m,k (|x(nk)| is the second digital A predistortion lookup table, M and K are the memory depth, _td is the end moment of the first time period, T is the duration of the signal to be sent, and Fs is the sampling rate.

In a third aspect, the present application provides an electronic device, including: a processor, a memory, and a bus; the processor and the memory communicate with each other through the bus; Executed program instructions, the processor calls the program instructions to be able to execute the method as described in any one of the foregoing implementation manners.

In a fourth aspect, the present application provides a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are read and executed by a computer, any one of the preceding implementation modes is executed. the method described.

Description of drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings that need to be used in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, so It should not be regarded as a limitation on the scope, and those skilled in the art can also obtain other related drawings according to these drawings without creative work.

FIG. 1 is a flow chart of a digital predistortion method provided in an embodiment of the present application;

FIG. 2 is a schematic diagram of a training signal provided by an embodiment of the present application;

FIG. 3 is a digital predistortion indirect learning framework provided by an embodiment of the present application;

FIG. 4 is an overall flow chart of a digital predistortion method provided in an embodiment of the present application;

FIG. 5 is a structural block diagram of a digital predistortion device provided by an embodiment of the present application;

FIG. 6 is a schematic structural diagram of an electronic device provided by an embodiment of the present application.

Detailed ways

The technical solutions in the embodiments of the present application will be described below with reference to the drawings in the embodiments of the present application.

The purpose of the embodiments of the present application is to provide a digital pre-distortion method, device, electronic equipment, and storage medium for realizing a high-precision digital pre-distortion solution in a Wi-Fi time-division duplex mode.

For the convenience of understanding this scheme, the professional terms involved in this scheme are explained below.

Time-division duplex mode: When the device needs to transmit data packets, it opens the transmission path (including PA) and closes the reception path. When the device does not need to transmit data packets, it remains in the receiving state, closes the transmission path, and opens the reception path. In time-division duplex mode, when the device needs to transmit data packets, it needs to switch from RX to TX and turn on PA at the same time.

Digital predistortion: through a predistortion element (Predistorter) to cascade with the power amplifier element (PA), the nonlinear distortion function is built into the digital, digital baseband signal processing domain, which is equivalent to ("equal") the amount of distortion exhibited by the amplifier , but the function is reversed. Combining these two non-linear distortion functions enables a highly linear, distortion-free system.

This technology can be realized by using corresponding software, hardware and a combination of software and hardware. The following describes the embodiments of the present application in detail.

Fig. 1 is a flow chart of a digital pre-distortion method provided by the embodiment of the present application, the digital pre-distortion method may include the following:

Step 101: Obtain a signal to be sent.

Step 102: In the first time period, perform digital predistortion on the signal to be transmitted according to the first digital predistortion lookup table, and determine the first digital predistortion output of the signal to be transmitted in the first time period.

Step 103: During the second period of time, perform digital predistortion on the signal to be transmitted according to the second digital predistortion lookup table, and determine a second digital predistortion output of the signal to be transmitted within the second period of time.

In the embodiment of the present application, when an electronic device supporting the Wi-Fi function (using time division duplex mode for data transmission and reception) sends a Wi-Fi data packet (that is, a signal to be sent), the electronic device switches from RX to TX, and the electronic device The digital predistorter in the Wi-Fi transmitter on the Internet obtains the signal to be sent to be sent by the electronic device, and the signal to be sent may be a digital signal.

When an electronic device switches from RX to TX, the PA in the Wi-Fi transmitter turns on. Since it takes a certain amount of time for the PA to reach a stable operating point from being turned on, changes in the working state of the PA during this period will cause a certain degree of deterioration of the EVM. Therefore, in order to match the change of the working state of the PA in different time periods, according to the set time segment, in the first time period, the digital predistorter uses the first digital predistortion lookup table to perform digital predistortion on the signal to be transmitted, Determine the first digital predistortion output of the signal to be sent within the first time period. During the second time period, the digital predistorter uses the second digital predistortion lookup table to perform digital predistortion on the signal to be transmitted, and determines the second digital predistortion output of the signal to be transmitted within the second time period.

It should be noted that the signal to be sent lasts for a period of time when it is sent. The first digital pre-distortion output is the output generated by the digital pre-distortion device after using the first digital pre-distortion look-up table to perform digital pre-distortion on the data of the signal to be transmitted in the first time period, and the second digital pre-distortion output is the output of the digital pre-distortion device An output generated after performing digital pre-distortion on the data of the signal to be transmitted within the second time period by using the second digital pre-distortion look-up table.

Through the above method, the first digital pre-distortion look-up table and the second digital pre-distortion look-up table are set. When performing digital pre-distortion, use the corresponding digital pre-distortion look-up table to perform digital pre-distortion on the signal to be sent in different time periods, reducing the The deterioration of EVM caused by the change of PA working state reduces the spectrum spread, so as to realize the high-precision digital pre-distortion scheme.

The following describes how to obtain the first digital predistortion lookup table and the second digital predistortion lookup table.

As an optional implementation manner, the digital predistortion method provided in the embodiment of the present application may also include the following content:

A1: Train the first digital predistortion model according to the data of the training signal in the first time period, and determine the first digital predistortion lookup table.

A2: Train the second digital predistortion model according to the data of the training signal in the second time period, and determine the second digital predistortion lookup table.

In the embodiment of the present application, before digital pre-distortion is performed on the signal to be transmitted, two digital pre-distortion models are constructed, and the data of the training signal in different time periods are used to carry out the first digital pre-distortion model and the second digital pre-distortion model. Training, determining the first digital pre-distortion look-up table and the second digital pre-distortion look-up table.

As an optional implementation, as shown in Figure 2, the first time period is the time period between the initial moment of the training signal (corresponding to Packet in Figure 2) and the time when the power amplifier reaches a stable working state, and the first time period The second time period is the time period between the time when the power amplifier reaches the stable working state and the end time of the training signal.

The PA is turned on when the electronic device is switched from RX to TX. In order to match the change of the working state of the PA in different time periods, the first time period is set as the time between the initial moment of the training signal and the moment when the PA reaches a stable working state. segment, train the first digital pre-distortion model according to the data of the training signal in the first time segment, and determine the first digital pre-distortion look-up table. The second time period is set as the time period between the moment when the PA reaches the stable working state and the end moment of the training signal, and the second digital predistortion model is trained according to the data of the training signal in the second time period, and the second digital predistortion model is determined. Two digital predistortion look-up tables.

Further, the above step A1 may include the following:

Obtain first training data and first feedback data; train the first digital pre-distortion model according to the first training data and the first feedback data, and obtain first model coefficients corresponding to the trained first digital pre-distortion model; according to the first A model coefficient generates a first digital predistortion look-up table.

In the embodiment of the present application, the first training data is the output data obtained after the data of the training signal in the first time period is input to the digital predistorter, and the first feedback data is the output data obtained after the first training data is input to the power amplifier.

Specifically, please refer to FIG. 3 . FIG. 3 is a digital predistortion indirect learning architecture provided by an embodiment of the present application. Firstly, a first digital pre-distortion model is constructed, where the first digital pre-distortion model may be a Volterra series-simplified GMP model. The first digital predistortion model is:

Among them, n=0, 1, 2, ..., N ₁ -1; y ₁ (n) is the first training data, f _p {|x ₁ (nk)|} is the nonlinear basis of the nonlinear memory model, M and K memory depth, P is the order of the nonlinear basis; x ₁ is the data of the training signal in the first time period, and a _mkp is the coefficient of the first digital predistortion model.

It should be noted that the value of M can be: 2, 5, 8 and other natural numbers, the value of K can be: 2, 5, 8 and other natural numbers, and the values of M and K can be equal or unequal. This application This is not specifically limited.

The digital predistorter in Figure 3 includes the pre-inverse function of the PA, and the digital pre-distortion trainer includes the post-inverse function of the PA. The two are equivalent to each other, using the same pre-distortion model and coefficients, and will undergo digital pre-distortion training The coefficients calculated by the filter are copied to the digital predistorter.

After determining the first digital pre-distortion model, send a training signal (x(n) in Figure 3), after the training signal x ₁ (n) in the first time period passes through the digital pre-distorter, output the first training data y ₁ (n). After the first training data y ₁ (n) is processed by the digital-to-analog converter, the up-conversion module, the PA, the up-conversion module and the analog-to-digital converter, the first feedback data z ₁ (n) is obtained.

In the process of training the first digital predistortion model, it is expected that the first feedback data z ₁ (n) is close to the training signal x ₁ (n), since the pre-inverse function and the post-inverse function are the same, that is, the expectation e ₁ (n) =y ₁ (n)-v ₁ (n) is the smallest, and v ₁ (n)→y ₁ (n) is taken as the iteration direction.

Create the first set of solving equations:

Define the equation basis r _mkp (n)=z ₁ (nm)f _p {|z ₁ (nk)|}

Then there is a matrix of equations:

in

The coefficient matrix _AL×1 can then be calculated using algorithms such as least squares, least mean squares, and recursive least squares. As an example, compute the coefficient matrix using the least squares algorithm:

Substitute the first training data y ₁ (n) into the above formula, and solve to obtain the coefficient matrix _AL×1 . Copy the calculated coefficients to the digital predistorter, send a training signal again, repeat the above steps, and perform the next round of coefficient matrix calculation until a converged coefficient matrix is obtained.

In some implementations, the convergence condition of the coefficient matrix may be that the mean square error MES of e ₁ (n)=y ₁ (n)−v ₁ (n) is smaller than a preset threshold.

In some other implementation manners, the convergence condition of the coefficient matrix may be that the mean square error MES of x ₁ (n)-z ₁ (n) is smaller than a preset threshold.

The converged coefficient matrix is the first model coefficient corresponding to the trained first digital predistortion model. After the first model coefficients are determined, a first digital predistortion look-up table LUT (Look-Up-Table) is generated according to the first model coefficients. It should be noted that the specific manner of generating the first digital predistortion lookup table according to the first model coefficients may refer to the prior art, and details are not repeated here for the sake of brevity in the description.

Further, the above step A2 may include the following:

Obtain second training data and second feedback data; train the second digital pre-distortion model according to the second training data and the second feedback data, and obtain second model coefficients corresponding to the trained second digital pre-distortion model; according to the second The second model coefficients generate a second digital predistortion lookup table.

In the embodiment of the present application, the second training data is the output data obtained after the data of the training signal in the second time period is input to the digital predistorter, and the second feedback data is the output data obtained after the second training data is input to the power amplifier.

Continuing to refer to FIG. 3, a second digital pre-distortion model is constructed, where the second digital pre-distortion model may be a Volterra series-simplified GMP model. The second digital predistortion model is:

Among them, n=0, 1, 2, ..., N ₂ -1; y ₂ (n) is the second training data, f _p {|x ₂ (nk)|} is the nonlinear basis of the nonlinear memory model, M and K memory depth, P is the order of the nonlinear basis; x ₂ is the data of the training signal in the second time period, and b _mkp is the second digital predistortion model coefficient.

It can be understood that the memory depths M and K in the first digital predistortion model may be the same as or different from the memory depths M and K in the second digital predistortion model. When using the same memory depth, the depth of the determined first digital pre-distortion look-up table and the second digital pre-distortion look-up table are the same; otherwise, the determined first digital pre-distortion look-up table and the depth of the second digital pre-distortion look-up table has a difference.

After the second digital predistortion model is determined, a second set of solving equations is established:

Define the equation basis r _mkp (n)=z ₂ (nm)f _p {|z ₂ (nk)|}

Then there is a matrix of equations:

in

The coefficient matrix _BL×1 can then be calculated using algorithms such as least squares, least mean squares, and recursive least squares. As an example, compute the coefficient matrix using the least squares algorithm:

The second training data y ₂ (n) is substituted into the above formula, and the coefficient matrix _BL×1 is obtained through calculation. Copy the calculated coefficients to the digital predistorter, send a training signal again, repeat the above steps, and perform the next round of coefficient matrix calculation until a converged coefficient matrix is obtained.

It should be noted that the training process of the second digital pre-distortion model is similar to the training process of the first digital pre-distortion model, and for the sake of brevity in the description, reference may be made to the same or similar points. The difference between the two is that the first digital predistortion model uses the data of the training signal in the first time period during training, and the second digital predistortion model uses the data of the training signal in the second time period during training. .

According to the foregoing introduction, it can be seen that the data of the training signal in the first time period and the data of the training signal in the second time period are continuous in time. Therefore, the training process of the first digital predistortion model and the second digital predistortion model can be performed serially, that is, after the training signal is input into the digital predistortion indirect learning framework in Fig. A digital predistortion model is trained. Immediately after the second period of time, the second digital predistortion model is trained. Using the above serial training manner can save resource overhead for training the first digital predistortion model and the second digital predistortion model.

In the embodiment of the present application, when determining the digital pre-distortion look-up table, considering that there is a difference in the non-linear characteristics of the power amplifier before reaching the stable working state and after reaching the stable working state, in order to eliminate this part of the difference, two digital pre-distortion The distortion model adopts the data of the training signal in two time periods before the power amplifier reaches the stable working state (the first time period) and after the power amplifier reaches the stable working state (the second time period). The pre-distortion model is trained to generate a first digital pre-distortion look-up table corresponding to the power amplifier before reaching a stable working state and a second digital pre-distortion look-up table corresponding to the power amplifier after reaching a stable working state.

Further, after the training of the first digital predistortion model and the second digital predistortion model is completed, a first digital predistortion lookup table and a second digital predistortion lookup table are obtained. The first digital predistortion lookup table and the second digital predistortion lookup table are stored in the digital predistorter. After the digital predistorter obtains the signal to be transmitted, the signal to be transmitted is within the first time period, and the signal to be transmitted is digitally predistorted using the first digital predistortion lookup table to determine the first time period of the signal to be transmitted within the first time period. A digital predistortion output; after the signal to be transmitted enters the second time period, use the second digital predistortion lookup table to perform digital predistortion on the signal to be transmitted, and determine the second digital predistortion output of the signal to be transmitted within the second time period.

As an optional implementation, the first time period is the time period between the initial moment of the signal to be transmitted and the time when the power amplifier reaches the stable working state, and the second time period is the time period between the time when the power amplifier reaches the stable working state and The time period between the end moments of the signal to be sent.

In the embodiment of the present application, in order to eliminate the nonlinear characteristics of the working state of the power amplifier before reaching the stable working state and after reaching the stable working state, the first time period is set from the initial moment of the signal to be sent to the arrival of the power amplifier. The time period between the moments of the stable state of work, the second time period is set as the time period between the moment when the power amplifier reaches the stable state of work and the end moment of the signal to be sent, when performing digital pre-distortion, at the first time The first digital pre-distortion look-up table is selected to perform digital pre-distortion in the first period, and the second digital pre-distortion look-up table is selected to perform digital pre-distortion in the second period, so as to realize a high-precision digital pre-distortion solution.

It can be understood that the two time periods when performing digital pre-distortion are the same as the two time periods when training the first digital pre-distortion model and the second digital pre-distortion model.

Further, as an optional implementation manner, the above step 102 may include the following content:

Determine the first digital predistortion output according to the following formula:

Wherein, y ₁ (n) is the first digital pre-distortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT1 _{m, k} (|x(nk)| is the first digital pre-distortion look-up table, M and K are the memory depth, t _d is the end moment of the first time period, and Fs is the sampling rate.

Further, as an optional implementation manner, the above step 103 may include the following content:

Determine the second digital predistortion output according to the following formula:

Wherein, y ₂ (n) is the second digital pre-distortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT2 _{m, k} (|x(nk)| is the second digital pre-distortion look-up table, M and K are the memory depth, t _d is the end moment of the first time period, T is the duration of the signal to be sent, and Fs is the sampling rate.

For ease of understanding, please refer to FIG. 4 , which is an overall flow chart of the digital predistortion method provided by the embodiment of the present application. As shown in Figure 4, the first digital pre-distortion model and the second digital pre-distortion model are first constructed, and the first set of solution equations and the second set of solutions are respectively constructed according to the first digital pre-distortion model and the second digital pre-distortion model Calculate the equation. After sending the training signal and inputting the training signal into the digital predistortion indirect learning framework in Fig. 3, within the first period of time, using the first training data and the first feedback data to solve the first set of solving equations, Determine the first coefficient matrix. In the second time period, the second set of solving equations are solved by using the second training data and the second feedback data to determine the second coefficient matrix. Multiple training signals are sent, and the above steps are repeated until the first coefficient matrix and the second coefficient matrix converge.

After the first coefficient matrix and the second coefficient matrix are determined, the first digital predistortion lookup table is determined according to the first coefficient matrix, the second digital predistortion lookup table is determined according to the second coefficient matrix, and the first digital predistortion lookup table and the second digital predistortion lookup table are determined. Two digital predistortion look-up tables are stored in the digital predistorter. In the digital pre-distortion stage, after the digital pre-distorter obtains the signal to be transmitted, the signal to be transmitted uses the first digital pre-distortion look-up table to perform digital pre-distortion on the signal to be transmitted within the first time period, and determines that the signal to be transmitted is in The first digital pre-distortion output in the first time period; after the signal to be transmitted enters the second time period, use the second digital pre-distortion lookup table to perform digital pre-distortion on the signal to be transmitted, and determine the signal to be transmitted in the second time period Second digital predistortion output. The digital predistortion output in FIG. 4 is the output of the signal to be transmitted after passing through the digital predistorter (ie, the first digital predistortion output and the second digital predistortion output).

Based on the same inventive concept, an embodiment of the present application further provides a digital predistortion device. Please refer to FIG. 5. FIG. 5 is a structural block diagram of a digital pre-distortion device provided in an embodiment of the present application. The digital pre-distortion device 500 may include:

An acquisition module 501, configured to acquire a signal to be sent;

The first pre-distortion module 502 is configured to perform digital pre-distortion on the signal to be transmitted according to a first digital pre-distortion lookup table within a first time period, and determine the signal to be transmitted within the first time period the first digital predistortion output;

The second pre-distortion module 503 is configured to perform digital pre-distortion on the signal to be transmitted according to a second digital pre-distortion lookup table within a second time period, and determine the signal to be transmitted within the second time period Second digital predistortion output.

In an optional implementation manner, the digital pre-distortion device further includes:

The first training module is used to train the first digital pre-distortion model according to the data of the training signal in the first time period, and determine the first digital pre-distortion look-up table;

The second training module is configured to train a second digital predistortion model according to data of the training signal within the second time period, and determine the second digital predistortion lookup table.

In an optional implementation manner, the first training module is specifically configured to acquire first training data and first feedback data; wherein, the first training data is data input of training signals within the first time period The output data obtained after the digital predistorter, the first feedback data is the output data obtained after the first training data is input into the power amplifier;

training the first digital pre-distortion model according to the first training data and the first feedback data, to obtain first model coefficients corresponding to the trained first digital pre-distortion model;

A first digital predistortion lookup table is generated according to the first model coefficients.

In an optional implementation manner, the second training module is specifically configured to acquire second training data and second feedback data; wherein, the second training data is the data input of the training signal within the second time period The output data obtained after the digital predistorter, the second feedback data is the output data obtained after the second training data is input into the power amplifier;

training the second digital predistortion model according to the second training data and the second feedback data, to obtain second model coefficients corresponding to the trained second digital predistortion model;

A second digital predistortion lookup table is generated according to the second model coefficients.

In an optional embodiment, the first time period is the time period between the start time of the signal to be transmitted and the time when the power amplifier reaches the working stable state, and the second time period is the time period when the power amplifier reaches the working state. The time period between the moment of the steady state and the end moment of the signal to be sent.

In an optional implementation manner, the first pre-distortion module 502 is specifically configured to determine the first digital pre-distortion output according to the following formula:

Wherein, y ₁ (n) is the first digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT1 _m,k (|x(nk)| is the first digital A predistortion lookup table, M and K are memory depths, t _d is the end moment of the first time period, and Fs is a sampling rate.

In an optional implementation manner, the second pre-distortion module 503 is specifically configured to determine the second digital pre-distortion output according to the following formula:

Wherein, y ₂ (n) is the second digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT2 _m,k (|x(nk)| is the second digital A predistortion lookup table, M and K are the memory depth, _td is the end moment of the first time period, T is the duration of the signal to be sent, and Fs is the sampling rate.

Please refer to FIG. 6 . FIG. 6 is a schematic structural diagram of an electronic device 600 according to an embodiment of the present application. The electronic device 600 includes: at least one processor 601 , at least one communication interface 602 , at least one memory 603 and at least one bus 604 . Wherein, the bus 604 is used to realize the direct connection and communication of these components, the communication interface 602 is used to perform signaling or data communication with other node devices, and the memory 603 stores machine-readable instructions executable by the processor 601 . When the electronic device 600 is running, the processor 601 communicates with the memory 603 through the bus 604 , and when the machine-readable instructions are invoked by the processor 601 , the digital pre-distortion method described above is executed.

The processor 601 may be an integrated circuit chip with signal processing capability. Above-mentioned processor 601 can be general-purpose processor, comprises central processing unit (Central Processing Unit, CPU), network processor (NetworkProcessor, NP) etc.; Can also be digital signal processor (Digital Signal Processing, DSP), ASIC (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can realize or execute various methods, steps and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

Memory 603 may include but not limited to random access memory (Random Access Memory, RAM), read-only memory (Read Only Memory, ROM), programmable read-only memory (Programmable Read-Only Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM), Electrically Erasable Read-Only Memory (Electric Erasable Programmable Read-Only Memory, EEPROM), etc.

It can be understood that the structure shown in FIG. 6 is only for illustration, and the electronic device 600 may also include more or less components than those shown in FIG. 6 , or have a configuration different from that shown in FIG. 6 . Each component shown in FIG. 6 may be implemented by hardware, software or a combination thereof. In the embodiment of the present application, the electronic device 600 may be, but not limited to, physical devices such as desktop computers, notebook computers, smart phones, smart wearable devices, and vehicle-mounted devices, or virtual devices such as virtual machines. In addition, the electronic device 600 is not necessarily a single device, but may also be a combination of multiple devices, such as a server cluster, and so on.

In addition, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run by a computer, the steps of the digital predistortion method in the above-mentioned embodiments are executed.

In the embodiments provided in this application, it should be understood that the disclosed devices and methods may be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

In addition, the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

Furthermore, each functional module in each embodiment of the present application may be integrated to form an independent part, each module may exist independently, or two or more modules may be integrated to form an independent part.

It should be noted that, if the functions are realized in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disk, and other media capable of storing program codes.

In this document, relational terms such as first and second etc. are used only to distinguish one entity or operation from another without necessarily requiring or implying any such relationship between these entities or operations. Actual relationship or sequence.

The above descriptions are only examples of the present application, and are not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and changes may be made to the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims (10)

1. A digital predistortion method, characterized in that, comprising: Get the signal to be sent; In the first time period, perform digital pre-distortion on the signal to be transmitted according to a first digital pre-distortion lookup table, and determine a first digital pre-distortion output of the signal to be transmitted in the first time period; In the second time period, perform digital pre-distortion on the signal to be transmitted according to a second digital pre-distortion lookup table, and determine a second digital pre-distortion output of the signal to be transmitted in the second time period. 2. The digital predistortion method according to claim 1, characterized in that, before the acquisition of the signal to be transmitted, the method further comprises: Train the first digital predistortion model according to the data of the training signal in the first time period, and determine the first digital predistortion lookup table; The second digital predistortion model is trained according to the data of the training signal in the second time period, and the second digital predistortion lookup table is determined. 3. The digital pre-distortion method according to claim 2, wherein the first digital pre-distortion model is trained according to the data of the training signal in the first time period, and the first digital pre-distortion model is determined. Digital predistortion lookup table, including: Obtain first training data and first feedback data; wherein, the first training data is the output data obtained after the data of the training signal is input into the digital predistorter within the first time period, and the first feedback data is output data obtained after the first training data is input into the power amplifier; training the first digital pre-distortion model according to the first training data and the first feedback data, to obtain first model coefficients corresponding to the trained first digital pre-distortion model; A first digital predistortion lookup table is generated according to the first model coefficients. 4. The digital pre-distortion method according to claim 2, wherein the second digital pre-distortion model is trained according to the data of the training signal in the second time period to determine the The second digital predistortion look-up table includes: Obtaining second training data and second feedback data; wherein, the second training data is the output data obtained after the data of the training signal is input into the digital predistorter within the second time period, and the second feedback data is output data obtained after the second training data is input into the power amplifier; training the second digital predistortion model according to the second training data and the second feedback data, to obtain second model coefficients corresponding to the trained second digital predistortion model; A second digital predistortion lookup table is generated according to the second model coefficients. 5. The digital predistortion method according to claim 1, wherein the first time period is the time period between the initial moment of the signal to be transmitted and the time when the power amplifier reaches a stable working state, so The second time period is a time period between the time when the power amplifier reaches a stable working state and the end time of the signal to be sent. 6. The digital pre-distortion method according to claim 1, wherein, within the first time period, digital pre-distortion is performed on the signal to be transmitted according to a first digital pre-distortion look-up table, and it is determined that the signal to be transmitted is The first digital predistortion output of the sending signal within the first time period includes: Determine the first digital predistortion output according to the following formula: Wherein, y ₁ (n) is the first digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT1 _m,k (|x(nk)| is the first digital A predistortion lookup table, M and K are memory depths, t _d is the end moment of the first time period, and Fs is a sampling rate. 7. The digital pre-distortion method according to claim 1, characterized in that, within the second time period, the signal to be transmitted is digitally pre-distorted according to a second digital pre-distortion look-up table, and the signal to be transmitted is determined to be The second digital predistortion output of the sending signal within the second time period includes: The second digital predistortion output is determined according to the following formula: Wherein, y ₂ (n) is the second digital predistortion output, x(nm) is the mth order delay of the signal to be transmitted, LUT2 _m,k (|x(nk)| is the second digital A predistortion lookup table, M and K are the memory depth, _td is the end moment of the first time period, T is the duration of the signal to be sent, and Fs is the sampling rate. 8. A digital predistortion device, characterized in that, comprising: An acquisition module, configured to acquire a signal to be sent; The first pre-distortion module is configured to perform digital pre-distortion on the signal to be transmitted according to a first digital pre-distortion lookup table within a first time period, and determine the first time period of the signal to be transmitted within the first time period a digital predistortion output; The second pre-distortion module is configured to perform digital pre-distortion on the signal to be transmitted according to a second digital pre-distortion look-up table within a second time period, and determine the first position of the signal to be transmitted within the second time period Two digital predistortion outputs. 9. An electronic device, characterized in that, comprising: a processor, a memory, and a bus; the processor and the memory complete mutual communication through the bus; the memory stores information that can be executed by the processor program instructions, and the processor can execute the method according to any one of claims 1-7 by calling the program instructions. 10. A computer-readable storage medium, characterized in that computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are read and run by a computer, any one of claims 1-7 is executed. method described in the item.