A digital predistortion method and device

Abstract

The embodiment of the present application discloses a digital predistortion method and device, wherein the digital predistortion device may include a transmitting module, a feedback link, and a coefficient iteration module; the transmitting module is used to receive a first input signal for nonlinear predistortion and power amplification, and output a first output signal; the feedback link is used to receive the first output signal and output a second output signal; the coefficient iteration module is used to obtain residual value energy based on the first input signal and the second output signal; and the coefficient configuration in the transmitting module is determined according to a plurality of residual value energies. The present application can maintain accurate matching of the model in the transmitting module.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a digital predistortion method and device. Background Art

[0002] In wireless communication systems, as the demand for device transmission power continues to increase, the requirements for low power consumption and high performance are also getting higher and higher. A common method used in the industry is to achieve system performance and low power consumption through matching work between digital pre-distortion (DPD) and power amplifier (PA).

[0003] The key to DPD technology is to obtain accurate nonlinear pre-distortion for the nonlinear distortion of the PA, that is, to perform nonlinear pre-distortion on the PA by matching the DPD nonlinear model with the PA nonlinear model.

[0004] In actual applications, PA module hardware batches, hardware individuals, high and low temperatures, aging, etc. are all different, making it difficult to ensure that the nonlinear model of the DPD model and the PA model are accurately matched. How to always maintain an accurate match of the nonlinear model to achieve communication system performance while reducing power consumption is a problem that needs to be solved. Summary of the invention

[0005] The embodiments of the present application provide a digital predistortion method and device, which achieve accurate matching of nonlinear models in the digital predistortion device, so that the communication system can reduce power consumption while ensuring performance.

[0006] In a first aspect, an embodiment of the present application provides a digital predistortion device, which includes a transmitting module, a feedback link, and a coefficient iteration module coupled to the transmitting module and the feedback link; the transmitting module is used to receive a first input signal, and then output a first output signal after performing nonlinear predistortion on the first input signal; the feedback link is used to receive the first output signal, and then output a second output signal; the coefficient iteration module is used to: obtain an error signal based on the first input signal and the second output signal, the error signal including nonlinear distortion residual and noise after nonlinear predistortion; perform autocorrelation calculation based on the error signal to obtain residual value energy, and the residual value energy is used to indicate the nonlinear predistortion effect of the transmitting module; the coefficient iteration module is also used to: determine the coefficient configuration in the transmitting module based on the multiple residual value energies obtained, and the multiple residual value energies are obtained by the coefficient iteration module based on the transmitting module receiving the first input signal multiple times. In the embodiment of the present application, when the digital pre-distortion device is used, since the nonlinear pre-distortion effect of the transmitting module can be directly indicated by the residual value energy, it is no longer necessary to use a single board connected to a spectrum analyzer to observe the nonlinear pre-distortion effect; when the transmitting module has differences due to hardware batches, hardware individuals, high and low temperatures, aging, etc., the digital pre-distortion device can also adaptively adjust the model of the transmitting module through the coefficient iteration module, so as to achieve accurate matching of the nonlinear model. In summary, the digital pre-distortion device in the embodiment of the present application can be separated from the laboratory or the spectrum analyzer, and even after the equipment path has differences due to hardware batches, hardware individuals, high and low temperatures, aging, etc., it can also adaptively perform accurate matching of the nonlinear model, so as to achieve the purpose of ensuring performance and reducing power consumption.

[0007] In combination with the first aspect, in some possible implementations, the coefficient iteration module specifically includes: aligning the first input signal with the second output signal, obtaining an error signal based on the alignment result, the alignment specifically includes eliminating the difference between the first input signal and the second output signal, and the difference may include one or more of phase, delay or amplitude; and obtaining residual value energy based on the error signal by using an autocorrelation calculation method. In the embodiment of the present application, since noise is introduced after the signal passes through the feedback link, this noise is usually relatively large, which makes it difficult to directly observe nonlinear distortion from the feedback link output. Therefore, the embodiment of the present application aligns the first input signal with the second output signal through a coefficient iteration module, obtains an error signal based on the alignment result, and uses autocorrelation calculation; wherein, the autocorrelation calculation can analyze the periodic components (i.e., the nonlinear distortion residual in the embodiment of the present application) and the noise components in the signal, because when the coefficients of the nonlinear model of the DPD module in the digital pre-distortion device have not changed, the nonlinear distortion residual of the device is the same, so the nonlinear distortion residual in the error signal is unchanged, but the noise will change all the time, so the coefficient iteration module can use autocorrelation calculation to analyze the nonlinear distortion residual and noise components in the signal, thereby removing the influence of noise to obtain the residual value energy, which is beneficial for the subsequent coefficient iteration module to judge the matching degree of the nonlinear model through the residual value energy.

[0008] In combination with the first aspect, in some possible implementations, the transmitting module includes: a digital predistortion DPD module and a power amplifier PA; the digital predistortion DPD module is used to receive a first input signal, and after performing nonlinear predistortion on the first input signal through a first nonlinear model, output a third output signal; the power amplifier PA is used to receive the third output signal, and after performing power amplification on the third output signal through a second nonlinear model, output the first output signal, and the first nonlinear model is the inverse model of the second nonlinear model. Since the power amplifier PA will produce nonlinear distortion when working close to the saturation point, it will have an adverse effect on the useful signal, reduce the spectral efficiency of the system, and affect the performance index of the transmitting antenna. Therefore, in the embodiment of the present application, the transmitting module performs appropriate nonlinear predistortion on the signal before the signal is input to the power amplifier PA to offset the nonlinear distortion caused by the PA, thereby improving the overall linearity of the system, wherein the nonlinear characteristics of the PA are represented by the second nonlinear model. Specifically, in order to perform nonlinear predistortion on the PA, the transmitting module in the embodiment of the present application adopts a DPD module, and the DPD module adopts a first nonlinear model, and the first nonlinear model is the inverse model of the second nonlinear model. The DPD module is specifically used to introduce distortion opposite to the nonlinear distortion of the PA before the signal (i.e., the first input signal) enters the PA, so that the output of the PA (i.e., the first output signal) can achieve signal linearization. The above implementation method can significantly improve the linearity of the power amplifier PA while maintaining a high efficiency.

[0009] In combination with the first aspect, in some possible implementations, the second nonlinear model used by the digital predistortion DPD module includes multiple memory items and a memory item combination; the coefficient iteration module is also used to: before the digital predistortion DPD module receives the first input signal, determine a target memory item from the multiple memory items, the target memory item is a memory item outside the memory item combination; perform coefficient fitting on the determined target memory item and the memory item combination, and update the first nonlinear model of the digital predistortion DPD module based on the result of the coefficient fitting. In the embodiment of the present application, the coefficient iteration module determines a target memory item from the multiple memory items and performs coefficient fitting on the memory item combination, and updates the first nonlinear model in the DPD module with the coefficient fitting result. Among them, multiple memory items represent all memory items within the value range of the second nonlinear model. The value range of the memory items is not fixed, but depends on multiple factors, such as the nonlinear characteristics of the power amplifier, signal bandwidth, system requirements, and the complexity of the selected model; the memory item combination is composed of one or more memory items, and the memory item combination is used to find a final memory item combination by continuously updating the memory items in the combination. The corresponding coefficients of the final memory item combination after coefficient fitting can make the digital predistortion DPD model and the power amplifier PA model achieve accurate matching, wherein the initial memory item combination is empty. The coefficient iteration module selects different target memory items and memory item combinations for coefficient fitting to obtain the digital predistortion DPD module under different coefficient configurations, which is conducive to the subsequent search for the memory item with the best nonlinear predistortion effect among multiple memory items.

[0010] In combination with the first aspect, in some possible implementations, the number of memory items other than the memory item combination in the multiple memory items is set to X; the coefficient iteration module is also used to: determine the target memory item X times from the multiple memory items, repeat the coefficient fitting X times, obtain X coefficient fitting results, and update the X updated first nonlinear models based on the results of the X coefficient fitting. In the embodiment of the present application, in the process of repeating the coefficient fitting X times, the target memory item determined each time is different, that is, the memory items other than the X memory item combination are selected once and the memory item combination is combined to perform coefficient fitting; after each coefficient fitting, the first nonlinear model is updated once. By traversing all the memory items once, all possible coefficient fitting results of the current memory item combination and the target memory item can be listed, and the digital pre-distortion DPD module under the corresponding coefficient configuration is conducive to the subsequent finding of the digital pre-distortion DPD module coefficient configuration, so that the DPD is accurately matched with the nonlinear model of the PA.

[0011] In combination with the first aspect, in some possible implementations, the digital pre-distortion DPD module is specifically used to receive the first input signal X times, and each time the first input signal is received, the first input signal is subjected to a nonlinear pre-distortion through the corresponding updated first nonlinear model, and the third output signal is output X times; the power amplifier PA is specifically used to receive the third output signal X times, and each time the third output signal is received, the third output signal is subjected to a power amplification, and the first output signal is output X times; the feedback link is specifically used to receive the first output signal X times, and output the second output signal X times. In the embodiment of the present application, after each update of the first nonlinear model is completed, the first input signal is subjected to a nonlinear pre-distortion based on the updated digital pre-distortion DPD module, and the second output signal of the corresponding feedback link is obtained. After repeating the above process X times, the digital pre-distortion DPD module corresponding to the current memory items and the memory item combination coefficients after fitting is obtained, and the input of the DPD module corresponding to the digital pre-distortion DPD module and the output of the feedback link when the digital pre-distortion DPD module is used are obtained for the subsequent calculation of the residual value energy.

[0012] In combination with the first aspect, in some possible implementations, the coefficient iteration module is further used to obtain X residual value energies based on the X times of the first input signal and the X times of the second output signal through signal alignment and autocorrelation calculation; determine the memory item corresponding to the minimum residual value energy item among the X residual value energies, and add the corresponding memory item to the memory item combination to update the memory item combination. In the embodiment of the present application, by comparing the residual value energies corresponding to the X memory items, the memory item with the minimum residual value energy, that is, the best nonlinear pre-distortion effect, is added to the memory item combination, that is, through the above method, the memory item added to the memory item combination each time is the memory item with the best nonlinear pre-distortion effect (that is, the minimum residual value energy).

[0013] In combination with the first aspect, in some possible implementations, the coefficient iteration module is also used to: repeatedly update the memory item combination multiple times until the current updated memory item combination reaches a preset value or the corresponding residual value energy meets the performance requirements; the coefficient iteration module determines the current updated memory item combination as the final memory item combination, and configures the digital predistortion DPD module based on the coefficient fitting result corresponding to the final memory item combination. In the embodiment of the present application, each time the memory item combination is updated, the value of X (that is, the number of memory items other than the memory item combination in multiple memory items) will decrease, because the update of the memory item combination is to add a memory item that needs to be traversed to the memory item combination, and each repetition will perform coefficient fitting on the X target memory items and the updated memory item combination. In this way, the final memory item combination can be obtained, and the coefficient fitting result corresponding to the final memory item combination can enable the DPD model to achieve an accurate match with the nonlinear model of the PA.

[0014] In combination with the first aspect, in some possible implementations, the transmitting module may further include: a digital-to-analog converter, a low-pass filter, and an up-conversion module; the digital-to-analog converter is used to receive the third output signal and convert the digital signal into an analog signal, and output the signal to the low-pass filter; the low-pass filter is used to receive the output signal of the digital-to-analog converter and filter the signal, and output the signal to the up-conversion module; the up-conversion module is used to receive the output signal of the low-pass filter and increase the signal frequency from a low frequency band to a high frequency band, and output the signal to the power amplifier PA. In the embodiment of the present application, the transmitting module may include a variety of circuit structures, and the components or modules in the transmitting module may be designed according to different application scenarios and circuit requirements.

[0015] In combination with the first aspect, in some possible implementations, the feedback link may include: a down-conversion module, a low-pass filter, and an analog-to-digital converter; the down-conversion module is used to receive the first output signal and reduce the signal frequency from the high frequency band to the low frequency band, and output the signal to the low-pass filter; the low-pass filter is used to receive the output signal of the down-conversion module to filter the signal, and output the signal to the analog-to-digital converter; the analog-to-digital converter is used to receive the output of the low-pass filter and convert the analog signal into a digital signal, and output the second output signal. In the embodiment of the present application, the feedback link may include a variety of circuit structures, and the components or modules in the transmitting module can be designed according to different application scenarios and circuit requirements.

[0016] In combination with the first aspect, when the residual value energy meets the performance requirements, the fewer the number of memory items in the memory item combination, the smaller the complexity of the first nonlinear model of the digital pre-distortion DPD module. In the embodiment of the present application, an increase in the number of memory items will increase the complexity of the digital pre-distortion DPD model, thereby increasing the amount of calculation and resource consumption; when the performance requirements are met, by reducing the number of memory items in the memory item combination, the amount of calculation and resource consumption of the device can be effectively reduced.

[0017] In combination with the first aspect, in some possible implementations, the first input signal received by the digital pre-distortion DPD module is a cyclic data source. In an embodiment of the present application, when training a model (including the first nonlinear model or the second nonlinear model described above), a feedback link is required to count multiple sample point data during sampling. Because the coefficient iteration module requires input and output data at the sampling point time and input and output data after the corresponding time delay when performing autocorrelation calculation, optionally, the first input signal can use a cyclic data source at this time. Among them, the cyclic data source can be specifically continuous and repeated signal transmission, that is, the signal received by the digital pre-distortion device is repeated each time. When the coefficient of the nonlinear model of the DPD module in the digital pre-distortion device has not changed, the nonlinear distortion residual of the device is the same, and the noise introduced in the device each time may be different. Therefore, the coefficient iteration module in the digital pre-distortion device can obtain multiple error signals based on the cyclic data source, and the multiple error signals include the same nonlinear distortion residual and different noises. Subsequently, the coefficient iteration module can perform autocorrelation calculation based on multiple error signals to remove the influence of noise and obtain residual value energy.

[0018] In a second aspect, an embodiment of the present application provides a digital predistortion method, which can be applied to a digital predistortion device, wherein the digital predistortion device includes: a transmitting module, a feedback link, and a coefficient iteration module coupled to the transmitting module and the feedback link, and the method includes: receiving a first input signal through the transmitting module, performing nonlinear predistortion and power amplification, and outputting a first output signal; receiving the first output signal through the feedback link, and outputting a second output signal; obtaining an error signal based on the first input signal and the second output signal through the coefficient iteration module, the error signal including the nonlinear distortion residual and noise after the nonlinear predistortion; performing autocorrelation calculation based on the error signal to obtain residual value energy, the residual value energy being used to indicate the nonlinear predistortion effect of the transmitting module; determining the coefficient configuration in the transmitting module based on multiple residual value energies, the multiple residual value energies being obtained based on the transmitting module receiving the first input signal multiple times.

[0019] In combination with the second aspect, in some possible implementations, obtaining the error signal based on the first input signal and the second output signal through the coefficient iteration module includes: aligning the first input signal and the second output signal, and obtaining the error signal based on a result of the alignment, wherein the alignment includes: eliminating the difference between the first input signal and the second output signal, wherein the difference includes one or more of phase, time delay or amplitude; and obtaining the residual value energy by using autocorrelation calculation based on the error signal.

[0020] In conjunction with the second aspect, in some possible implementations, the transmitting module includes: a digital predistortion DPD module and a power amplifier PA. The first input signal is received through the DPD module, the first input signal is subjected to the nonlinear predistortion using a first nonlinear model, and a third output signal is output; the third output signal is received through the PA, the third output signal is subjected to the power amplification using a second nonlinear model, and the first output signal is output, wherein the first nonlinear model is an inverse model of the second nonlinear model.

[0021] In combination with the second aspect, the second nonlinear model includes multiple memory items and memory item combinations, and the memory item combination is composed of one or more memory items from the multiple memory items. The method also includes: before receiving the first input signal through the DPD module, determining a target memory item from the multiple memory items, and the target memory item is a memory item other than the memory item combination; performing coefficient fitting on the target memory item and the memory item combination through a coefficient iteration module, and updating the first nonlinear model based on the result of the coefficient fitting.

[0022] In conjunction with the second aspect, in some possible implementations, the number of memory items in the multiple memory items other than the memory item combination is X. The method further includes: determining the target memory item X times from the multiple memory items through a coefficient iteration module, repeating the coefficient fitting X times to obtain X coefficient fitting results, and updating based on the X coefficient fitting results to obtain X updated first nonlinear models.

[0023] In combination with the second aspect, in some possible implementations, the receiving the first input signal through the DPD module, performing the nonlinear predistortion on the first input signal using the first nonlinear model, and outputting the third output signal includes: receiving the first input signal X times through the DPD module, performing the nonlinear predistortion on the first input signal once according to the updated first nonlinear model each time the first input signal is received, and outputting the third output signal X times; the receiving the third output signal through the PA, performing the power amplification on the third output signal using the second nonlinear model, and outputting the first output signal includes: receiving the third output signal X times through the PA, performing the power amplification on the third output signal once each time the third output signal is received, and outputting the first output signal X times; the receiving the first output signal through the feedback link and outputting the second output signal includes: receiving the first output signal X times through the feedback link, and outputting the second output signal X times.

[0024] In combination with the second aspect, in some possible implementations, the method further includes: calculating, through a coefficient iteration module, X residual value energies based on the X times the first input signal and the X times the second output signal; determining a memory item corresponding to a minimum residual value energy item among the X residual value energies; and adding the corresponding memory item to the memory item combination to update the memory item combination.

[0025] In combination with the second aspect, in some possible implementations, the method also includes: repeatedly updating the memory item combination multiple times through a coefficient iteration module until the currently updated memory item combination reaches a preset value or the corresponding residual value energy meets the performance requirements; determining the currently updated memory item combination as the final memory item combination, and configuring the digital predistortion DPD module based on the coefficient fitting result corresponding to the final memory item combination.

[0026] In combination with the second aspect, in some possible implementations, the transmitting module includes: a digital-to-analog converter, a low-pass filter and an up-conversion module, and the method also includes: receiving the third output signal through the digital-to-analog converter and converting the digital signal into an analog signal, and outputting the signal to the low-pass filter; receiving the output signal of the digital-to-analog converter through the low-pass filter and filtering the signal, and outputting the signal to the up-conversion module; receiving the output signal of the low-pass filter through the up-conversion module and increasing the signal frequency from a low frequency band to a high frequency band, and outputting the signal to the power amplifier PA.

[0027] In combination with the second aspect, in some possible implementations, the feedback link includes: a down-conversion module, a low-pass filter and an analog-to-digital converter, and the method also includes: receiving the first output signal through the down-conversion module and reducing the signal frequency from a high frequency band to a low frequency band, and outputting the signal to the low-pass filter; receiving the output signal of the down-conversion module through the low-pass filter and filtering the signal, and outputting the signal to the analog-to-digital converter; receiving the output signal of the low-pass filter through the analog-to-digital converter and converting the analog signal into a digital signal, and outputting the second output signal.

[0028] In combination with the second aspect, in some possible implementations, when the residual value energy meets the performance requirements, the fewer the number of memory items in the memory item combination, the smaller the complexity of the first nonlinear model of the digital predistortion DPD module.

[0029] In conjunction with the second aspect, in some possible implementations, the first input signal includes a cyclic data source.

[0030] In a third aspect, an embodiment of the present application provides a transmitter, comprising an antenna and a digital predistortion device as described in any one of the first aspects above.

[0031] In a fourth aspect, an embodiment of the present application provides a chip system, the chip system including a processor, configured to support a digital pre-distortion device to implement any method of the second aspect.

[0032] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. The computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes a method as described in any one of the second aspects. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the background technology, the drawings required for use in the embodiments of the present application or the background technology will be described below.

[0034] Figure 1 is a structural schematic diagram of a digital predistortion device provided in an embodiment of the present application;

[0035] Figure 2 is a structural schematic diagram of another digital predistortion device provided in an embodiment of the present application;

[0036] Figure 3 is a structural schematic diagram of another digital predistortion device provided in an embodiment of the present application;

[0037] Figure 4 It is a flow chart of a residual value energy acquisition method provided in an embodiment of the present application;

[0038] Figure 5 is a flow chart of a method for obtaining digital predistortion coefficients provided in an embodiment of the present application;

[0039] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The terms used in the following application embodiments of the present application are only for the purpose of describing specific application embodiments and are not intended to limit the present application.

[0041] First, some terms in this application are explained to facilitate understanding by those skilled in the art.

[0042] (1) A power amplifier (PA) is an electronic device whose main function is to generate maximum power output to drive a load (such as speakers, headphones, RF transmitters, etc.) under given conditions.

[0043] (2) Digital pre-distortion (DPD) is a technology used to suppress the nonlinear distortion of power amplifiers (PAs). Its basic principle is to insert a pre-distortion module before the signal is input to the power amplifier and appropriately modulate the input signal to offset the nonlinear distortion caused by the power amplifier, thereby improving the overall performance of the system.

[0044] (3) Generalized memory polynomials (GMP) is a memory model that is a simplified power amplifier behavior model based on the Volterra Series Model (VSM). It has the characteristics of multiple variables and can retain a certain time offset term, thereby enhancing the memory effect while keeping the computational complexity not too high, making the model performance better.

[0045] (4) Memory depth refers to the number of past time points or steps that a memory model can take into account when describing a system or process. It determines the length of historical data that the model needs to consider when building a model. Specifically, the greater the memory depth, the more system dynamic characteristics the model can capture, but it also means that the complexity and computational effort of the model will increase.

[0046] (5) Memory terms usually refer to those terms that take into account the impact of signal history or past states on current output. These terms reflect the impact of the system’s input at different time points on the current output, thereby simulating the system’s memory effect.

[0047] (6) Autocorrelation calculation is an important and commonly used method in signal processing, which is mainly used to describe the correlation between a signal and itself at different time points.

[0048] First, in order to facilitate understanding of the embodiments of the present application, the technologies that may be used to solve the technical problems in the present application are further analyzed. In wireless communication systems, as the transmission power requirements of devices continue to increase, the requirements for low power consumption and high performance are also getting higher and higher. The digital pre-distortion DPD model and the power amplifier PA matching work to achieve the purpose of excellent system performance and low power consumption is a method commonly used in the industry.

[0049] The power amplifier PA must ensure the transmission power when transmitting signals and will work in a nonlinear region, thus causing nonlinear distortion of the signal. In order to solve the nonlinear distortion problem, a digital predistortion DPD model is used.

[0050] The digital pre-distortion (DPD) model is an effective method for improving the linearity of power amplifiers (PAs). In wireless communication systems, the nonlinear characteristics of the power amplifiers themselves will cause distortion of the signal during transmission, affecting system performance. Digital pre-distortion technology pre-processes the signal before it is input into the power amplifier, i.e., nonlinear pre-distortion, to offset the nonlinear distortion caused by the power amplifier, thereby improving the overall performance of the system.

[0051] Exemplarily, the digital predistortion DPD model is an inverse model of the power amplifier PA model. The generalized memory polynomial model shown below is one of the most widely used nonlinear models currently:

[0052]

[0053] Where y is the output signal of the power amplifier PA, x(n) is the input signal of the power amplifier PA, m1 represents the signal memory term, m2 represents the modulus memory term, p represents the nonlinear order, M1 represents the memory depth, M2 represents the modulus memory depth, c m 1 ,m 2 ,p is the coefficient of the memory item whose parameter value combination is m1, m2, p. For example, y in the above formula (1) is the first output signal in the embodiment of the present application, x(n) is the third output signal in the embodiment of the present application, and m1, m2, p are the memory items in the embodiment of the present application.

[0054] For example, in actual engineering implementation, a lookup table is usually used to reduce the complexity and cost of digital predistortion DPD compensation. The formula is as follows:

[0055]

[0056] Wherein, y is the output signal of the power amplifier PA, x(n) is the input signal of the power amplifier PA, m1 represents the signal memory item, m2 represents the module memory item, M1 represents the memory depth, M2 represents the module memory depth, and F() represents the lookup table. Exemplarily, y in the above formula (2) is the first output signal in the embodiment of the present application, x(n) is the third output signal in the embodiment of the present application, and m1 and m2 are the memory items in the embodiment of the present application.

[0057] The above method is one of the nonlinear models used to represent the power amplifier PA in this application, and the nonlinear model also includes: memorize polynomials (MP), Volterra Series Model (VSM) and other models. In the following application embodiments, the above generalized memory polynomial is used as an example for description.

[0058] The specific structure and function of the digital predistortion device are introduced below. The digital predistortion device provided by this application is intended to solve the problem that the matching degree between the digital predistortion DPD model and the power amplifier PA model is reduced due to the power amplifier PA hardware batch, hardware individual, high and low temperature, aging, etc., and ensure that the digital predistortion DPD model and the power amplifier PA model maintain accurate matching.

[0059] Figure 1 A schematic diagram of the structure of a digital pre-distortion device is provided for an embodiment of the present application. Figure 1 As shown, the digital predistortion device 100 may include: a transmitting module 101 , a feedback link 104 , and a coefficient iteration module 105 .

[0060] The transmitting module 101 is used to perform nonlinear predistortion and power amplification on a received first input signal, and output a first output signal; the feedback link 104 is used to receive the first output signal, and output a second output signal;

[0061] The feedback link 104 is used to receive the first output signal and output a second output signal;

[0062] The coefficient iteration module 105 obtains an error signal based on the first input signal and the second output signal, wherein the error signal includes a nonlinear distortion residue and noise after the nonlinear predistortion; performs autocorrelation calculation based on the error signal to obtain residual value energy, wherein the residual value energy is used to indicate a nonlinear predistortion effect of the transmitting module;

[0063] The coefficient iteration module 105 is further used to determine the coefficient configuration in the transmitting module 101 according to the multiple residual value energies, where the multiple residual value energies are obtained by the coefficient iteration module based on the transmitting module 101 receiving the first input signal multiple times.

[0064] In the embodiment of the present application, when the digital pre-distortion device 100 is used, since the nonlinear pre-distortion effect of the transmitting module can be directly indicated by the residual value energy, it is no longer necessary to use a single board connected to a spectrum analyzer to observe the nonlinear pre-distortion effect; when the transmitting module 101 has differences due to hardware batches, hardware individuals, high and low temperatures, aging, etc., the digital pre-distortion device 100 can also adaptively adjust the model of the transmitting module through the coefficient iteration module 105, so as to achieve accurate matching of the nonlinear model. In summary, the digital pre-distortion device in the embodiment of the present application can be separated from the laboratory or the spectrum analyzer, and even after the equipment path has differences due to hardware batches, hardware individuals, high and low temperatures, aging, etc., it can also adaptively perform accurate matching of the nonlinear model, so as to achieve the purpose of ensuring performance and reducing power consumption.

[0065] Optionally, when training the nonlinear model in the transmitting module, the first input signal can use a cyclic data source, assuming that its cycle length is N. The cyclic data source refers to a data sequence that will start again from the beginning after reaching its end to form a closed loop, and its content is repeated and predictable, that is, the signal received by the digital pre-distortion device is repeated each time. When the coefficients of the nonlinear model of the DPD module in the digital pre-distortion device have not changed, the nonlinear distortion residual of the device is the same, and the noise introduced into the device each time may be different. Therefore, the coefficient iteration module in the digital pre-distortion device can obtain multiple error signals based on the cyclic data source, and the multiple error signals include the same nonlinear distortion residual and different noises. Subsequently, the coefficient iteration module can perform autocorrelation calculation based on the multiple error signals to remove the influence of noise and obtain residual value energy.

[0066] Optionally, in the process of receiving the first output signal, the feedback link 104 may further perform frequency reduction, filtering, and signal conversion on the received first output signal to output a second output signal.

[0067] Optionally, after the coefficient iteration module 105 receives the first input signal and the second output signal, when performing pre-distortion algorithm training, the coefficient iteration module 105 can perform multiple sets of sampling on the signal for subsequent autocorrelation calculation. At least M+N sample points are counted, where M is the number of sample points required for subsequent autocorrelation calculation, and N is the length of the cyclic data source, that is, the coefficient iteration module 105 needs to count the input and output data at M sample points and the corresponding input and output data after the corresponding sample point data completes one cycle.

[0068] In one possible implementation, the coefficient iteration module 105 is specifically used to: align the first input signal and the second output signal, and obtain the error signal based on the result of the alignment, wherein the alignment includes: eliminating the difference between the first input signal and the second output signal, wherein the difference includes one or more of phase, time delay or amplitude; and obtaining the residual value energy based on the error signal using autocorrelation calculation.

[0069] In an embodiment of the present application, in a digital predistortion device, since various delays such as circuit delays and processing delays are introduced during the transmission and processing of the signal, there will be a time difference between the input signal of the transmitting module (i.e., the first input signal) and the signal actually output by the feedback link (i.e., the second output signal). This time difference will seriously affect the predistortion effect and may even cause system performance to degrade. Therefore, it is necessary to eliminate this time difference through an alignment operation to ensure that the nonlinear distortion of the power amplifier can be accurately compensated. Because the noise introduced by the signal after passing through the feedback link is usually relatively large, it will result in the inability to directly observe the nonlinear distortion residual from the error signal, and the error signal includes the nonlinear distortion residual and noise. Exemplarily, the coefficient iteration module 105 performs autocorrelation to calculate the residual value energy size, and the specific formula is as follows:

[0070]

[0071] Wherein, paErrPwr is the residual value energy, M is the number of samples, m is the sample time, N is the length of the cyclic data source, awgn is the noise value, fbErr is the error signal, and paErr is the nonlinear distortion residual. Exemplarily, paErrPwr in the above formula (3) is the residual value energy in the embodiment of the present application, awgn is the noise introduced in the embodiment, fbErr is the error signal in the embodiment, and paErr is the nonlinear distortion residual in the embodiment of the present application.

[0072] In the embodiment of the present application, autocorrelation calculation is a method of measuring the similarity or correlation between a signal and itself at different time delays. By calculating the autocorrelation function of the signal, the periodic components (i.e., the nonlinear distortion residual in the embodiment of the present application) and the noise components in the signal can be analyzed. Since the autocorrelation function of noise usually has a faster decay characteristic, the periodic components in the signal will form an obvious peak in the autocorrelation function. Therefore, this characteristic can be used to distinguish between signals and noise.

[0073] In one possible implementation, Figure 2 As shown, the transmitting module 101 may specifically include a digital predistortion DPD module 102 and a power amplifier PA103, wherein the digital predistortion DPD module 102 is used to receive a first input signal, perform nonlinear predistortion on the first input signal through a first nonlinear model, and output a third output signal to the power amplifier PA103; the power amplifier PA103 is used to receive a third output signal, perform power amplification on the third output signal through a second nonlinear model, and output the first output signal.

[0074] In the embodiment of the present application, when the power amplifier PA103 works near the saturation point, nonlinear distortion will be generated, which will have an adverse effect on the useful signal, reduce the spectral efficiency of the system, and affect the performance index of the transmitting antenna. Therefore, the transmitting module 101 performs appropriate nonlinear pre-distortion on the signal before the signal is input to the power amplifier PA103 to offset the nonlinear distortion caused by the power amplifier PA103, thereby improving the overall linearity of the system, wherein the nonlinear characteristics of the power amplifier PA103 are represented by the second nonlinear model. Specifically, in order to compensate for the nonlinear distortion caused by the power amplifier PA103, a digital predistortion DPD module 102 is used in the transmitting module in the embodiment of the present application, and the digital predistortion DPD module 102 adopts a first nonlinear model, which is an inverse model of the second nonlinear model. The digital predistortion DPD module 102 is specifically used to introduce a distortion opposite to the nonlinear distortion of the power amplifier PA103 before the signal (i.e., the first input signal) enters the power amplifier PA103, so that the output of the PA (i.e., the first output signal) realizes the linearization of the signal. The above implementation can significantly improve the linearity of the power amplifier PA103 while maintaining a high efficiency. Exemplarily, the second nonlinear model may include: memorize polynomials (MP), generalized memory polynomials (GMP), Volterra Series Model (VSM), etc. Optionally, the second nonlinear model is represented by a generalized memory polynomial, then the memory item combination optimization refers to searching for the best combination of m1 and m2 in the above formula (2) to achieve accurate matching between the digital predistortion DPD module 102 and the power amplifier PA103.

[0075] In a possible implementation, the coefficient iteration module 105 is also used to: determine a target memory item from the multiple memory items before the digital predistortion DPD module 102 receives the first input signal, and the target memory item is a memory item other than the memory item combination; perform coefficient fitting on the target memory item and the memory item combination, and update the first nonlinear model based on the result of the coefficient fitting.

[0076] In the embodiment of the present application, the coefficient iteration module 105 determines a target memory item from a plurality of memory items and performs coefficient fitting with the memory item combination, and updates the first nonlinear model in the digital predistortion DPD module 102 with the coefficient fitting result. Wherein, the plurality of memory items represent all memory items within the value range of the second nonlinear model, and the value range of the memory item is not fixed, but depends on multiple factors, such as the nonlinear characteristics of the power amplifier, the signal bandwidth, the system requirements, and the complexity of the selected model; the memory item combination is composed of one or more memory items, and the memory item combination is used to find a final memory item combination by continuously updating the memory items in the combination in the future. The corresponding coefficients after the coefficient fitting of the final memory item combination can make the digital predistortion DPD model and the power amplifier PA model achieve accurate matching, wherein the initial memory item combination is empty. The coefficient iteration module 105 selects different target memory items and memory item combinations for coefficient fitting, so as to obtain the digital predistortion DPD module 102 under different coefficient configurations, which is conducive to the subsequent search for the memory item with the best nonlinear predistortion effect among the plurality of memory items. Exemplarily, the coefficient fitting operation may include: constructing a model equation according to a selected nonlinear model (such as a memory polynomial, a generalized memory polynomial), assigning an initial value to each coefficient in the model according to a target memory item and a memory item combination. Solving the equation group uses a mathematical method to solve the above equation group, such as a least square method, a minimum mean square error method, etc., and after adjustment, obtains the specific value of the coefficient of the digital predistortion DPD module 102.

[0077] In a possible implementation, the number of memory items other than the memory item combination in the multiple memory items is X; the coefficient iteration module 105 is further used to: determine the target memory items X times from the multiple memory items, repeat the coefficient fitting X times to obtain X coefficient fitting results, and update based on the X coefficient fitting results to obtain X updated first nonlinear models.

[0078] In the embodiment of the present application, in the process of repeating the coefficient fitting X times, the target memory item determined each time is different, that is, the memory items other than the X memory item combinations are selected once and the memory item combination is combined for coefficient fitting; after each coefficient fitting, the first nonlinear model is updated once. By traversing all memory items once, all possible coefficient fitting results of the current memory item combination and the target memory item can be listed, and the digital predistortion DPD module 102 under the corresponding coefficient configuration can be used to find out the coefficient configuration of the digital predistortion DPD module 102 in the future, so that the DPD can be accurately matched with the nonlinear model of the PA.

[0079] In a possible implementation, the digital predistortion DPD module 102 is used to receive the first input signal X times, and each time the first input signal is received, perform a nonlinear predistortion on the first input signal according to the updated first nonlinear model, and output the third output signal X times;

[0080] The power amplifier PA103 is used to receive the third output signal X times, and each time the third output signal is received, the third output signal is power amplified once, and the first output signal is output X times; the feedback link 104 is used to receive the first output signal X times, and output the second output signal.

[0081] In the embodiment of the present application, after each update of the first nonlinear model is completed, the first input signal is nonlinearly predistorted based on the updated digital predistortion DPD module 102, and a second output signal corresponding to the feedback link 104 is obtained. After repeating the above process X times, the digital predistortion DPD module 102 corresponding to all current memory items and memory item combination coefficients after fitting is obtained, and the input of the digital predistortion DPD module 102 and the output of the feedback link 104 corresponding to the digital predistortion DPD module 102 when the digital predistortion DPD module 102 is used are obtained for subsequent calculation of residual value energy.

[0082] In a possible implementation, the coefficient iteration module 105 is further used to calculate X residual value energies based on the X times of the first input signal and the X times of the second output signal; determine the memory item corresponding to the minimum residual value energy item among the X residual value energies; and add the corresponding memory item to the memory item combination to update the memory item combination.

[0083] In the embodiment of the present application, by comparing the residual value energies corresponding to X memory items, the memory item with the smallest residual value energy, that is, the best nonlinear pre-distortion effect, is added to the memory item combination, so that the memory item added to the memory item combination is the memory item outside the memory item combination that has the greatest influence on the residual value energy. In this way, each time the memory item is added, the memory item with the best nonlinear pre-distortion effect (that is, the smallest residual value energy) in the current situation is added; then when the nonlinear pre-distortion performance requirements are met, the number of memory items in the memory item combination can be effectively reduced, thereby reducing the complexity of the nonlinear model in the DPD module, thereby reducing the amount of calculation and resource consumption of the device.

[0084] In a possible implementation, the coefficient iteration module 105 is further used to: repeatedly update the memory item combination multiple times until the currently updated memory item combination reaches a preset value or the corresponding residual value energy meets the performance requirements; determine the currently updated memory item combination as the final memory item combination, and configure the digital predistortion DPD module 102 based on the coefficient fitting result corresponding to the final memory item combination.

[0085] In the embodiment of the present application, each time the memory item combination is updated, the value of X (i.e., the number of memory items other than the memory item combination in the multiple memory items) will decrease, because the update of the memory item combination is to add a memory item that needs to be traversed to the memory item combination, and each repetition will fit the coefficients of the X target memory items with the updated memory item combination; the update is repeated until the current updated memory item combination reaches the preset value or the corresponding residual value energy meets the performance requirements, and the final memory item combination is obtained and the corresponding coefficient fitting result is configured to the digital predistortion DPD module 102. Among them, according to the data processing capabilities of different devices, the number of memory item combinations has an upper limit. A preset value is set in the coefficient iteration module 105 to ensure that the obtained memory item combination does not exceed the data processing capability of the device. When the memory item combination reaches the preset value or the residual value energy indicates that the matching degree of the current DPD model and the PA model meets the performance requirements, the final memory item combination is obtained. The coefficient fitting result corresponding to the final memory item combination is configured in the DPD model, so as to achieve accurate matching between the DPD model and the PA model.

[0086] In one possible implementation, Figure 3 As shown, the transmitting module 101 may further include: a digital-to-analog converter 106 , an up-conversion module 107 , and a coupler 108 . Optionally, the feedback link 104 may include: a down-conversion module 109 , and an analog-to-digital converter 110 .

[0087] The digital-to-analog converter 106 is used to convert the output signal of the digital predistortion DPD module 102 from a digital signal to an analog signal. In a possible implementation, when the digital predistortion DPD module 102 processes a digital signal, the power amplifier PA103 receives an analog signal. Therefore, before the nonlinear predistorted signal is sent to the power amplifier PA103, the digital signal needs to be converted into an analog signal by the digital-to-analog converter 106.

[0088] The up-conversion module 107 is used to convert the low-frequency signal into a high-frequency signal. In a possible implementation, in the digital pre-distortion DPD module 102, the signal after nonlinear pre-distortion is a low-frequency signal, but the subsequent communication system needs to transmit the signal at a higher frequency. Therefore, the up-conversion module 107 converts the low-frequency signal after nonlinear pre-distortion into a high-frequency signal to meet the system transmission requirements.

[0089] The coupler 108 is used to output the output of the power amplifier PA103 to the down-conversion module 109 through the coupler 108. Specifically, the output signal of the power amplifier PA103 is coupled to the coupling port according to a preset ratio, that is, the output signal of the power amplifier PA103 couples part of its energy to the down-conversion module 109.

[0090] The down-conversion module 109 is used to convert the received high-frequency radio frequency signal into a lower-frequency intermediate frequency or baseband signal. In a possible implementation, the signal output by the power amplifier PA103 is a high-frequency radio frequency signal, which cannot be directly processed by the digital processing unit. Therefore, it is necessary to down-convert the signal to a frequency range suitable for digital processing through the down-conversion module 109.

[0091] The analog-to-digital converter 110 is used to convert the analog signal back into a digital signal and output it to the coefficient iteration module 105 so as to perform calculation and adjustment of the autocorrelation algorithm in the coefficient iteration module 105 .

[0092] See also Figure 4 , Figure 4 The present application provides a flowchart of a residual value energy acquisition method. Figure 4 As shown, the residual value energy acquisition method is applied to a digital predistortion device, and the digital predistortion device is the above Figure 2 to Figure 3 The structure shown in any of the application embodiments of the application embodiment. The digital predistortion device includes a digital predistortion DPD module, a power amplifier PA, a feedback link and a coefficient iteration module. After the signal is nonlinearly predistorted by the digital predistortion DPD module, there is still some nonlinear distortion after passing through the power amplifier PA. The residue of these nonlinear distortions is referred to as residual value energy in the following process, and the acquisition method includes the following steps:

[0093] S401 , sending a cyclic data source to a digital predistortion DPD module.

[0094] Specifically, the cyclic data source is sent as an input signal to the digital predistortion DPD module, and the digital predistortion DPD module performs nonlinear predistortion on the input signal to obtain the digital predistortion DPD module output signal. The power amplifier PA amplifies the output signal of the digital predistortion DPD module to obtain the output signal of the power amplifier PA. The output signal of the power amplifier PA passes through a feedback link, and the obtained feedback link is output to the coefficient iteration module.

[0095] S402: The coefficient iteration module receives an input signal of the digital predistortion DPD module and an output signal of the feedback link.

[0096] Specifically, the coefficient iteration module receives a digital predistortion DPD module input signal of at least M+N sample points and a feedback link output signal of the feedback link.

[0097] S403: Align the DPD module input signal with the feedback link output signal, and obtain an error signal based on the alignment result.

[0098] S404: Perform autocorrelation calculation according to the error signal to obtain residual value energy.

[0099] The above method can be used to obtain the nonlinear distortion residual in the PA output signal in the digital predistortion device, that is, the nonlinear predistortion effect of the transmitting module is indicated by the residual value energy. It should be noted that the various steps of the residual value energy acquisition method described in the embodiment of the present application can be referred to the above Figure 1-Figure 3 The relevant description in the device embodiment described in will not be repeated here.

[0100] See also Figure 5 , Figure 5 FIG. 1 is a flowchart of a method for obtaining digital predistortion coefficients provided by an embodiment of the present application. Figure 5 As shown, the method for obtaining digital predistortion coefficients is applied to a digital predistortion device, and the digital predistortion device is the above-mentioned Figures 2 to 3 The circuit shown in any one of the application embodiments of the present invention. The digital predistortion device includes a digital predistortion DPD module, a power amplifier PA, a feedback link and a coefficient iteration module. The digital predistortion coefficient acquisition method includes the following steps:

[0101] S501 , fitting coefficients of a memory item combination and a memory item other than the memory item combination, and configuring corresponding coefficients into a digital predistortion DPD module.

[0102] Specifically, the coefficient iteration module performs coefficient fitting on the memory item combination and a target memory item, and configures the corresponding coefficient into the digital predistortion DPD module, where the target memory item is a memory item other than the memory item combination.

[0103] S502, sending a circular data source and receiving an output.

[0104] Specifically, the cyclic data source is sent to the digital predistortion DPD module, and the digital predistortion DPD module performs nonlinear predistortion on the input signal to obtain a digital predistortion DPD module output signal.

[0105] Specifically, the cyclic data source is sent as an input signal to the digital predistortion DPD module, and the digital predistortion DPD module performs nonlinear predistortion on the input signal to obtain the digital predistortion DPD module output signal. The power amplifier PA amplifies the output signal of the digital predistortion DPD module to obtain the output signal of the power amplifier PA. The output signal of the power amplifier PA passes through a feedback link, and the obtained feedback link is output to the coefficient iteration module.

[0106] S503: After aligning the input and output, perform autocorrelation calculation to obtain residual value energy.

[0107] Specifically, the coefficient iteration module aligns the input signal of the digital predistortion DPD module with the output signal of the feedback link, and based on the error signal, performs autocorrelation calculation according to the error signal to obtain the residual value energy. Since various delays such as circuit delays and processing delays are introduced during the transmission and processing of the signal, there will be a time difference between the input signal of the predistortion circuit of the transmitting module (i.e., the first input signal) and the signal actually output by the feedback link (i.e., the second output signal). This time difference will seriously affect the predistortion effect and may even cause the system performance to deteriorate. Therefore, it is necessary to eliminate this time difference through alignment operations to ensure that the nonlinear distortion of the power amplifier can be accurately compensated.

[0108] S504, determining whether all memory items other than the memory item combination have been traversed.

[0109] Specifically, the coefficient iteration module determines whether all memory items other than all memory item combinations have been traversed. If not, the above operations S501 to S503 are repeated until all memory items other than all memory item combinations have been traversed; if yes, the following operations are then performed.

[0110] S505: Compare all traversed residual value energies, select the memory item corresponding to the minimum residual value energy and add it to the latest memory item combination.

[0111] S506: Determine whether the number of memory item combinations reaches a preset value or whether the residual value energy meets performance requirements.

[0112] Specifically, the coefficient iteration module determines whether the number of memory item combinations reaches a preset value or whether the residual value energy reaches the performance requirement. If neither of them can be reached, the above steps S501 to S505 are repeated until at least one of the requirements is met, and then S507 is executed.

[0113] S507 , generating a final memory item combination and configuring coefficients into a digital predistortion DPD module.

[0114] The above method can be used to obtain coefficients that can accurately match the nonlinear model of DPD and PA, thereby ensuring performance and reducing power consumption. It should be noted that the various steps of the method for obtaining digital predistortion coefficients described in the embodiment of the present application can be referred to in the above Figure 1-Figure 3 The relevant description in the device embodiment described in will not be repeated here.

[0115] Figure 6 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0116] The electronic device may include a processor 610, a memory 620, a universal serial bus (USB) interface 630, an antenna 1, an antenna 2, a mobile communication module 650, a wireless communication module 660, a sensor module 680, a display screen 694, etc. The sensor module 680 may include a pressure sensor 680A, a touch sensor 680K, etc.

[0117] It is to be understood that the structure illustrated in the embodiments of the present application does not constitute a specific limitation on the electronic device. In other embodiments of the present application, the electronic device may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0118] The processor 610 may include one or more processing units, for example, the processor 610 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated into one or more processors. The controller may generate an operation control signal according to the instruction opcode and the timing signal to complete the control of fetching and executing instructions. A memory may also be provided in the processor 610 for storing instructions and data.

[0119] In some application embodiments, the processor 610 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0120] Exemplarily, the processor 610 can couple the touch sensor 680K through the I2C interface, so that the processor 610 and the touch sensor 680K communicate through the I2C bus interface to realize the touch function of the electronic device. The processor 610 communicates with the Bluetooth module in the wireless communication module 660 through the UART interface to realize the Bluetooth function. The MIPI interface includes a display serial interface (DSI). The processor 610 and the display screen 694 communicate through the DSI interface to realize the display function of the electronic device. The GPIO interface can be configured by software. The GPIO interface can be configured as a control signal or as a data signal. The GPIO interface can also be configured as an I2C interface, an I2S interface, a UART interface, a MIPI interface, etc.

[0121] The USB interface 630 is an interface that complies with USB standard specifications, and may specifically be a Mini USB interface, a Micro USB interface, a USB Type C interface, etc. The USB interface 630 may be used to connect a charger to charge the electronic device, and may also be used to transmit data between the electronic device and a peripheral device.

[0122] It is understandable that the interface connection relationship between the modules illustrated in the embodiments of the present application is only a schematic illustration and does not constitute a structural limitation on the electronic device. In other embodiments of the present application, the electronic device may also adopt different interface connection methods in the above application embodiments, or a combination of multiple interface connection methods.

[0123] The wireless communication function of the electronic device can be implemented through antenna 1, antenna 2, mobile communication module 650, wireless communication module 660, modem processor and baseband processor.

[0124] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in the electronic device can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of the antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other application embodiments, the antenna can be used in combination with a tuning switch.

[0125] The mobile communication module 650 can provide solutions for wireless communications including 2G / 3G / 4G / 5G, etc., applied to electronic devices. The mobile communication module 650 may include at least one digital predistortion DPD module, a digital-to-analog converter, a low-pass filter, an up-converter, a power amplifier PA, a down-conversion module, a low-pass filter and an analog-to-digital converter, a coefficient iteration module, etc.

[0126] The mobile communication module 650 can receive a signal from the antenna 1, and the digital predistortion DPD module performs nonlinear predistortion on the received signal and then outputs it to the digital-to-analog converter. The digital-to-analog converter converts the digital signal into an analog signal and outputs it to the low-pass filter. The low-pass filter performs filtering and then outputs it to the up-converter. The up-converter increases the signal frequency from the low frequency band to the high frequency band and outputs it to the power amplifier PA. The power amplifier PA amplifies the signal. The down-conversion module receives the signal amplified by the power amplifier PA, reduces the signal frequency from the high frequency band to the low frequency band and outputs it to the low-pass filter. The low-pass filter performs filtering and then outputs it to the analog-to-digital converter. The analog-to-digital converter converts the analog signal into a digital signal and outputs it to the coefficient iteration module. The coefficient iteration module receives the signal multiple times and processes it to find an accurate match between the digital predistortion DPD model and the power amplifier PA model. The mobile communication module 650 can receive electromagnetic waves from the antenna 1, and performs the above-mentioned predistortion, signal conversion, filtering and amplification on the received electromagnetic waves, and transmits them to the modulation and demodulation processor for demodulation. The mobile communication module 650 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some application embodiments, at least some functional modules of the mobile communication module 650 can be set in the processor 610. In some application embodiments, at least some functional modules of the mobile communication module 650 can be set in the same device as at least some modules of the processor 610.

[0127] The modem processor may include a modulator and a demodulator. The modulator is used to modulate the low-frequency baseband signal to be sent into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After the low-frequency baseband signal is processed by the baseband processor, it is passed to the application processor. The application processor outputs a sound signal through an audio device, or displays an image or video through a display screen 694. In some application embodiments, the modem processor may be an independent device. In other application embodiments, the modem processor may be independent of the processor 610 and be set in the same device as the mobile communication module 650 or other functional modules.

[0128] The wireless communication module 660 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to electronic devices. In the embodiment of the present application, the wireless communication module 660 can be one or more devices integrating at least one communication processing module. The wireless communication module 660 may include at least one digital pre-distortion DPD module, a digital-to-analog converter, a low-pass filter, an up-converter, a power amplifier PA, a down-conversion module, a low-pass filter and an analog-to-digital converter, a coefficient iteration module, etc. The wireless communication module 660 can receive a signal from the antenna 2, and the digital pre-distortion DPD module performs nonlinear pre-distortion on the received signal and then outputs it to the digital-to-analog converter. The digital-to-analog converter converts the digital signal into an analog signal and outputs it to the low-pass filter. The low-pass filter performs filtering and then outputs it to the up-converter. The up-converter increases the signal frequency from the low frequency band to the high frequency band and outputs it to the power amplifier PA. The power amplifier PA amplifies the signal. The down-conversion module receives the signal amplified by the power amplifier PA, reduces the signal frequency from the high frequency band to the low frequency band and outputs it to the low-pass filter. The low-pass filter performs filtering and then outputs it to the analog-to-digital converter. The analog-to-digital converter converts the analog signal into a digital signal and outputs it to the coefficient iteration module. The coefficient iteration module receives the signal multiple times and processes it to find an accurate match between the digital pre-distortion DPD model and the power amplifier PA model. The wireless communication module 660 receives electromagnetic waves via the antenna 2, modulates the electromagnetic wave signal and performs filtering, and sends the processed signal to the processor 610. The wireless communication module 660 can also receive the signal to be sent from the processor 610, pre-distort, frequency modulate, amplify the signal, and convert it into electromagnetic waves for radiation through the antenna 2.

[0129] The electronic device implements the display function through a GPU, a display screen 694, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 694 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 610 may include one or more GPUs that execute program instructions to generate or change display information.

[0130] The display screen 694 is used to display images, videos, etc. The display screen 694 includes a display panel. The display screen 694 includes a display panel. The display panel can be a liquid crystal display (LCD). The display panel can also be made of an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a quantum dot light-emitting diode (QLED), etc. In some application embodiments, the electronic device may include 1 or N display screens 694, where N is a positive integer greater than 1.

[0131] The memory 620 may be used to store computer executable program codes, and the executable program codes may include instructions. The processor 610 executes various functional applications and data processing of the electronic device by running the instructions stored in the memory 620. The memory 620 may include a program storage area and a data storage area. In a specific implementation, the memory 620 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more disk storage devices, flash memory devices or other non-volatile solid-state storage devices.

[0132] The pressure sensor 680A is used to sense the pressure signal and can convert the pressure signal into an electrical signal. In some application embodiments, the pressure sensor 680A can be set on the display screen 694. When a touch operation is applied to the display screen 694, the electronic device detects the intensity of the touch operation according to the pressure sensor 680A. The electronic device can also calculate the touch position according to the detection signal of the pressure sensor 680A.

[0133] The touch sensor 680K is also called a "touch control device". The touch sensor 680K can be set on the display screen 694, and the touch sensor 680K and the display screen 694 form a touch screen, also called a "touch control screen". The touch sensor 680K is used to detect touch operations acting on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display screen 694. In some other application embodiments, the touch sensor 680K can also be set on the surface of the electronic device, which is different from the position of the display screen 694.

[0134] As used in the specification and the appended claims of the present application, the singular expressions "a", "an", "said", "above", "the" and "this" are intended to also include plural expressions, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more of the listed items. As used in the above-mentioned application embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrase "when determining..." or "if (stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "when (stated condition or event) is detected" or "in response to detecting (stated condition or event)", depending on the context.

[0135] In the above application embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0136] A person skilled in the art can understand that to implement all or part of the processes in the above-mentioned application embodiments, the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned application embodiments. The aforementioned storage medium includes: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

[0137] The embodiments of the present application are described in detail above. The principles and implementations of the present application are described in detail using specific examples herein. The description of the embodiments of the present application is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, according to the idea of ​​the present application, there will be changes in the specific implementation and application scope. In summary, the content of this specification should not be understood as limiting the present application.

Claims

1. A digital predistortion device, characterized in that: The digital predistortion device comprises a transmitting module, a feedback link, and a coefficient iteration module coupled to the transmitting module and the feedback link; The transmitting module is used to perform nonlinear predistortion and power amplification on the received first input signal, and output a first output signal; The feedback link is used to receive the first output signal and output a second output signal; The coefficient iteration module is used to: An error signal is obtained based on the first input signal and the second output signal, wherein the error signal includes a nonlinear distortion residue and noise after the nonlinear predistortion; a residual value energy is obtained by performing an autocorrelation calculation based on the error signal, wherein the residual value energy is used to indicate a nonlinear predistortion effect of the transmitting module; The coefficient iteration module is also used for: Determine the coefficient configuration in the transmitting module according to the plurality of residual value energies, wherein the plurality of residual value energies are obtained by the coefficient iteration module based on the transmitting module receiving the first input signal multiple times; The first input signal includes a cyclic data source, and a plurality of error signals are obtained corresponding to the currently received first input signal; the coefficient iteration module is specifically used for: Performing autocorrelation calculation based on the multiple error signals to remove the influence of noise and thereby obtain residual value energy corresponding to the current first input signal; According to the nonlinear pre-distortion effect indicated by the residual value energy corresponding to the current first input signal, the coefficients of the nonlinear model in the transmitting module are adjusted, and the residual value energy corresponding to the first input signal received next time is calculated based on the adjusted coefficients. The process is repeated until the nonlinear pre-distortion effect indicated by the adjusted residual value energy meets the standard, and the corresponding coefficients are determined as the coefficient configuration in the transmitting module.

2. The device according to claim 1, characterized in that The coefficient iteration module is specifically used for: Aligning the first input signal and the second output signal, and obtaining the error signal based on the alignment result, wherein the alignment includes: eliminating the difference between the first input signal and the second output signal, wherein the difference includes one or more of phase, delay or amplitude; The residual value energy is obtained by using the autocorrelation calculation based on the error signal.

3. The device according to claim 1, characterized in that The transmitting module includes: a digital pre-distortion DPD module and a power amplifier PA; The DPD module is used to: receiving the first input signal, performing the nonlinear predistortion on the first input signal through a first nonlinear model, and outputting a third output signal; The PA is used to: The third output signal is received, the power of the third output signal is amplified by a second nonlinear model, and the first output signal is output, wherein the first nonlinear model is an inverse model of the second nonlinear model.

4. The device according to claim 3, characterized in that The second nonlinear model includes a plurality of memory items and a memory item combination, wherein the memory item combination is composed of one or more memory items among the plurality of memory items; The coefficient iteration module is also used for: Before the DPD module receives the first input signal, determining a target memory item from the plurality of memory items, the target memory item being a memory item other than the memory item combination; The target memory item is combined with the memory item to perform coefficient fitting, and the first nonlinear model is updated based on the result of the coefficient fitting.

5. The device according to claim 4, characterized in that The number of memory items in the plurality of memory items other than the memory item combination is X, and the coefficient iteration module is further used for: Determine the target memory item X times from the multiple memory items, repeat the coefficient fitting X times to obtain X coefficient fitting results, and update to obtain X updated first nonlinear models based on the X coefficient fitting results.

6. The device according to claim 5, characterized in that The DPD module is specifically configured to receive the first input signal X times, and each time the first input signal is received, perform the nonlinear predistortion on the first input signal once by corresponding to the updated first nonlinear model, and output the third output signal X times; The PA is specifically configured to receive the third output signal X times, perform power amplification on the third output signal once each time the third output signal is received, and output the first output signal X times; The feedback link is specifically configured to receive the first output signal X times and output the second output signal X times.

7. The device according to claim 6, characterized in that The coefficient iteration module is also used for: Based on the X times of the first input signals and the X times of the second output signals, calculate and obtain X residual value energies; Determine a memory item corresponding to the minimum item of the residual value energy among the X residual value energies; The corresponding memory item is added to the memory item combination to update the memory item combination.

8. The device according to claim 7, characterized in that The coefficient iteration module is also used for: Repeat the updating of the memory item combination multiple times until the currently updated memory item combination reaches a preset value or the corresponding residual value energy meets the performance requirement; The currently updated memory item combination is determined as a final memory item combination, and the digital predistortion DPD module is configured based on a coefficient fitting result corresponding to the final memory item combination.

9. The device according to any one of claims 3 to 8, characterized in that: The transmitting module includes: a digital-to-analog converter, a low-pass filter and an up-conversion module; The digital-to-analog converter is used to receive the third output signal and convert the digital signal into an analog signal, and output the signal to the low-pass filter; The low-pass filter is used to receive the output signal of the digital-to-analog converter and filter the signal, and output the signal to the up-conversion module; The up-conversion module is used to receive the output signal of the low-pass filter and increase the signal frequency from a low frequency band to a high frequency band, and output the signal to the power amplifier PA.

10. The device according to any one of claims 1 to 8, characterized in that: The feedback link includes: a down-conversion module, a low-pass filter and an analog-to-digital converter; The down-conversion module is used to receive the first output signal and reduce the signal frequency from a high frequency band to a low frequency band, and output the signal to the low-pass filter; The low-pass filter is used to receive the output signal of the down-conversion module and filter the signal, and output the signal to the analog-to-digital converter; The analog-to-digital converter is used to receive the output signal of the low-pass filter and convert the analog signal into a digital signal, and output the second output signal.

11. The device according to any one of claims 4 to 8, characterized in that: When the residual value energy meets the performance requirement, the fewer the number of memory items in the memory item combination, the smaller the complexity of the first nonlinear model of the digital predistortion DPD module.

12. A digital predistortion method, characterized in that: Applied to a digital predistortion device, the digital predistortion device comprises: a transmitting module, a feedback link, and a coefficient iteration module coupled to the transmitting module and the feedback link, the method comprises: Performing nonlinear predistortion and power amplification on the received first input signal through the transmitting module, and outputting a first output signal; receiving the first output signal through the feedback link and outputting a second output signal; Obtaining an error signal based on the first input signal and the second output signal through the coefficient iteration module, wherein the error signal includes the nonlinear distortion residue and noise after the nonlinear predistortion; performing autocorrelation calculation based on the error signal to obtain residual value energy, wherein the residual value energy is used to indicate the nonlinear predistortion effect of the transmitting module; determining the coefficient configuration in the transmitting module according to a plurality of the residual value energies, wherein the plurality of the residual value energies are obtained based on the transmitting module receiving the first input signal multiple times; The first input signal includes a cyclic data source, and a plurality of error signals are obtained corresponding to the currently received first input signal; and determining the coefficient configuration in the transmitting module according to the plurality of residual value energies includes: Performing autocorrelation calculation based on the multiple error signals to remove the influence of noise and thereby obtain residual value energy corresponding to the current first input signal; According to the nonlinear pre-distortion effect indicated by the residual value energy corresponding to the current first input signal, the coefficients of the nonlinear model in the transmitting module are adjusted, and the residual value energy corresponding to the first input signal received next time is calculated based on the adjusted coefficients. The process is repeated until the nonlinear pre-distortion effect indicated by the adjusted residual value energy meets the standard, and the corresponding coefficients are determined as the coefficient configuration in the transmitting module.

13. The method according to claim 12, characterized in that The step of obtaining an error signal based on the first input signal and the second output signal through the coefficient iteration module includes: The error signal is obtained by aligning the first input signal and the second output signal based on the result of the alignment, wherein the alignment includes: eliminating a difference between the first input signal and the second output signal, wherein the difference includes one or more of a phase, a time delay or an amplitude; The residual value energy is obtained by using the autocorrelation calculation based on the error signal.

14. The method according to claim 12, characterized in that The transmitting module includes: a digital predistortion DPD module and a power amplifier PA; the method also includes: receiving the first input signal through the DPD module, performing the nonlinear predistortion on the first input signal using a first nonlinear model, and outputting a third output signal; The third output signal is received by the PA, the third output signal is power amplified by using a second nonlinear model, and the first output signal is output, wherein the first nonlinear model is an inverse model of the second nonlinear model.

15. The method according to claim 14, characterized in that The second nonlinear model includes a plurality of memory items and a memory item combination, wherein the memory item combination is composed of one or more memory items among the plurality of memory items, and the method further includes: Before receiving the first input signal through the DPD module, determining a target memory item from the plurality of memory items, the target memory item being a memory item other than the combination of memory items; The target memory item is combined with the memory item to perform coefficient fitting through the coefficient iteration module, and the first nonlinear model is updated based on the result of the coefficient fitting.

16. The method according to claim 15, characterized in that The number of memory items other than the memory item combination in the plurality of memory items is X; the method further includes: The target memory item is determined X times from the multiple memory items by the coefficient iteration module, the coefficient fitting is repeated X times to obtain X coefficient fitting results, and X updated first nonlinear models are updated based on the X coefficient fitting results.

17. The method according to claim 16, characterized in that The receiving the first input signal through the DPD module, performing the nonlinear predistortion on the first input signal using a first nonlinear model, and outputting a third output signal includes: receiving the first input signal X times through the DPD module, performing the nonlinear predistortion on the first input signal once by corresponding to the updated first nonlinear model each time the first input signal is received, and outputting the third output signal X times; Receiving the third output signal through the PA, performing the power amplification on the third output signal using a second nonlinear model, and outputting the first output signal comprises: receiving the third output signal X times through the PA, performing the power amplification on the third output signal once each time the third output signal is received, and outputting the first output signal X times; The receiving the first output signal through the feedback link and outputting the second output signal comprises: The first output signal is received X times through the feedback link, and the second output signal is output X times.

18. The method according to claim 17, characterized in that The method further comprises: Based on the X times of the first input signal and the X times of the second output signal, X residual value energies are calculated by the coefficient iteration module, and a memory item corresponding to the minimum residual value energy item among the X residual value energies is determined; and the corresponding memory item is added to the memory item combination to update the memory item combination.

19. The method according to claim 18, characterized in that The method further comprises: The updating of the memory item combination is repeated multiple times by the coefficient iteration module until the currently updated memory item combination reaches a preset value or the corresponding residual value energy meets the performance requirements; the currently updated memory item combination is determined as the final memory item combination, and the digital predistortion DPD module is configured based on the coefficient fitting result corresponding to the final memory item combination.

20. The method according to any one of claims 14 to 19, characterized in that: The transmitting module includes: a digital-to-analog converter, a low-pass filter and an up-conversion module, and the method further includes: Receive the third output signal through the digital-to-analog converter and convert the digital signal into an analog signal, and output the signal to the low-pass filter; The output signal of the digital-to-analog converter is received by the low-pass filter and filtered, and the signal is output to the up-conversion module; The up-conversion module receives the output signal of the low-pass filter and increases the signal frequency from a low frequency band to a high frequency band, and outputs the signal to the power amplifier PA.

21. The method according to any one of claims 12 to 19, characterized in that: The feedback link includes: a down-conversion module, a low-pass filter and an analog-to-digital converter, and the method further includes: The down-conversion module receives the first output signal and reduces the signal frequency from a high frequency band to a low frequency band, and outputs the signal to the low-pass filter; The output signal of the down-conversion module is received through the low-pass filter and filtered, and the signal is output to the analog-to-digital converter; The output signal of the low-pass filter is received by the analog-to-digital converter, and the analog signal is converted into a digital signal, and the second output signal is output.

22. The method according to any one of claims 15 to 19, characterized in that: When the residual value energy meets the performance requirement, the fewer the number of memory items in the memory item combination, the smaller the complexity of the first nonlinear model of the digital predistortion DPD module.

23. A transmitter, characterized in that: The transmitter comprises an antenna and a digital predistortion device as claimed in any one of claims 1 to 11.

24. A chip system, characterized in that: The chip system includes a processor, which is used to support the digital pre-distortion device to implement the method according to any one of claims 12 to 22.

25. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 12 to 22.

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