Determination method of pre-distortion signal and pre-distortion device

Abstract

The embodiment of the invention provides a pre-distortion signal determination method and a pre-distortion device, and the method comprises the steps: respectively inputting a digital baseband signal into a plurality of pre-distortion processing units, obtaining a plurality of initial pre-distortion signals, enabling the plurality of pre-distortion processing units to have the same amplitude selection affine function generation module, and enabling the amplitude selection affine function generation module to generate a plurality of initial pre-distortion signals; the amplitude selection affine function generation module is used for executing linear operation on the amplitude of a signal sampling point in the digital baseband signal; and determining a target pre-distortion signal according to the plurality of initial pre-distortion signals. According to the embodiment of the invention, the problem that the operation complexity is high in the predistortion signal generation process in the prior art can be solved, the amplitude selection affine function generation module is utilized to perform linear operation on the amplitude of the signal sampling point in the digital baseband signal, the operation complexity is reduced, and hardware resources are reduced.

Description

Technical Field

[0001] The present application relates to the field of digital predistortion of radio frequency power amplifiers, and in particular to a method for determining a predistortion signal and a predistortion device. Background Art

[0002] In the related art, commonly used digital pre-distortion models such as memory polynomial (MP) and generalized memory polynomial (GMP) can compensate for the nonlinearity of the short-term memory effect of the power amplifier (PA), but cannot compensate for the long-term memory effect whose time magnitude is much larger than the RF signal period. In GaN transistors, the electron trap effect is considered to be an important source of the long-term memory effect in GaN power amplifiers. Especially in time-division duplex systems, signals with discontinuous power levels will make the trap effect significant, increasing the difficulty of GaN PA digital pre-distortion.

[0003] In order to compensate for the long-term memory effect of GaN power amplifiers (PAs), Barradas et al. proposed a behavioral model based on the physical mechanism of the trap effect. This method significantly improves the pre-distortion effect by introducing the trap state of GaN PAs into the conventional behavioral model.

[0004] However, while using the above method to improve the pre-distortion effect, the number of model coefficients and the complexity of the model structure will increase sharply. In particular, in the calculation process of the pre-distortion signal, a large number of nonlinear operations need to be performed, resulting in a high computational complexity problem in the process of generating the pre-distortion signal.

[0005] In summary, there is no good solution to the problem of high computational complexity in the process of generating a predistortion signal in the related art. Summary of the invention

[0006] The embodiments of the present application provide a method for determining a predistortion signal and a predistortion device, so as to at least solve the problem of high computational complexity in the process of generating a predistortion signal in the related art.

[0007] According to an embodiment of the present application, a method for determining a predistortion signal is provided, the method comprising: inputting a digital baseband signal into a plurality of predistortion processing units respectively to obtain a plurality of initial predistortion signals, wherein the plurality of predistortion processing units have the same amplitude selection affine function generation module, the amplitude selection affine function generation module being used to perform a linear operation on the amplitude of a signal sampling point in the digital baseband signal; and determining a target predistortion signal according to the plurality of initial predistortion signals.

[0008] According to another embodiment of the present application, a predistortion device is provided, which includes: multiple predistortion processing units, used to process a digital baseband signal to obtain multiple initial predistortion signals, wherein the multiple predistortion processing units have the same amplitude selection affine I-MSA function generation module, and the I-MSA function generation module is used to perform a linear operation different from a nonlinear operation on the amplitude of a signal sampling point in the digital baseband signal; a merging unit, used to determine a target predistortion signal according to a first initial predistortion signal, a second initial predistortion signal and a third initial predistortion signal.

[0009] According to another embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program executes the steps of any of the above method embodiments when executed by a processor.

[0010] According to another embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0011] Through the embodiments of the present application, the I-MSA function generation module is used to perform linear operation on the amplitude of the signal sampling point in the digital baseband signal to obtain the target pre-distortion signal, which can solve the problem of high computational complexity in the process of generating the pre-distortion signal in the related art. While ensuring the compensation performance, the amount of computation of the pre-distortion model is reduced, achieving the technical effect of improving the efficiency of generating the pre-distortion signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of a hardware structure block diagram of a method for determining a predistortion signal according to an embodiment of the present application;

[0013] Figure 2 is a flow chart of a method for determining a predistortion signal according to an embodiment of the present application;

[0014] Figure 3 is a structural schematic diagram of a trap effect model according to an embodiment of the present application;

[0015] Figure 4 is a structural schematic diagram of a digital predistorter according to an embodiment of the present application;

[0016] Figure 5 is a schematic diagram of the structure of an I-MSA function generation module according to an embodiment of the present application;

[0017] Figure 6 is a structural schematic diagram of a first pre-distortion processing unit according to an embodiment of the present application;

[0018] Figure 7 is a structural schematic diagram of a second pre-distortion processing unit according to an embodiment of the present application;

[0019] Figure 8 is a structural schematic diagram of a third pre-distortion processing unit according to an embodiment of the present application;

[0020] Fig. 9 is a schematic diagram of the overall structure of a predistortion device according to an embodiment of the present application;

[0021] Fig.10 It is a comparison diagram of the pre-distortion effects obtained by using the pre-distortion model in the embodiment of the present application and the GMP model in the related art. DETAILED DESCRIPTION

[0022] The embodiments of the present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0024] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, Figure 1 is a schematic diagram of a hardware structure block diagram of a method for determining a predistortion signal according to an embodiment of the present application, such as Figure 1 As shown, the hardware board may include one or more ( Figure 1 Only one is shown in the figure) a processor 12 (the processor 12 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device) and a memory 14 for storing data, wherein the mobile terminal may also include a transmission device 16 for communication functions and an input and output device 18. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the mobile terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0025] The memory 14 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the method for determining the predistortion signal in the embodiment of the present application. The processor 12 executes various functional applications and the method for determining the predistortion signal by running the computer program stored in the memory 14, that is, the above method is implemented. The memory 14 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 14 may further include a memory remotely arranged relative to the processor 12, and these remote memories can be connected to the mobile terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0026] The transmission device 16 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider. In one example, the transmission device 16 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 16 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0027] In one embodiment of the present application, a method for determining a predistortion signal is provided. Figure 2 is a flow chart of a method for determining a predistortion signal according to an embodiment of the present application, such as Figure 2 As shown, the process may include the following steps:

[0028] Step S202, inputting the digital baseband signal into a plurality of predistortion processing units respectively to obtain a plurality of initial predistortion signals, wherein the plurality of predistortion processing units have the same amplitude selection affine function generation module, and the amplitude selection affine function generation module is used to perform a linear operation on the amplitude of a signal sampling point in the digital baseband signal;

[0029] Step S204: determining a target predistortion signal according to the multiple initial predistortion signals.

[0030] Among them, the amplitude selection affine function generation module can be understood as an I-MSA function generation module, which can divide the input data into multiple regions according to the amplitude of the input signal, and linearize the nonlinear terms of the power amplifier model in each region. In other words, in the embodiment of the present application, the I-MSA function can be used to simplify the high-order terms (nonlinear terms) in the digital pre-distortion model.

[0031] The function of the I-MSA function generation module in the predistortion processing unit is to respectively correspond to a set of different coefficients for different amplitude intervals, and to perform different linear operations on the amplitude of the input digital baseband signal using each set of different coefficients.

[0032] In order to facilitate understanding of the above-mentioned method for determining the pre-distortion signal, firstly, a brief introduction is given to the construction and principle of the digital pre-distortion model (also referred to as the pre-distortion model) and the method for determining the trap state of the GaN power amplifier.

[0033] 1. Construction of digital pre-distortion model

[0034] In this embodiment, the digital predistortion model for compensating the power amplifier trap effect based on the I-MSA function has the following structure and principle:

[0035] The predistortion model including trap effect compensation can be expressed as follows:

[0036]

[0037] in, is the baseband signal vector after predistortion, is the model matrix of the conventional model, is the model parameter vector, is the trap state under the current input signal, is the Kronecker product.

[0038] If the compensation including trapping effect is performed based on the generalized memory polynomial (GMP) model in the related art, taking this model as an example, the compensation model can be expressed by the following formula (2):

[0039]

[0040] It can be seen from formula (2) that compared with the model without adding trap states Model after adding trap effect compensation The complexity will double.

[0041] (II) Trap states of GaN amplifiers Determination

[0042] Assume that the input signal The trap state of the GaN amplifier is It can be obtained by, but not limited to, the following steps:

[0043] S31, construction of the model of the trap effect;

[0044] According to the mechanism of the trap effect, we can establish Figure 3The trap effect model shown in FIG. 1 is shown in FIG. 1 . The mathematical expressions of the process in the time domain and the digital domain are respectively the following formulas (3) and (4):

[0045]

[0046]

[0047] Among them, v d is the drain potential of the GaN transistor; v c is the trap state of the transistor; R1 and R2 are resistors, C is a capacitor; τ cap =R cap C = R1C is the time constant of the process of trapping electrons; τ rel =R rel C = (R1 + R2) C is the time constant of the trap releasing electrons; f s is the sampling rate.

[0048] S32, retrieval of long-term memory effects;

[0049] 1) Input signal Under the action of The amplifier output Modeling is performed using a memoryless polynomial model, which only compensates for static nonlinearity;

[0050] 2) The modeling results Subtract the actual amplifier output to get an output that includes dynamic nonlinearity

[0051] 3) After low-pass filtering, the output contains only long-term memory effects.

[0052] S33, fitting to obtain the time constant;

[0053] will only contain output of long-term memory effects and the trap state in formula (2) By fitting, the time constant corresponding to the best fit can be obtained through the fitting function in MATLAB, and then the trap state of the GaN power amplifier under any input signal can be calculated.

[0054] Combined with the description of formula (2), it can be seen that the GaN power amplifier will be affected by long-term memory effects such as trap effects. Compensating for trap effects based on the traditional model will increase the complexity of the model. In the embodiment of the present application, the I-MSA function is mainly used to simplify the compensation model with high complexity, thereby reducing the complexity of the model while ensuring a good compensation effect.

[0055] Specifically, the I-MSA model is used to divide the input data into several regions according to the amplitude of the input signal, and the nonlinear terms of the power amplifier model are linearized in each region. The nonlinear high-order terms in the compensation model based on the GMP model (Formula (2)) are rewritten using the MSA function to obtain:

[0056]

[0057] The corresponding relationship between the rewritten formula (5) and the formula (2) before rewriting is as follows:

[0058] (1) Substitute the nonlinear term in formula (2) Rewritten as formula (5)

[0059] The nonlinear term in formula (2) Rewritten as formula (5)

[0060] The nonlinear term in formula (2) Rewritten as formula (5)

[0061] For example, the overall structure of the digital predistorter (referred to as predistorter or predistortion device) for compensating power amplifier trap effect based on the I-MSA function is as follows: Figure 4 As shown, it includes a first predistortion processing unit 001, a second predistortion processing unit 002, a third predistortion unit 003, an amplitude selective affine function (I-MSA) generation module, etc.

[0062] By inputting the digital baseband signal x(n) into the first predistortion processing unit 001, the second predistortion processing unit 002 and the third predistortion unit 003 respectively, a first initial predistortion signal, a second initial predistortion signal and a third initial predistortion signal are obtained, thereby determining a target predistortion signal.

[0063] From the comparison between the above formula (2) and formula (5), it can be seen that the I-MSA function generation module performs linear operations on the amplitude of the signal sampling points in the digital baseband signal, thereby avoiding a large number of nonlinear operations caused by compensating for the trap effect based on the traditional memory polynomial model in the related art, simplifying the model complexity, and reducing the operations in the process of generating the pre-distortion function.

[0064] In order to more clearly understand the digital predistortion method for compensating the power amplifier trap effect based on the I-MSA function in the embodiment of the present application, the following is combined with Fig. 9 The structural schematic diagram of the predistortion device shown is used to describe the specific implementation process of the above predistortion method.

[0065] S902, sending the input digital baseband signal x(n) to a power amplifier digital predistorter based on the I-MSA function, wherein the power amplifier digital predistorter based on the I-MSA function includes a predistortion model for compensating for the power amplifier trap effect based on the I-MSA function, and performs predistortion processing on the input digital baseband signal x(n) to generate a digital predistortion signal x pre (n);

[0066] S904-S906, for digital predistortion signal x pre (n) Perform digital-to-analog conversion and send it to the modulator to generate a radio frequency signal;

[0067] S908, sending the radio frequency signal to a power amplifier for amplification and output;

[0068] S910-S914, the output signal of the power amplifier is demodulated, filtered, and converted from digital to analog after being attenuated and coupled by a demodulator, a low-pass filter, and an analog-to-digital converter to generate an output digital baseband signal y(n);

[0069] Finally, the power amplifier digital predistortion model based on the I-MSA function is trained for the input digital baseband signal x(n) and the output digital baseband signal y(n) to determine the predistortion parameters in the predistorter.

[0070] The predistortion parameters may be, but are not limited to, the first group of coefficients, the second group of coefficients, and the third group of coefficients determined by the coefficient selectors in the I-MSA function generation modules in the first predistortion processing unit to the third predistortion unit. Each group of coefficients will be described below in conjunction with a specific embodiment.

[0071] In an exemplary embodiment, the linear operation includes a multiplication operation and an addition operation, and the nonlinear operation includes an exponential operation.

[0072] In an exemplary embodiment, in step S202, the digital baseband signal is input into a plurality of predistortion processing units respectively to obtain a plurality of initial predistortion signals, which includes the following steps:.

[0073] S202-1, inputting the digital baseband signal into the first predistortion processing unit to obtain a first initial predistortion signal, wherein the first amplitude selection affine function generation module in the first predistortion processing unit is used to perform a first linear operation on the amplitude of the digital baseband signal;

[0074] S202-2, inputting the digital baseband signal into a second predistortion processing unit to obtain a second initial predistortion signal, wherein the second amplitude selection affine function generation module in the second predistortion processing unit is used to perform a second linear operation on the amplitude of the digital baseband signal;

[0075] S202-3, inputting the digital baseband signal into a third predistortion processing unit to obtain a third initial predistortion signal, wherein a third amplitude selection affine function generation module in the third predistortion processing unit is used to perform a third linear operation on the amplitude of the digital baseband signal;

[0076] Among them, the structures of the first amplitude selection affine function generation module, the second amplitude selection affine function generation module and the third amplitude selection affine function generation module are the same.

[0077] like Figure 4 As shown in FIG. 1 , the overall structure of the digital predistorter (referred to as predistorter or predistortion device) for compensating the power amplifier trap effect based on the I-MSA function is as follows: Figure 4 As shown, it includes a first predistortion processing unit 001, a second predistortion processing unit 002, a third predistortion unit 003, an amplitude selective affine function (I-MSA) generation module, etc.

[0078] 011 is an I-MSA function generation module; 012 is a delay unit, used for delaying and outputting input data; 013 is a multiplier, used for multiplying and outputting input data; 014 is an adder, used for adding and outputting input data.

[0079] In addition, the first predistortion processing unit is the first part of the digital predistorter for compensating the power amplifier trap effect based on the I-MSA function, the second predistortion processing unit is the second part of the digital predistorter for compensating the power amplifier trap effect based on the I-MSA function, and the third predistortion processing unit is the third part of the digital predistorter for compensating the power amplifier trap effect based on the I-MSA function.

[0080] The digital baseband signal x(n) is input into the first predistortion unit 001 to obtain the first initial predistortion signal x pre1 (n); Input the digital baseband signal x(n) into the second predistortion unit 002 to obtain a second initial predistortion signal x pre2 (n); Input the digital baseband signal x(n) into the third predistortion unit 003 to obtain a third initial predistortion signal x pre3 (n).

[0081] The digital baseband signal x(n) may be, but is not limited to, a signal stream, n represents a sampling point in the digital domain, which may also be understood as a moment, and x(n) is a complex number that changes with the moment n. In other words, the amplitudes of the sampling points (instantaneous samples) obtained at different moments are different.

[0082] As an optional example, the step of inputting the digital baseband signal into the first predistortion processing unit to obtain the first initial predistortion signal includes:

[0083] Inputting the digital baseband signal into a first amplitude selection affine function generation module in the first predistortion processing unit to obtain a first output signal based on the amplitude selection affine function, wherein the first output signal based on the amplitude selection affine function corresponds to the signal amplitude of the digital baseband signal;

[0084] A first initial predistortion signal is determined based on the first output signal of the amplitude-selective affine function and the digital baseband signal.

[0085] This is because the I-MSA function generation module divides the input data into a plurality of different regions or intervals according to the amplitude of the input signal, and corresponds to a set of compensation coefficients corresponding to the signal amplitude of the digital baseband signal in each region.

[0086] In an exemplary embodiment, the digital baseband signal is input into the first I-MSA function generation module in the first pre-distortion processing unit to obtain a first output signal based on an amplitude-selective affine function corresponding to the signal amplitude of the digital baseband signal, including: determining the first output signal based on a first set of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0087] In a specific embodiment, the first output signal based on the amplitude selection affine function is determined by the following formula (6):

[0088]

[0089] The first set of coefficients includes and is the signal amplitude of the digital baseband signal, is the signal amplitude of the (nm)th sampling point in the digital baseband signal, S is the number of regions divided by the signal amplitude of the digital baseband signal, β S is the threshold of the divided area, S is a positive integer greater than or equal to 2, i is equal to 1 or 2, and k is a positive integer greater than or equal to 1 and less than or equal to S.

[0090] The structure of the first I-MSA function generation module in the embodiment of the present application is as follows Figure 5 As shown, the coefficient selector stores coefficients indexed according to signal amplitude classification, for example, coefficients A and B in formula (6).

[0091] The coefficient selector pre-stores the pre-distortion parameters obtained by the power amplifier digital pre-distortion training based on the I-MSA function generation module. The model training process includes the following steps:

[0092] S51, obtaining an input digital baseband signal x(n) and an output digital baseband signal y(n) and performing normalization and alignment processing;

[0093] S52, segmenting and approximating the model input signal according to its amplitude, and determining the memory depth, the number of partitions S of the basis function, and the set partition threshold βs;

[0094] S53, according to the memory depth, the number of partitions of the basis function and the set partition threshold, the output digital baseband signal y(n) is used as the model input, and the input digital baseband signal x(n) is used as the model output, to perform predistortion parameter training, extract and determine the predistortion coefficient.

[0095] In the above step S53, the process of extracting the predistortion coefficient includes the following steps:

[0096] S5302, finding the model input samples y'(n) and the corresponding model output samples x'(n) belonging to the same small area according to the constraint conditions of the input y(n) of the digital pre-distortion model.

[0097] S5304, the relationship between the input and output samples of the model in each small area can be expressed by the following formula (7):

[0098] X′ N′×1 =Y′ N′×Q′ W′ Q′×1 (7)

[0099] Where Y′ is the input matrix of the model, X′ is the corresponding model output vector, W′ is the model coefficient in each small area, N′ is the number of samples in each small area, and Q′ is the number of W′.

[0100] S5306, using the least squares (LS) algorithm, the corresponding solution can be expressed as the following formula (8):

[0101]

[0102] in represents the extracted predistortion coefficients, (·)H represents the conjugate transpose of the complex matrix, and (·)-1 represents the inverse of the complex matrix.

[0103] pass Figure 6 The first I-MSA function generation module in the first predistortion processing unit shown in the figure is used to determine the first group of coefficients in the above formula (6) according to the signal amplitude of the digital baseband signal x(n), wherein the first group of coefficients includes and k is a positive integer greater than or equal to 1 and less than or equal to S.

[0104] In determining the first output signal of the amplitude-based selected affine function After the first set of coefficients, determining a first initial predistortion signal according to a first output signal of the amplitude-selective affine function and a digital baseband signal specifically includes:

[0105] The first initial predistortion signal is determined by the following formula (9):

[0106]

[0107] in, is the (nm)th sampling point in the digital baseband signal, and the first output signal of the amplitude-selective affine function includes and v c (n) is the trap state, M a is the upper limit of the delay.

[0108] Combine the following Figure 6 The first predistortion processing unit shown determines a first initial predistortion signal The specific process is described as follows: the digital baseband signal is input into the first I-MSA function generation module to generate the corresponding output signal based on the amplitude selection affine function This signal is multiplied with the corresponding delayed signal of the baseband signal and added accordingly to obtain two nonlinear signals. One of the nonlinear signals With trap state v c (n) multiplied and connected to another branch nonlinear signal Add and output the first initial predistortion signal x pre1 (n).

[0109] The coefficient selector in the first I-MSA function generation module outputs the first set of coefficients corresponding to the modulus value of the digital baseband signal x(n), including and

[0110] The specific steps of determining the first initial predistortion signal are further described below in conjunction with the above formula (9):

[0111] S1002, With output value Multiply them and get M a The third product, and M a The third products are added to obtain a first sum value;

[0112] S1004, With output value Multiply them and get M a The fourth product, and M a The fourth products are added together to obtain a second sum value;

[0113] S1006, add the second sum value to v c The product of (n) is determined as the first target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal;

[0114] S1008: Add the first sum value and the first target sum value to obtain a value of the nth sampling point in the first initial pre-distortion signal.

[0115] As an optional implementation, in combination with formula (6), the output value in the above step S1002 may be determined by, but is not limited to, the following method: and the output value in step S1004

[0116] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the first output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M a Group output value, M a is the preset first maximum delay number, m is greater than or equal to 0 and less than or equal to M a The mth group of output values ​​includes the output value and output value

[0117] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the value of the nth sampling point in the digital baseband signal. The first set of coefficients includes a preset set of coefficients, and the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0118] The coefficient and The signal amplitude is multiplied to obtain the first product, and the first product is multiplied by the coefficient Add together to get the output value in the mth group of output values in, is the value of the (nm)th sampling point in the digital baseband signal;

[0119] The coefficient and The signal amplitude is multiplied to obtain the second product, and the second product is multiplied by the coefficient Add together to get the output value in the mth group of output values

[0120] Comparing the nonlinear high-order terms in the above formula (9) with those in the above formula (2), It can be seen that by using the first I-MSA function generation module, the power operation in the process of generating the first initial pre-distortion signal in the related art is converted into simple multiplication and addition and subtraction operations, thereby reducing the calculation operations.

[0121] In an exemplary embodiment, the digital baseband signal is input into a second predistortion processing unit to obtain a second initial predistortion signal, including: inputting the digital baseband signal into a second amplitude affine function generation module in the second predistortion processing unit to obtain a second output signal, wherein the second output signal corresponds to the signal amplitude of the digital baseband signal; and determining the second initial predistortion signal according to the second output signal and the digital baseband signal.

[0122] In an exemplary embodiment, the digital baseband signal is input into the second amplitude affine function generation module in the second predistortion processing unit to obtain the second output signal, including: determining the second output signal based on a second set of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0123] Among them, the structure of the second amplitude affine function generation module is as follows: Figure 5 As shown, the coefficient selector stores coefficients indexed according to signal amplitude classification, for example, coefficients A and B in the above formula (6), and coefficients C and D in the following formula (10).

[0124] pass Figure 7 The second I-MSA function generating module in the second predistortion processing unit shown in the figure is used to generate the second I-MSA function, and determine the second group of coefficients as shown in the following formula (10) according to the signal amplitude of the digital baseband signal x(n). Further, according to the second group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal, determine the second output signal based on the amplitude selection affine function as shown in the following formula (10):

[0125]

[0126] The second set of coefficients includes and is the signal amplitude of the (nm)th sampling point in the digital baseband signal, S is the number of regions divided by the signal amplitude of the digital baseband signal, β S is the threshold of the divided area, i is equal to 1 or 2, and k is a positive integer greater than or equal to 1 and less than or equal to S.

[0127] In determining the second output signal of the amplitude-based selected affine function After the second set of coefficients is obtained, a second initial predistortion signal is determined based on the second output signal and the digital baseband signal. Specifically, the second initial predistortion signal x is determined by the following formula (11): pre2 (n):

[0128]

[0129] in, is the (nm)th sampling point in the digital baseband signal, and the second output signal of the amplitude-selective affine function includes and v c (n) is the trap state, M b is the upper limit of the delay, L b is the maximum delay depth of the filter.

[0130] Combine the following Figure 7 The second predistortion processing unit shown determines the second initial predistortion signal x pre2 The specific process of (n) is described as follows: the digital baseband signal is input into the second amplitude affine function generation module to generate a corresponding second output signal based on the amplitude selection affine function After passing through a series of FIR filters, the signal is multiplied with the corresponding delayed signal of the baseband signal and added accordingly to obtain two nonlinear signals. One of the nonlinear signals With trap state v c (n) and multiplied by the nonlinear signal of the other branch Added together, the output baseband predistortion signal x pre2 (n).

[0131] The coefficient selector in the second I-MSA function generation module outputs the corresponding second set of coefficients according to the modulus value of the digital baseband signal x(n). and

[0132] The specific steps of determining the second initial predistortion signal are further described below in conjunction with the above formula (11):

[0133] S1102, the output value and output value Input the target filter and get the first filtered output value and the second filtered output value

[0134] S1104, The first filter output value Multiply them and get M b The seventh product, and M b The seventh products are added together to obtain a third sum value;

[0135] S1106, will The second filter output value Multiply them and get M b The eighth product, and M b The eighth products are added together to obtain a fourth sum value;

[0136] S1108, add the fourth sum value to v c The product of (n) is determined as the second target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal;

[0137] S1110 , adding the third sum value and the second target sum value to obtain a value of the nth sampling point in the second initial pre-distortion signal.

[0138] That is, the output value After filtering by the target filter FIR, the first filtered output value is obtained. Output value After filtering by the target filter FIR, the second filtered output value is obtained. The target filter FIR here can be understood, but is not limited to, as a filter in which all delayed tap coefficients are 1, and its purpose is to achieve delayed addition of signals.

[0139] As an optional implementation, in combination with formula (10), the output value in the above step S1102 can be determined by, but not limited to, the following method: and output value

[0140] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the second output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M b Group output value, M b is the preset second maximum delay number, m is greater than or equal to 0 and less than or equal to M b The mth group of output values ​​includes the output value and

[0141] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the second set of coefficients includes a preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0142] The coefficient and The signal amplitude is multiplied to obtain the fifth product, and the fifth product is multiplied by the coefficient Add and get the output value in, is the value of the (nm)th sampling point in the digital baseband signal;

[0143] The coefficient and The signal amplitude is multiplied to obtain the sixth product, and the sixth product is multiplied by the coefficient Add and get the output value

[0144] Obviously, the logic for calculating the second output signal is the same as the logic for calculating the first output signal, except that a first different set of coefficients (the first set of coefficients and the second set of coefficients) is applied.

[0145] Comparing the nonlinear high-order terms in the above formula (11) with those in the above formula (2), It can be seen that by using the second amplitude affine function generation module, the power operation in the process of generating the second initial pre-distortion signal in the related art is converted into simple multiplication and addition and subtraction operations, thereby reducing the calculation operations.

[0146] In an exemplary embodiment, the digital baseband signal is input into a third predistortion processing unit to obtain a third initial predistortion signal, including: inputting the digital baseband signal into a third amplitude affine function generation module in the third predistortion processing unit to obtain a third output signal, wherein the third output signal corresponds to the signal amplitude of the digital baseband signal; and determining the third initial predistortion signal according to the third compensation signal and the digital baseband signal.

[0147] The step of inputting the digital baseband signal into the third amplitude affine function generating module in the third predistortion processing unit to obtain the third output signal includes: determining the third output signal according to the third group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0148] Among them, the structure of the third amplitude affine function generation module is as follows: Figure 5 As shown, the coefficient selector stores coefficients indexed by signal amplitude classification, for example, coefficients A and B in the above formula (6), coefficients in the above formula (10) The second group of coefficients includes and And the coefficients in the following formula (12) and

[0149] pass Figure 8 The third amplitude affine function generating module in the third predistortion processing unit shown in the figure is used to determine the third group of coefficients in the following formula (12) according to the signal amplitude of the digital baseband signal x(n); further, the third output signal is determined according to the third group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal, including:

[0150]

[0151] The third group of coefficients includes and is the signal amplitude of the (nm)th sampling point in the digital baseband signal, S is the number of regions divided by the signal amplitude of the digital baseband signal, β S is the threshold of the divided area, i is equal to 1 or 2, and k is a positive integer greater than or equal to 1 and less than or equal to S.

[0152] In determining the third output signal based on the amplitude selection affine function After the third set of coefficients, the third initial predistortion signal is determined according to the third output signal of the amplitude-selective affine function and the digital baseband signal. Specifically, the third initial predistortion signal x is determined by the following formula (13): pre3 (n):

[0153]

[0154] in, is the (nm)th sampling point in the digital baseband signal. The third output signal of the amplitude-selective affine function includes and v c (n) is the trap state, M c is the upper limit of the delay, L c is the maximum look-ahead depth of the filter.

[0155] Combine the following Figure 8 The third predistortion processing unit shown determines a third initial predistortion signal x pre3The specific process of (n) is described as follows: the digital baseband signal is input into the third I-MSA function generation module to generate a corresponding third output signal based on the amplitude selection affine function. After passing through a series of FIR filters, the signal is multiplied with the corresponding delayed signal of the baseband signal and added accordingly to obtain two nonlinear signals. One of the nonlinear signals With trap state v c (n) and multiplied by the nonlinear signal of the other branch Added together, the output baseband predistortion signal x pre3 (n).

[0156] The coefficient selector in the third I-MSA function generation module outputs the corresponding third set of coefficients according to the modulus value of the digital baseband signal x(n). and

[0157] It should be noted that the preset set of coefficients corresponding to the k-th amplitude interval mentioned in the above embodiments may be fixed or continuously updated with the training process of the model. In other words, the preset set of coefficients respectively included in the first set of coefficients, the second set of coefficients and the third set of coefficients in the above embodiments are only examples and are not limited thereto.

[0158] The specific steps of determining the third initial predistortion signal are further described below in conjunction with the above formula (13):

[0159] S1202, output value and output value Input the target filter and get the third filter output value And the fourth filter output value

[0160] S1204, The third filter output value Multiply them and get M c eleventh product, and M c The eleventh products are added together to obtain the fifth sum;

[0161] S1206, AND and the fourth filter output value Multiply them and get M c The twelfth product, and M c The twelfth products are added together to obtain the sixth sum;

[0162] S1208, add the sixth sum value and v c The product of (n) is determined as the third target sum value, where vc (n) is the value of the nth sampling point in the preset trap state signal;

[0163] S1210: Add the fifth sum value and the third target sum value to obtain the value of the nth sampling point in the third initial pre-distortion signal.

[0164] That is, the output value After filtering by the target filter FIR, the third filter output value is obtained. Output value After filtering by the target filter FIR, the fourth filter output value is obtained. The target filter FIR here can be understood, but is not limited to, as a filter in which all delayed tap coefficients are 1, and its purpose is to achieve delayed addition of signals.

[0165] As an optional implementation, in combination with formula (12), the output value in the above step S1202 can be determined by, but not limited to, the following method: and output value

[0166] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the third output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M c Group output value, M c is the preset third maximum delay number, and m is greater than or equal to 0 and less than or equal to M c The mth group of output values ​​includes the output value and

[0167] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the third set of coefficients includes a preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0168] The coefficient and The signal amplitude is multiplied to obtain the ninth product, and the ninth product is multiplied by the coefficient Add and get the output value in, is the value of the (nm)th sampling point in the digital baseband signal;

[0169] The coefficient and The signal amplitude is multiplied to obtain the tenth product, and the tenth product is multiplied by the coefficient Add and get the output value

[0170] Obviously, the logic for calculating the third output signal is the same as the logic for calculating the first output signal and the second output signal, the difference being that a different set of coefficients (the third set of coefficients) is applied.

[0171] Comparing the nonlinear high-order terms in the above formula (13) with those in the above formula (2), It can be seen that by using the third I-MSA function generation module, the power operation in the process of generating the third initial pre-distortion signal in the related art is converted into simple multiplication and addition and subtraction operations, thereby reducing the calculation operations.

[0172] In an exemplary embodiment, after determining the first initial pre-distortion signal, the second initial pre-distortion signal and the third initial pre-distortion signal, the method further includes:

[0173] The first initial predistortion signal, the second initial predistortion signal and the third initial predistortion signal are summed to obtain a target predistortion signal.

[0174] By utilizing the I-MSA function generation module, the nonlinear operation in the process of generating the first initial predistortion signal, the second predistortion signal and the third predistortion signal is converted into different linear operation, thereby ensuring the compensation performance and reducing the operation complexity.

[0175] Combined with the analysis of the above embodiments, it can be seen that the pre-distortion method proposed in the embodiments of the present application is to classify the amplitude of the input signal (digital baseband signal), and replace the complex high-order terms in the original model with amplitude-selective affine functions in any region to which the input signal amplitude belongs. While ensuring similar compensation performance, the computational complexity of the hardware implementation is greatly reduced.

[0176] Fig.10 It is the result of digital predistortion of LTE 20M signal using the method in the present invention. The figure shows the output without predistortion, the predistortion output without trap effect compensation (using the GMP model) and the power spectral density result after predistortion using the method in the embodiment of the present application.

[0177] In the spectrum diagram, the power spectrum on the left and right sides of the main signal is usually used to reflect the ACPR (adjacent channel power ratio) performance, and the lower the power spectrum on the left and right sides of the main signal, the better the ACPR (adjacent channel power ratio) performance. Fig.10 It can be seen intuitively that, compared with the GMP solution without trap effect compensation, the technical solution in the embodiment of the present application can bring about a 2-3dB improvement in ACPR (adjacent channel power ratio) performance with fewer multiplier resources.

[0178] Fig. 9 is a schematic diagram of the structure of a (digital) pre-distortion device according to an embodiment of the present application. Fig. 9 As shown, the predistortion device includes the following structure:

[0179] A power-efficient digital predistorter 902 based on an I-MSA function, wherein the predistorter 902 comprises a plurality of predistortion processing units for processing a digital baseband signal to obtain a plurality of initial predistortion signals, wherein the plurality of predistortion processing units have a same amplitude selection affine function generation module, and the amplitude affine function generation module is used to perform a linear operation on the amplitude of a signal sampling point in the digital baseband signal;

[0180] The merging unit is used to determine a target predistortion signal according to a plurality of initial predistortion signals.

[0181] In addition, the following units are included:

[0182] A digital-to-analog converter number 904 is used for digital predistortion signal x pre (n) performing digital-to-analog conversion;

[0183] The modulator 906 is used to modulate the output signal of the digital-to-analog converter to generate a radio frequency signal;

[0184] A power amplifier 908, used to amplify and output the output signal of the modulator;

[0185] A demodulator 910, configured to demodulate the output signal of the attenuating coupler;

[0186] A low-pass filter 912, used for low-pass filtering the output signal of the demodulator;

[0187] The analog-to-digital converter 914 is used to perform analog-to-digital conversion on the output signal of the low-pass filter to generate an output digital baseband signal y(n).

[0188] In a specific embodiment, the complexity analysis of the digital predistortion model for compensating the power amplifier trap effect based on the I-MSA function and the GMP model in the related art is compared as follows:

[0189] For the digital predistortion model (model 1) based on the I-MSA function to compensate for the power amplifier trap effect, the calculation The number of real multiplications required is: For the GMP-based model (Model 2), calculate The number of real multiplications required is: N2 = [6 (M a +1)+6(M b +1)L b +6(M c +1)L c )]×2+2.

[0190] K a =8, K b =K c =5,M a =M b =M c =6,L b =L c =2 as an example, the complexity of model (1) is N1=422, and the complexity of model (2) is N2=2426, which shows that the complexity of the digital predistortion model based on I-MSA function to compensate for the power amplifier trap effect is greatly reduced compared with the traditional GMP-based model.

[0191] In an optional embodiment, the device further comprises:

[0192] The first pre-distortion processing unit (such as Figure 6 ), used to process the digital baseband signal to obtain a first initial predistortion signal, wherein the first amplitude affine function generating module in the first predistortion processing unit is used to perform a first linear operation on the amplitude of the digital baseband signal;

[0193] The second pre-distortion processing unit (such as Figure 7 As shown), used to process the digital baseband signal to obtain a second initial predistortion signal, wherein the second amplitude affine function generating module in the second predistortion processing unit is used to perform a second linear operation on the amplitude of the digital baseband signal;

[0194] The third pre-distortion processing unit (such as Figure 8 As shown), it is used to process the digital baseband signal to obtain a third initial pre-distortion signal, wherein the third amplitude affine function generation module in the third pre-distortion processing unit is used to perform a third linear operation on the amplitude of the digital baseband signal.

[0195] In an optional embodiment, the first pre-distortion processing unit further includes:

[0196] A first amplitude affine function generating module, used for processing the digital baseband signal to obtain a first output signal, wherein the first output signal corresponds to the signal amplitude of the digital baseband signal;

[0197] The first processing module is used to determine a first initial predistortion signal according to the first output signal and the digital baseband signal.

[0198] In an optional embodiment, the first processing module further includes:

[0199] The first processing submodule is used to determine a first output signal according to a first group of compensation coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0200] The first processing submodule is further configured to determine the first output signal through the following steps:

[0201] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the first output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M a Group output value, M a is the preset first maximum delay number, m is greater than or equal to 0 and less than or equal to M a The mth group of output values ​​includes the output value and output value

[0202] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the value of the nth sampling point in the digital baseband signal. The first set of coefficients includes a preset set of coefficients, and the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0203] The coefficient and The signal amplitude is multiplied to obtain the first product, and the first product is multiplied by the coefficient Add together to get the output value in the mth group of output values in, is the value of the (nm)th sampling point in the digital baseband signal;

[0204] The coefficient and The signal amplitude is multiplied to obtain the second product, and the second product is multiplied by the coefficient Add together to get the output value in the mth group of output values

[0205] In an optional embodiment, the first processing module further includes:

[0206] The second processing submodule is used to determine a first initial predistortion signal through the following steps:

[0207] Will With output value Multiply them and get M a The third product, and M a The third products are added to obtain a first sum value;

[0208] Will With output value Multiply them and get M a The fourth product, and M a The fourth products are added to obtain a second sum value;

[0209] Add the second sum to v c The product of (n) is determined as the first target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal;

[0210] The first sum value and the first target sum value are added to obtain the value of the nth sampling point in the first initial predistortion signal.

[0211] In an optional embodiment, the second pre-distortion processing unit further includes:

[0212] A second amplitude affine function generating module, used for processing the digital baseband signal to obtain a second output signal, wherein the second output signal corresponds to the signal amplitude of the digital baseband signal;

[0213] The second processing module is used to determine a second initial predistortion signal according to the second output signal and the digital baseband signal.

[0214] In an optional embodiment, the second processing module further includes:

[0215] The third processing submodule is used to determine the second output signal according to the second group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0216] The third processing submodule is further configured to determine the second output signal through the following steps:

[0217] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the second output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M b Group output value, M b is the preset second maximum delay number, m is greater than or equal to 0 and less than or equal to M b The mth group of output values ​​includes the output value and

[0218] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the second set of coefficients includes a preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0219] The coefficient and The signal amplitude is multiplied to obtain the fifth product, and the fifth product is multiplied by the coefficient Add and get the output value in, is the value of the (nm)th sampling point in the digital baseband signal;

[0220] The coefficient and The signal amplitude is multiplied to obtain the sixth product, and the sixth product is multiplied by the coefficient Add and get the output value

[0221] In an optional embodiment, the second processing module further includes:

[0222] The fourth processing submodule is used to determine the second initial predistortion signal through the following steps:

[0223] Output value and output value Input the target filter and get the first filtered output value and the second filtered output value

[0224] Will The first filter output value Multiply them and get M b The seventh product, and M b The seventh products are added together to obtain a third sum value;

[0225] Will The second filter output value Multiply them and get M b The eighth product, and M b The eighth products are added together to obtain a fourth sum value;

[0226] Add the fourth sum to v c The product of (n) is determined as the second target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal;

[0227] The third sum value and the second target sum value are added to obtain the value of the nth sampling point in the second initial predistortion signal.

[0228] In an optional embodiment, the third pre-distortion processing unit further includes:

[0229] A third amplitude affine function generating module, used for processing the digital baseband signal to obtain a third output signal, wherein the third output signal corresponds to the signal amplitude of the digital baseband signal;

[0230] The third processing module is used to determine a third initial pre-distortion signal according to the third output signal and the digital baseband signal.

[0231] In an optional embodiment, the third processing module further includes:

[0232] The fifth processing submodule is used to determine a third output signal according to a third group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

[0233] The fifth processing submodule is further used to determine the third output signal through the following steps:

[0234] The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the third output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M c Group output value, M c is the preset third maximum delay number, and m is greater than or equal to 0 and less than or equal to M c The mth group of output values ​​includes the output value and

[0235] exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the third set of coefficients includes a preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S;

[0236] The coefficient and The signal amplitude is multiplied to obtain the ninth product, and the ninth product is multiplied by the coefficient Add and get the output value in, is the value of the (nm)th sampling point in the digital baseband signal;

[0237] The coefficient and The signal amplitude is multiplied to obtain the tenth product, and the tenth product is multiplied by the coefficient Add and get the output value

[0238] In an optional embodiment, the third processing module further includes:

[0239] The sixth processing submodule is used to determine the third initial pre-distortion signal through the following steps:

[0240] Output value and output value Input the target filter and get the third filter output value And the fourth filter output value

[0241] Will The third filter output value Multiply them and get M c eleventh product, and M c The eleventh products are added together to obtain the fifth sum;

[0242] Will AND and the fourth filter output value Multiply them and get M c The twelfth product, and M c The twelfth products are added together to obtain the sixth sum;

[0243] Add the sixth sum to v cThe product of (n) is determined as the third target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal;

[0244] The fifth sum value and the third target sum value are added to obtain the value of the nth sampling point in the third initial pre-distortion signal.

[0245] In an optional embodiment, the merging unit further includes:

[0246] The fourth processing module is used to sum the first initial predistortion signal, the second initial predistortion signal and the third initial predistortion signal to obtain a target predistortion signal.

[0247] In an optional embodiment, the linear operation includes a multiplication operation and an addition operation, and the nonlinear operation includes an exponential operation.

[0248] Through the embodiments of the present application, an amplitude affine function generation module is used to perform linear operation on the amplitude of the signal sampling point in the digital baseband signal to obtain a target predistortion signal, which can solve the problem of high computational complexity in the process of generating the predistortion signal in the related art. While ensuring the compensation performance, the amount of computation of the predistortion model is reduced, achieving the technical effect of improving the efficiency of generating the predistortion signal.

[0249] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program executes the steps of any of the above method embodiments when executed by a processor.

[0250] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0251] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0252] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0253] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0254] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0255] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for determining a predistortion signal, characterized in that: include: Inputting the digital baseband signal into a plurality of predistortion processing units respectively to obtain a plurality of initial predistortion signals, wherein the plurality of predistortion processing units have the same amplitude selection affine function generation module, and the amplitude selection affine function generation module is used to perform a linear operation on the amplitude of a signal sampling point in the digital baseband signal; A target predistortion signal is determined according to the multiple initial predistortion signals.

2. The method according to claim 1, characterized in that The digital baseband signal is input into a plurality of predistortion processing units respectively to obtain a plurality of initial predistortion signals, including: Inputting the digital baseband signal into a first predistortion processing unit to obtain a first initial predistortion signal, wherein a first amplitude selection affine function generation module in the first predistortion processing unit is used to perform a first linear operation on the amplitude of the digital baseband signal; Inputting the digital baseband signal into a second predistortion processing unit to obtain a second initial predistortion signal, wherein the second amplitude selection affine function generation module in the second predistortion processing unit is used to perform a second linear operation on the amplitude of the digital baseband signal; Inputting the digital baseband signal into a third predistortion processing unit to obtain a third initial predistortion signal, wherein a third amplitude selection affine function generation module in the third predistortion processing unit is used to perform a third linear operation on the amplitude of the digital baseband signal; The first linear operation, the second linear operation, and the third linear operation are used to perform the same linear operation logic on the amplitude of the digital baseband signal using different parameters.

3. The method according to claim 2, characterized in that Inputting the digital baseband signal into a first predistortion processing unit to obtain a first initial predistortion signal comprises: Inputting the digital baseband signal into the first amplitude selection affine function generation module in the first predistortion processing unit to obtain a first output signal, wherein the first output signal corresponds to the signal amplitude of the digital baseband signal; The first initial predistortion signal is determined according to the first output signal and the digital baseband signal.

4. The method according to claim 3, characterized in that The step of inputting the digital baseband signal into the first amplitude selection affine function generation module in the first predistortion processing unit to obtain a first output signal comprises: The first output signal is determined based on a first set of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

5. The method according to claim 4, characterized in that The determining the first output signal according to the first group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal comprises: The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the first output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M a Group output value, M a is the preset first maximum delay number, m is greater than or equal to 0 and less than or equal to M a A positive integer, the mth group of output values ​​includes output values and output value exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the value of the nth sampling point in the digital baseband signal, the first set of coefficients includes the preset set of coefficients, and the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S; The coefficient and The signal amplitude is multiplied to obtain a first product, and the first product is multiplied by the coefficient Add together to obtain the output value in the mth group of output values in, is the value of the (nm)th sampling point in the digital baseband signal; The coefficient With the The signal amplitude is multiplied to obtain a second product, and the second product is multiplied by the coefficient Add together to obtain the output value in the mth group of output values 6. The method according to claim 5, characterized in that The determining the first initial predistortion signal according to the first output signal and the digital baseband signal comprises: The With the output value Multiply them and get M a third products, and adding the Ma third products to obtain a first sum value; The With the output value Multiply them and get M a fourth products, and adding the Ma fourth products to obtain a second sum value; The second sum is added to v c The product of (n) is determined as the first target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal; The first sum value and the first target sum value are added to obtain a value of the nth sampling point in the first initial predistortion signal.

7. The method according to claim 2, characterized in that Inputting the digital baseband signal into a second predistortion processing unit to obtain a second initial predistortion signal comprises: Inputting the digital baseband signal into the second amplitude selection affine function generation module in the second predistortion processing unit to obtain a second output signal, wherein the second output signal corresponds to the signal amplitude of the digital baseband signal; The second initial predistortion signal is determined according to the second output signal and the digital baseband signal.

8. The method according to claim 7, characterized in that The step of inputting the digital baseband signal into the second amplitude selection affine function generation module in the second predistortion processing unit to obtain a second output signal comprises: The second output signal is determined based on a second set of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

9. The method according to claim 8, characterized in that Determining the second output signal according to a second group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal comprises: The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the second output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M b Group output value, M b is the preset second maximum delay number, m is greater than or equal to 0 and less than or equal to M b A positive integer, the mth group of output values ​​includes output values and exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the second set of coefficients includes the preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S; The coefficient and The signal amplitude is multiplied to obtain a fifth product, and the fifth product is multiplied by the coefficient Add together to get the output value in, is the value of the (nm)th sampling point in the digital baseband signal; The coefficient and The signal amplitude is multiplied to obtain a sixth product, and the sixth product is multiplied by the coefficient Add together to get the output value 10. The method according to claim 9, characterized in that The determining the second initial predistortion signal according to the second output signal and the digital baseband signal comprises: The output value and the output value Input the target filter and get the first filtered output value and the second filtered output value The The first filtered output value Multiply them and get M b The seventh product, and the M b The seventh products are added together to obtain a third sum value; The The second filtered output value Multiply them and get M b The eighth product, and the M b The eighth products are added together to obtain a fourth sum value; The fourth summation value is added to v c The product of (n) is determined as the second target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal; The third sum value and the second target sum value are added to obtain a value of the nth sampling point in the second initial predistortion signal.

11. The method according to claim 2, characterized in that Inputting the digital baseband signal into a third predistortion processing unit to obtain a third initial predistortion signal comprises: Inputting the digital baseband signal into the third amplitude selection affine function generation module in the third predistortion processing unit to obtain a third output signal, wherein the third output signal corresponds to the signal amplitude of the digital baseband signal; The third initial predistortion signal is determined according to the third output signal and the digital baseband signal.

12. The method according to claim 11, characterized in that The step of inputting the digital baseband signal into the third amplitude selection affine function generation module in the third predistortion processing unit to obtain a third output signal comprises: The third output signal is determined based on a third set of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal.

13. The method according to claim 12, characterized in that Determining the third output signal according to the third group of coefficients corresponding to the signal amplitude of the digital baseband signal and the signal amplitude of the digital baseband signal comprises: The mth group of output values ​​in the nth output value set is determined by the following steps, wherein the third output signal includes the nth output value set corresponding to the nth sampling point in the digital baseband signal, n is a positive integer greater than or equal to 1, and the nth output value set includes M c Group output value, M c is the preset third maximum delay number, and m is greater than or equal to 0 and less than or equal to M c A positive integer, the mth group of output values ​​includes output values and exist When the signal amplitude of is located in the kth amplitude interval among the preset S amplitude intervals, a preset set of coefficients corresponding to the kth amplitude interval is obtained, wherein, is the nth sampling point in the digital baseband signal, the third set of coefficients includes the preset set of coefficients, the preset set of coefficients includes coefficients and coefficient And the coefficient and coefficient Wherein, S is a positive integer greater than or equal to 2, and k is a positive integer greater than or equal to 1 and less than or equal to S; The coefficient and The signal amplitude is multiplied to obtain a ninth product, and the ninth product is multiplied by the coefficient Add together to get the output value in, is the value of the (nm)th sampling point in the digital baseband signal; The coefficient and The signal amplitude is multiplied to obtain the tenth product, and the tenth product is multiplied by the coefficient Add together to get the output value 14. The method according to claim 13, characterized in that Determining the third initial predistortion signal according to the third output signal and the digital baseband signal comprises: The output value and the output value Input the target filter and get the third filter output value And the fourth filter output value The The third filter output value Multiply them and get M c eleventh product, and the M c The eleventh products are added together to obtain the fifth sum; The and the fourth filtered output value Multiply them and get M c The twelfth product, and the M c The twelfth products are added together to obtain the sixth sum; The sixth summation value and v c The product of (n) is determined as the third target sum value, where v c (n) is the value of the nth sampling point in the preset trap state signal; The fifth sum value and the third target sum value are added to obtain a value of the nth sampling point in the third initial predistortion signal.

15. The method according to any one of claims 1 to 14, characterized in that The determining a target predistortion signal according to the first initial predistortion signal, the second initial predistortion signal and the third initial predistortion signal comprises: The first initial predistortion signal, the second initial predistortion signal, and the third initial predistortion signal are summed to obtain the target predistortion signal.

16. The method according to any one of claims 1 to 14, characterized in that The linear operation includes a multiplication operation and an addition operation, and the nonlinear operation includes an exponential operation.

17. A radio frequency chip, characterized in that: include: A plurality of predistortion processing units, used for processing the digital baseband signal to obtain a plurality of initial predistortion signals, wherein the plurality of predistortion processing units have the same amplitude selection affine amplitude selection affine function generation module, and the amplitude selection affine function generation module is used for performing linear operation on the amplitude of the signal sampling point in the digital baseband signal; The merging unit is used to determine a target predistortion signal according to a plurality of initial predistortion signals.

18. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program executes the method described in any one of claims 1 to 16 when executed by a processor.

19. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 16.

Images