A predistorter processing method and apparatus, an electronic device, and a medium

Abstract

The application discloses a pre-distortion processor processing method and device, electronic equipment and medium, and the method comprises the following steps: finding corresponding multi-order nonlinear terms from a parameter lookup table; calculating corresponding product terms and values by using the multi-order nonlinear terms and pre-distortion coefficients of an updated pre-distortion model; performing product calculation on the product term values and corresponding data terms of an input signal to obtain a product calculation result; and performing accumulation calculation on the product calculation result to complete pre-distortion processing and obtain a corresponding output signal. The application no longer needs to use complex complex number calculation, and can quickly perform pre-distortion processing by using product calculation and accumulation calculation.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a predistorter processing method, apparatus, electronic device, and medium. Background Technology

[0002] Predistortion involves artificially adding a system whose characteristics are exactly opposite to the nonlinear distortion of the system, including the power amplifier, to compensate for each other. It does not have stability issues and has a large bandwidth.

[0003] Currently, the market's digital predistortion processing models mainly adopt indirect learning. This learning structure adds a learner (coefficient estimator) with the same structure as the predistorter in the feedback path. This learning structure is located after the power amplifier (PA). It solves the coefficient estimate based on the output of the power amplifier PA. After learning, the coefficient estimate is copied to the predistorter. However, this results in increased computational complexity, leading to long computation time and slow convergence speed for the predistorter. Summary of the Invention

[0004] The purpose of this invention is to provide a predistorter processing method, apparatus, electronic device, and medium that eliminates the need for complex complex number calculations and improves predistortion processing efficiency by utilizing product and summation calculations.

[0005] In a first aspect, to achieve the above objective, embodiments of the present invention provide a predistorter processing method, comprising the steps of:

[0006] Find the corresponding multi-order nonlinear term from the parameter lookup table;

[0007] The product terms and values ​​are calculated by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model.

[0008] The product calculation result is obtained by performing a product calculation based on the sum of the product terms and the data terms corresponding to the input signal;

[0009] The product calculation results are accumulated to complete the pre-distortion processing and obtain the corresponding output signal.

[0010] In a second aspect, to address the same technical problem, embodiments of the present invention provide a predistorter processing apparatus, comprising:

[0011] The lookup module is used to find the corresponding multi-order nonlinear terms from the parameter lookup table;

[0012] The calculation module is used to calculate the corresponding product terms and values ​​based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model.

[0013] The calculation module is also used to perform product calculation based on the sum of the product terms and the data terms corresponding to the input signal to obtain the product calculation result;

[0014] The processing module is used to perform pre-distortion processing by multiplying and accumulating the product terms and the corresponding data terms of the input signal.

[0015] In a third aspect, in order to solve the same technical problem, embodiments of the present invention provide an electronic device including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the memory being coupled to the processor, and the processor executing the computer program to implement the steps in the predistorter processing method described in any of the preceding claims.

[0016] In a fourth aspect, in order to solve the same technical problem, embodiments of the present invention provide a computer-readable storage medium storing a computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to perform the steps in the predistorter processing method described in any of the preceding claims.

[0017] This invention provides a predistorter processing method, apparatus, electronic device, and medium. This invention utilizes pre-stored multi-order nonlinear terms for predistortion processing, which can reduce the amount of complex mathematical calculations, simplify the predistortion model to be equivalent to multiplication and accumulation, reduce running time, and accelerate convergence speed. Attached Figure Description

[0018] Figure 1 This is a schematic flowchart of a predistorter processing method provided in an embodiment of the present invention;

[0019] Figure 2 This is another schematic flowchart of the predistorter processing method provided in an embodiment of the present invention;

[0020] Figure 3 A simplified diagram of the predistorter and power amplifier (PA) processing provided in an embodiment of the present invention;

[0021] Figure 4 This is another schematic flowchart of the predistorter processing method provided in an embodiment of the present invention;

[0022] Figure 5 n and a provided for embodiments of the present invention kmq a 0m A diagram illustrating the relationship between b(m);

[0023] Figure 6 This is a schematic diagram of the predistorter processing device provided in an embodiment of the present invention;

[0024] Figure 7 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] It should be understood that the steps described in the method embodiments of this disclosure may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this disclosure is not limited in this respect.

[0027] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0028] Please see Figure 1 , Figure 1 This is a flowchart illustrating a predistorter processing method provided in an embodiment of the present invention, wherein the method includes steps S101 to S103.

[0029] S101. Find the corresponding multi-order nonlinear term from the parameter lookup table;

[0030] Specifically, before calculating the corresponding product term and value based on pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model, the following steps are included:

[0031] An updated predistortion model is generated based on the obtained updated model parameters; the model parameters include the order, memory depth, latency, and coefficients of the predistortion model.

[0032]

[0033] Wherein, Z(n) is the predistortion model, k is the order of the predistortion model, q is the memory depth of the predistortion model, m is the latency of the predistortion model, and a kmq The coefficients of the predistortion model are given. Additionally, x(nm) represents the input signal under time delay, and K, M, and Q are all constants.

[0034] Specifically, before calculating the corresponding product term and value based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model, the process further includes the following steps:

[0035] The corresponding multi-order nonlinear terms are obtained by decomposing and calculating the predistortion model.

[0036] Specifically, after obtaining the predistortion model according to the above process, the predistortion model is decomposed into multiple terms to obtain multi-order nonlinear terms. Among them, in the predistortion technology based on memory polynomials, the commonly used methods for solving the predistortion are LU decomposition, Cholisky decomposition, QR decomposition, inversion method, singular value decomposition method, etc.

[0037] The multi-order nonlinear terms are stored and corresponding index values ​​are generated; the index values ​​are bound to the multi-order nonlinear terms.

[0038] S102. Calculate the corresponding product terms and values ​​by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model.

[0039] Specifically, after finding the corresponding multi-order nonlinear term from the parameter lookup table based on the index value, the pre-distortion coefficient and the found multi-order nonlinear term are substituted into the following formula to calculate the sum of the product terms;

[0040] b(m) = sum(a) kmq ·y(k, nq)+a 0m )

[0041] Where b(m) is the sum of the product terms, a kmq Here are the coefficients of the predistortion model, y(k, nq) is the multi-order nonlinear term, and a 0m It is a constant.

[0042] S103. Perform product calculation based on the sum of the product terms and the data terms corresponding to the input signal to obtain the product calculation result;

[0043] S104. The product calculation results are accumulated to complete the pre-distortion processing to obtain the corresponding output signal.

[0044] Specifically, the step of performing pre-distortion processing by accumulating the product calculation results to obtain the corresponding output signal includes the following steps:

[0045]

[0046] Z(n)=sum[x(nm)·b(m)], m=0,…,M-1

[0047] Wherein, Z(n) is the predistortion model, k is the order of the predistortion model, q is the memory depth of the predistortion model, m is the latency of the predistortion model, and a kmq Here are the coefficients of the predistortion model, sum is the cumulative calculation symbol, b(m) is the sum of the product terms, and a 0m K, M, and Q are all constants.

[0048] Digital predistortion introduces a nonlinear module in the transmit channel before the power amplifier. This module's transmission characteristics are opposite to those of the power amplifier. The signal is preprocessed by the predistorter, whose output serves as the input signal to the power amplifier. The predistorter compensates for the nonlinear distortion generated by the power amplifier. After passing through the cascaded predistorter and power amplifier, the output signal exhibits a linear relationship with the input signal. By employing predistortion technology, predetermined amplitude and phase distortions are introduced into the signal before it enters the power amplifier. Because the characteristic curves of the predistorter and the power amplifier are opposite, the predistorted signal undergoes nonlinear cancellation after passing through the power amplifier.

[0049] This invention utilizes pre-stored multi-order nonlinear terms for predistortion processing, reducing the computational burden of complex mathematical operations. It simplifies the predistortion model, making it equivalent to multiplication and summation, thus reducing runtime and accelerating convergence. This invention eliminates the need for complex complex calculations; multiplication and summation significantly improve predistortion processing efficiency.

[0050] Reference Figure 2 , Figure 2 This is a flowchart illustrating a predistorter processing method provided in an embodiment of the present invention, wherein the method includes steps S201 to S203.

[0051] S201. Obtain the feedback signal from the power amplifier;

[0052] S202, The input signal and feedback signal are processed to generate corresponding predistortion coefficients; the data processing includes alignment processing and matrix operations;

[0053] S203. Store the predistortion coefficients in the parameter lookup table to complete the update.

[0054] Specifically, due to the nonlinear characteristics of power amplifiers, distortion occurs. To compensate for this distortion, a predistortion function is added to the digital signal to fit the amplifier coefficients. Predistortion is essentially the inverse problem of the power amplifier response. For example... Figure 3 The diagram shows a simplified processing flow of the predistorter F(|Vi|) and power amplifier G(|Vp|), where yd(t) is the input signal, x(t) is the predistorted signal, y(t) is the output signal, and H... -1[] represents the matrix of the predistorted signal, and H[] represents the matrix of the output signal.

[0055] The step of obtaining the feedback signal from the power amplifier and correcting the feedback signal includes the following steps:

[0056] The feedback signal is obtained by attenuating, down-converting, and analog-to-digital converting the signal output from the power amplifier.

[0057] Specifically, such as Figure 4 As shown, the predistortion model is as follows:

[0058]

[0059] By fitting the predistorter to the power amplifier, and by performing operations on K and Q in the predistorter first, we can obtain...

[0060]

[0061] Decomposed as follows

[0062]

[0063] and It is a constant, which can be pre-summed and provided as a constant, assuming that the present invention sets... The formula obtained after the above decomposition is as follows:

[0064]

[0065] And |x(nq)| k Since each value will be called multiple times, they can be calculated once and stored in memory, represented as y(k, nq). Therefore, the above formula can be further calculated as follows:

[0066]

[0067] Essentially, it's a calculation involving the multiplication of a real number and a complex number. For example, assuming K = 3 and Q = 4, the expression can be expanded as follows:

[0068]

[0069] like Figure 5 As shown, the output has 8 multiplicative terms and one single term. Each coefficient is repeated 32 times throughout the line. In lines 3-6, the next line's y(1, n) is a 1-element shift of the previous line's y(1, n). In lines 7-10, the next line's y(2, n) is a 1-element shift of the previous line's y(2, n). Assume b(m) is... Figure 5The sum of each column in the table shown is repeated M times to obtain b(0), ..., b(M-1).

[0070] This invention receives an updated coefficient table and determines the values ​​of K, M, and Q. Then, it calculates y(k, nq) and saves it to the storage module. Finally, it retrieves y(k, nq) from the storage module along with the coefficient a. kmq Multiply. Based on the values ​​of K, M, and Q, sum the above product terms and a. 0m The sum is denoted as b(m). This is used to calculate x(nm)*b(m) for a given value of n and the input signal. Then, x(nm)*b(m) is summed M times. For a given value of n, the predistorter operation is complete. The above steps are repeated to calculate all input signals to achieve the desired predistortion effect.

[0071] For example, let K = 3, M = 2, Q = 4

[0072] Then z(n) = sum[x(nm)*b(m)] = x(n-0)*b(0) + x(n-1)*b(1)

[0073] When n=1

[0074] Z(1)=x(1)*b(0)+x(0)*b(1)

[0075] =x(1)*[a 100 ·y(1,1)+a 101 ·y(1,0)+a 102 ·y(1,-1)+a 103 ·y(1,-2)+a 200 ·y(2,1)+a 201 ·y(2,0)+a 202 ·y(2,-1)+a 203 ·y(2,-2)+a 00 ]+x(0)*[a 110 ·y(1,1)+a 111 ·y(1,0)+a 112 ·y(1,-1)+a 113 ·y(1,-2)+a 210 ·y(2,1)+a 211 ·y(2,0)+a 212 ·y(2,-1)+a 213 ·y(2,-2)+a 01 ]

[0076] z(1) can be calculated through the above process. Similarly, all sample signals n = 0, 1, 2, ... N, where N is a natural number, can be calculated by analogy.

[0077] Please see Figure 6 , Figure 6 A schematic diagram of a predistorter processing device provided in an embodiment of the present invention includes:

[0078] The lookup module 701 is used to find the corresponding multi-order nonlinear term from the parameter lookup table;

[0079] The calculation module 702 is used to calculate the corresponding product terms and values ​​based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model.

[0080] The calculation module 702 is further configured to perform product calculation based on the sum of the product terms and the data terms corresponding to the input signal to obtain the product calculation result;

[0081] The processing module 703 is used to perform pre-distortion processing by multiplying and accumulating the product term and the data term corresponding to the input signal.

[0082] In specific implementation, the above modules and / or units can be implemented as independent entities, or they can be arbitrarily combined and implemented as the same or several entities. For the specific implementation of the above modules and / or units, please refer to the previous method embodiments. For the specific beneficial effects that can be achieved, please also refer to the beneficial effects in the previous method embodiments, which will not be repeated here.

[0083] Furthermore, the electronic device provided in this embodiment of the invention can be a mobile terminal such as a smartphone or tablet computer. The electronic device includes a processor and a memory. The processor and the memory are electrically connected.

[0084] The processor is the control center of an electronic device. It connects various parts of the electronic device through various interfaces and lines. By running or loading applications stored in memory and calling data stored in memory, it performs various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole.

[0085] In this embodiment, the processor in the electronic device loads the instructions corresponding to the processes of one or more applications into the memory according to the following steps, and then the processor runs the applications stored in the memory to achieve various functions:

[0086] Find the corresponding multi-order nonlinear term from the parameter lookup table;

[0087] The product terms and values ​​are calculated by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model.

[0088] The product calculation result is obtained by performing a product calculation based on the sum of the product terms and the data terms corresponding to the input signal;

[0089] The product calculation results are accumulated to complete the pre-distortion processing and obtain the corresponding output signal.

[0090] This electronic device can implement the steps in any embodiment of the predistorter processing method provided in the embodiments of the present invention. Therefore, it can achieve the beneficial effects that any predistorter processing method provided in the embodiments of the present invention can achieve, as detailed in the preceding embodiments, and will not be repeated here.

[0091] Please see Figure 7 , Figure 7 Another structural schematic diagram of the electronic device provided in the embodiment of the present invention, such as... Figure 7 As shown, Figure 7 A specific structural block diagram of an electronic device provided in an embodiment of the present invention is shown. This electronic device can be used to implement the predistorter processing method provided in the above embodiments. The electronic device 900 can be a mobile terminal such as a smartphone or a laptop computer.

[0092] RF circuit 910 is used to receive and transmit electromagnetic waves, converting electromagnetic waves into electrical signals and vice versa, thereby enabling communication with communication networks or other devices. RF circuit 910 may include various existing circuit elements used to perform these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, Subscriber Identity Module (SIM) cards, memory, etc. RF circuit 910 can communicate with various networks such as the Internet, corporate intranets, and wireless networks, or communicate with other devices via wireless networks. The aforementioned wireless networks may include cellular telephone networks, wireless local area networks (WLANs), or metropolitan area networks (MANs). The aforementioned wireless networks may use various communication standards, protocols, and technologies, including but not limited to Global System for Mobile Communication (GSM), Enhanced Data GSM Environment (EDGE), Wideband Code Division Multiple Access (WCDMA), Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Wireless Fidelity (Wi-Fi) (such as IEEE 802.11a, IEEE 802.11b, IEEE 802.11g, and / or IEEE 802.11n), Voice over Internet Protocol (VoIP), Worldwide Interoperability for Microwave Access (Wi-Max), other protocols for email, instant messaging, and short messages, and any other suitable communication protocols, including those that have not yet been developed.

[0093] The memory 920 can be used to store software programs and modules, such as the program instructions / modules corresponding to the predistorter processing method in the above embodiments. The processor 980 executes the software programs and modules stored in the memory 920. One or more programs are stored in the memory and configured to be executed by one or more processors. One or more programs contain instructions for performing the following operations:

[0094] Find the corresponding multi-order nonlinear term from the parameter lookup table;

[0095] The product terms and values ​​are calculated by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model.

[0096] The product calculation result is obtained by performing a product calculation based on the sum of the product terms and the data terms corresponding to the input signal;

[0097] The product calculation results are accumulated to complete the pre-distortion processing and obtain the corresponding output signal.

[0098] Memory 920 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, memory 920 may further include memory remotely located relative to processor 980, which can be connected to electronic device 900 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0099] The input unit 930 can be used to receive input digital or character information, and to generate keyboard, mouse, joystick, optical, or trackball signal inputs related to user settings and function control. Specifically, the input unit 930 may include a touch-sensitive surface 931 and other input devices 932. The touch-sensitive surface 931, also known as a touch display screen or touchpad, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch-sensitive surface 931), and drive the corresponding connection device according to a pre-set program. Optionally, the touch-sensitive surface 931 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, sends it to the processor 980, and can receive and execute commands from the processor 980. In addition, the touch-sensitive surface 931 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch-sensitive surface 931, the input unit 930 may also include other input devices 932. Specifically, other input devices 932 may include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0100] Display unit 940 can be used to display information input by the user or information provided to the user, as well as various graphical user interfaces of electronic device 900. These graphical user interfaces can be composed of graphics, text, icons, video, and any combination thereof. Display unit 940 may include display panel 941, which may optionally be configured as an LCD (Liquid Crystal Display), OLED (Organic Light-Emitting Diode), or similar form. Further, touch-sensitive surface 931 may cover display panel 941. When touch-sensitive surface 931 detects a touch operation on or near it, it transmits the information to processor 980 to determine the type of touch event. Subsequently, processor 980 provides corresponding visual output on display panel 941 according to the type of touch event. Although in the figures, touch-sensitive surface 931 and display panel 941 are implemented as two separate components to achieve input and output functions, in some embodiments, touch-sensitive surface 931 and display panel 941 can be integrated to achieve input and output functions.

[0101] Electronic device 900 may also include at least one sensor 950, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 941 according to the ambient light level, and the proximity sensor can generate an interruption when the flip is closed or shut down. As a type of motion sensor, a gravity acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that recognize the phone's posture (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. Other sensors that electronic device 900 may be configured with, such as gyroscopes, barometers, hygrometers, thermometers, and infrared sensors, will not be described in detail here.

[0102] Audio circuitry 960, speaker 961, and microphone 962 provide an audio interface between the user and electronic device 900. Audio circuitry 960 converts received audio data into electrical signals and transmits them to speaker 961, where speaker 961 converts them into sound signals for output. Conversely, microphone 962 converts collected sound signals into electrical signals, which are then received by audio circuitry 960, converted back into audio data, and processed by processor 980. The audio data is then transmitted via RF circuitry 910 to, for example, another terminal, or output to memory 920 for further processing. Audio circuitry 960 may also include an earphone jack to facilitate communication between peripheral headphones and electronic device 900.

[0103] Electronic device 900, through transmission module 970 (e.g., Wi-Fi module), can help users receive requests, send information, etc., providing users with wireless broadband internet access. Although transmission module 970 is shown in the figure, it is understood that it is not an essential component of electronic device 900 and can be omitted as needed without changing the essence of the invention.

[0104] The processor 980 is the control center of the electronic device 900. It connects to various parts of the phone via various interfaces and lines, and performs various functions and processes data of the electronic device 900 by running or executing software programs and / or modules stored in the memory 920, and by calling data stored in the memory 920, thereby providing overall monitoring of the electronic device. Optionally, the processor 980 may include one or more processing cores; in some embodiments, the processor 980 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may also not be integrated into the processor 980.

[0105] The electronic device 900 also includes a power supply 990 (such as a battery) that supplies power to various components. In some embodiments, the power supply may be logically connected to the processor 980 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. The power supply 990 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0106] In practice, the above modules can be implemented as independent entities or combined in any way to be implemented as the same or several entities. For the specific implementation of the above modules, please refer to the previous method implementation examples, which will not be repeated here.

[0107] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. Therefore, embodiments of the present invention provide a storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps of any embodiment of the predistorter processing method provided by the present invention.

[0108] Find the corresponding multi-order nonlinear term from the parameter lookup table;

[0109] The product terms and values ​​are calculated by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model.

[0110] The product calculation result is obtained by performing a product calculation based on the sum of the product terms and the data terms corresponding to the input signal;

[0111] The product calculation results are accumulated to complete the pre-distortion processing and obtain the corresponding output signal.

[0112] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0113] Since the instructions stored in the storage medium can execute the steps in any embodiment of the predistorter processing method provided in the embodiments of the present invention, the beneficial effects that any predistorter processing method provided in the embodiments of the present invention can achieve can be realized, as detailed in the preceding embodiments, and will not be repeated here.

[0114] The foregoing has provided a detailed description of a predistorter processing method, apparatus, electronic device, and storage medium provided by embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention. Moreover, those skilled in the art can make several improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A predistorter processing method, characterized in that, Including the following steps: Find the corresponding multi-order nonlinear term from the parameter lookup table; The product terms and values ​​are calculated by combining the multi-order nonlinear terms and the predistortion coefficients of the updated predistortion model. The product calculation result is obtained by performing a product calculation based on the sum of the product terms and the data terms corresponding to the input signal; The product calculation results are accumulated to complete the pre-distortion processing and obtain the corresponding output signal; The step of finding the corresponding multi-order nonlinear term from the parameter lookup table includes: finding the corresponding multi-order nonlinear term from the parameter lookup table according to the index value; The step of calculating the product term sum value by combining the multi-order nonlinear term and the predistortion coefficient of the updated predistortion model includes: substituting the predistortion coefficient and the found multi-order nonlinear term into the following formula to calculate the product term sum value; Where b(m) is the sum of the product terms, a kmq The coefficients of the predistortion model are... Let a be the multi-order nonlinear term. 0m It is a constant; The step of accumulating the product calculation results to complete the pre-distortion processing and obtain the corresponding output signal includes: Where Z(n) is the predistortion model, k is the order of the predistortion model, q is the memory depth of the predistortion model, m is the time delay of the predistortion model, and a kmq Here are the coefficients of the predistortion model, sum is the cumulative calculation symbol, b(m) is the sum of the product terms, and a 0m K, M, and Q are all constants.

2. The predistorter processing method according to claim 1, characterized in that, Before calculating the corresponding product term and value based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model, the following steps are included: An updated predistortion model is generated based on the obtained updated model parameters; the model parameters include the order, memory depth, latency, and coefficients of the predistortion model. Where Z(n) is the predistortion model, k is the order of the predistortion model, q is the memory depth of the predistortion model, m is the time delay of the predistortion model, and a kmq The coefficients of the predistortion model are K, M, and Q, which are all constants.

3. The predistorter processing method according to claim 1, characterized in that, The steps before generating the updated predistortion model based on the obtained updated model parameters include: Obtain the feedback signal from the power amplifier; The input signal and feedback signal are processed to generate corresponding predistortion coefficients; the data processing includes alignment processing and matrix operations. The predistortion coefficients are stored in the parameter lookup table to complete the update.

4. The predistorter processing method according to claim 3, characterized in that, The step of obtaining the feedback signal from the power amplifier includes: The feedback signal is obtained by attenuating, down-converting, and analog-to-digital converting the signal output from the power amplifier.

5. The predistorter processing method according to any one of claims 1-4, characterized in that, Before calculating the corresponding product term and value based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model, the following steps are included: The corresponding multi-order nonlinear terms are obtained by decomposing and calculating the predistortion model. The multi-order nonlinear terms are stored and corresponding index values ​​are generated; the index values ​​are bound to the multi-order nonlinear terms.

6. A predistorter processing apparatus, characterized in that, include: The lookup module is used to find the corresponding multi-order nonlinear terms from the parameter lookup table; The calculation module is used to calculate the corresponding product terms and values ​​based on the pre-stored multi-order nonlinear terms and the pre-distortion coefficients of the updated pre-distortion model. The calculation module is also used to perform product calculation based on the sum of the product terms and the data terms corresponding to the input signal to obtain the product calculation result; The processing module is used to multiply and accumulate the product terms and the corresponding data terms of the input signal to complete the predistortion processing; The search module is also used to find the corresponding multi-order nonlinear term from the parameter lookup table based on the index value. The calculation module is also used to substitute the predistortion coefficients and the found multi-order nonlinear terms into the following formula to calculate the sum of the product terms; Where b(m) is the sum of the product terms, a kmq The coefficients of the predistortion model are... Let a be the multi-order nonlinear term. 0m It is a constant; The processing module is also used for Where Z(n) is the predistortion model, k is the order of the predistortion model, q is the memory depth of the predistortion model, m is the time delay of the predistortion model, and a kmq Here are the coefficients of the predistortion model, sum is the cumulative calculation symbol, b(m) is the sum of the product terms, and a 0m K, M, and Q are all constants.

7. An electronic device, characterized in that, The method includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the memory being coupled to the processor, and the processor executing the computer program to implement the steps of the predistorter processing method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the steps of the predistorter processing method as described in any one of claims 1 to 5.

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