Nonlinear distortion compensation methods, models, and communication systems for signals

Abstract

The disclosed signal nonlinear distortion compensation method, model, and communication system relate to the wireless communication technology field. In this disclosure, a preset nonlinear compensation fusion model is used to perform DPD processing, CFR processing, and error compensation processing on an initial OFDM signal to obtain a nonlinear distortion-compensated initial OFDM signal. In this nonlinear compensation fusion model, the BL-DPD module, BL-CFR module, and error compensation module are arranged in parallel, avoiding the technical drawbacks of the prior art, where the DPD module is applied after the CFR module, which increases the requirements for the ADC / DAC sampling rate and the requirements for hardware and algorithm convergence speed, thereby increasing the difficulty and cost of system implementation. This not only reduces the requirements for the ADC / DAC sampling rate, but also improves the DPD compensation ability for power amplifier nonlinearities, thereby improving the communication and sensing performance of the OFDM system.

Description

Technical Field

[0001] The present disclosure relates to the field of wireless communication technologies, and particularly to a method, model, and communication system for compensating for non-linear distortion of signals.

Background Art

[0002] Orthogonal Frequency Division Multiplexing (OFDM) technology is a multi-carrier modulation technology that divides a carrier into a plurality of mutually orthogonal sub-carriers to solve frequency-selective fading and narrow-band interference.

[0003] Therefore, a signal modulated using OFDM technology, that is, an OFDM signal, usually has characteristics such as non-constant envelope, wide (frequency) band, and Peak-to-Average Power Ratio (PAPR, abbreviated as peak-to-average ratio). However, when an OFDM signal passes through a Power Amplifier (PA, abbreviated as power amplifier), it is inevitable that non-linear distortion will occur.

[0004] First, in order to make the signal output from the power amplifier have good linearity, usually, a simple power back-off method is used, but this method reduces the efficiency of the power amplifier and wastes resources. And in order to improve the efficiency of the power amplifier, usually, the power amplifier is operated near the saturation point, but this causes serious in-band distortion, increases the bit error rate of the communication system, and also causes out-of-band spectrum spreading and interference with adjacent channels.

[0005] In light of this, conventionally, to improve the effects of nonlinear distortion in power amplifiers, crest factor reduction (CFR) and digital pre-distortion (DPD) techniques are typically used. Here, CFR technique reduces the PAPR of the signal by lowering the signal peak. As the PAPR of the signal is reduced in this way, the backoff value of the power amplifier relative to the output peak power at the average power operating point can be reduced, thereby improving the efficiency of the power amplifier. DPD technique is an effective method for compensating for the nonlinear and memory effects of power amplifiers in the high-efficiency range. As described above, by combining CFR and DPD techniques, the application needs of improving power amplifier efficiency and improving the linearity index can be simultaneously satisfied.

[0006] Therefore, in related technologies, CFR modules and DPD modules can usually be cascaded to improve power amplifier efficiency and linearity. Furthermore, in technical means that combine conventional CFR and DPD technologies, the DPD module is usually applied after the CFR module.

[0007] However, by cascading the CFR module and the DPD module, the DPD module is applied after the CFR module. As a result, the PARA of the signal, which has been peak-clipped and its PAPR reduced via the CFR module, increases again after passing through the DPD module. Furthermore, due to the nonlinearity of the power amplifier, spectral spread occurs in the output signal. This increases the requirements for the sampling rate of the analog-to-digital converter (ADC) / digital-to-analog converter (DAC) in the OFDM system, as well as the hardware and algorithm convergence speed, thereby increasing the difficulty and cost of realizing the system.

[0008] Therefore, reducing the sampling rate requirements of ADCs / DACs while simultaneously improving the DPD's ability to compensate for nonlinearities in power amplifiers are currently technical challenges that need to be addressed. [Overview of the project]

[0009] Embodiments of this disclosure provide a method, model, and communication system for compensating for nonlinear distortion of signals to further improve the communication and sensing capabilities of OFDM systems by reducing the sampling rate requirements of ADC / DACs and improving the DPD's ability to compensate for nonlinearities in power amplifiers.

[0010] In a first embodiment, an embodiment of the present disclosure provides a method for compensating for nonlinear distortion of a signal, the method being: The method involves inputting an initial orthogonal wave frequency division multiplexed OFDM signal into a preset nonlinear compensation fusion model, the nonlinear compensation fusion model comprising a frequency band limiting-digital predistortion BL-DPD module, a frequency band limiting-crest factor reduction BL-CFR module, and an error compensation module, wherein the error compensation module performs error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module. Regarding the initial OFDM signal, the first OFDM signal processed by the BL-DPD module, the second OFDM signal processed by the BL-CFR module, and the third OFDM signal processed by the error compensation module are acquired, respectively. This includes obtaining an initial OFDM signal after nonlinear distortion compensation based on a first OFDM signal, a second OFDM signal, and a third OFDM signal.

[0011] In one preferred embodiment, the basis functions used by the BL-DPD module and the BL-CFR module are the same.

[0012] In one preferred embodiment, with respect to the initial OFDM signal, a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module are obtained, respectively. This includes modulating an initial OFDM signal based on the converged model parameter sets obtained in the offline modes of the BL-DPD module, BL-CFR module, and error compensation module, and acquiring the first OFDM signal, the second OFDM signal, and the third OFDM signal, respectively.

[0013] In one preferred embodiment, the model parameter set is: The combination of parameters consisting of kernel coefficients, nonlinear order, memory depth, and order of the low-order low-pass filter (LPF) of the BL-DPD module, The combination of parameters consisting of kernel coefficients, nonlinear order, memory depth, and order of the low-order LPF of the BL-CFR module, The combination of parameters consisting of kernel coefficients, nonlinear order, and memory depth of the error compensation module, It includes one of the following.

[0014] In one preferred embodiment, if the combination of parameters in the model parameter set consists of the kernel coefficients of the BL-DPD module, the nonlinear order, the memory depth, and the order of the low-order LPF, then the model parameter set is: The process involves inputting a sample OFDM signal in offline mode into the BL-DPD module and obtaining the sample OFDM signal after DPD processing, and Based on the sample OFDM signal after DPD processing and the conjugate parameter set corresponding to the initial parameter set of the BL-DPD module, the sample OFDM signal after inverse DPD processing is obtained. Based on the sample OFDM signal in offline mode and the sample OFDM signal after inverse DPD processing, the target DPD error signal is acquired, Based on a target DPD error signal and a preset low-noise variable step size—a least mean squares algorithm—the initial parameter set is iteratively modified until the absolute value of the target DPD error signal is smaller than the set threshold for the DPD error signal. This is obtained by using the initial parameter set after iterative correction as the model parameter set for the BL-DPD module.

[0015] In one preferred embodiment, the sample OFDM signal after inverse DPD processing is obtained based on the sample OFDM signal after DPD processing and the conjugate parameter set corresponding to the initial parameter set of the BL-DPD module. The sample OFDM signal after DPD processing is subjected to digital-to-analog conversion, upconverting, and power amplification in sequence, and the sample OFDM signal after power amplification is obtained. The process involves sequentially applying power attenuation, down-converting, and analog-to-digital conversion to the power-amplified sample OFDM signal, and obtaining the analog-to-digital converted sample OFDM signal. This includes obtaining a sample OFDM signal after inverse DPD processing, based on the sample OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the initial parameter set.

[0016] In one preferred embodiment, iterative modifications are made to the initial parameter set based on a target DPD error signal and a preset low-noise variable step size-least mean squares algorithm. Each time you modify the initial parameter set, Currently, the sample OFDM signal is in offline mode, and the sample OFDM signal corresponding to each of the multiple historical time points adjacent to it is obtained. Based on the historical DPD error signal corresponding to each of multiple sample OFDM signals, the average value of the DPD error signal of the sample OFDM signal at the current time in offline mode is obtained, Based on the average value of the DPD error signal, the step size factor at the previous historical time point adjacent to the current time, the target DPD error signal at the current time, and the historical DPD error signal at the previous historical time point, the first target step size factor is obtained. This includes modifying the initial parameter set at the current time based on the first target step size factor, the conjugate DPD error signal corresponding to the target DPD error signal at the current time, and the sample OFDM signal after analog-to-digital conversion, and obtaining and executing the modified initial parameter set.

[0017] In one preferred embodiment, before iteratively modifying the initial parameter set based on the target DPD error signal and a preset low-noise variable step size-least mean squares algorithm, If the absolute value of the target DPD error signal is greater than or equal to the threshold value of the DPD error signal, the initial parameter set is used as the model parameter set for the BL-DPD module.

[0018] In one preferred embodiment, if the combination of parameters in the model parameter set consists of the kernel coefficients of the BL-CFR module, the nonlinear order, the memory depth, and the order of the low-order LPF, then the model parameter set is: The sample OFDM signal in offline mode is input sequentially to the BL-DPD module and the preset CFR module, and the sample OFDM signal after DPD-CFR processing is obtained. Based on the sample OFDM signal in offline mode and the conjugate parameter set corresponding to the initial parameter set of the BL-CFR module, the sample OFDM signal after CFR processing is obtained, Based on the sample OFDM signal after DPD-CFR processing and the sample OFDM signal after CFR processing, the target CFR error signal is obtained. Based on the target CFR error signal and the preset low-noise variable step size - least mean square algorithm, iterative correction is performed on the initial parameter set until the absolute value of the target CFR error signal becomes smaller than the threshold value of the set CFR error signal, and The initial parameter set after iterative correction is used as the model parameter set of the BL-CFR module, and is obtained by

[0019] In a preferred embodiment, based on the target CFR error signal and the preset low-noise variable step size - least mean square algorithm, before performing iterative correction on the initial parameter set, When the absolute value of the target CFR error signal is greater than or equal to the threshold value of the CFR error signal, further including setting the initial parameter set directly as the model parameter set of the BL-CFR module.

[0020] In a preferred embodiment, when the combination of parameters of the model parameter set consists of the kernel coefficient, non-linear order, and memory depth of the error compensation module, the model parameter set Inputs the sample OFDM signal in the offline mode into the non-linear compensation fusion model and the preset high-order LPF respectively, and obtains the sample OFDM signal after non-linear distortion compensation and the sample OFDM signal after filtering processing, and Based on the sample OFDM signal after non-linear distortion compensation and the sample OFDM signal after filtering processing, obtains the target compensation error signal, and Based on the target compensation error signal and the preset low-noise variable step size - least mean square algorithm, iterative correction is performed on the initial parameter set of the error compensation module until the absolute value of the target compensation error signal becomes smaller than the threshold value of the set compensation error signal, and The initial parameter set after iterative correction is used as the model parameter set of the error compensation module, and is obtained by

[0021] In one preferred embodiment, before iteratively modifying the initial parameter set of the error compensation module based on the target compensation error signal and a preset low-noise variable step size-least mean squares algorithm, This further includes using the initial parameter set as the model parameter set for the error compensation module if the absolute value of the target compensation error signal is greater than or equal to the threshold of the compensation error signal.

[0022] In one preferred embodiment, after obtaining an initial OFDM signal after nonlinear distortion compensation based on the first OFDM signal, the second OFDM signal, and the third OFDM signal, Based on the initial OFDM signal after nonlinear distortion compensation and the conjugate parameter set corresponding to the model parameter set of the BL-DPD module, the initial OFDM signal after inverse DPD processing is obtained, Based on the initial OFDM signal after nonlinear distortion compensation and the initial OFDM signal after inverse DPD processing, the target distortion compensation error signal is obtained, This further includes iteratively modifying the model parameter set based on a target distortion compensation error signal and a preset sine and error variable step size-least mean squares algorithm until the absolute value of the target distortion compensation error signal is less than a set threshold for distortion compensation error.

[0023] In one preferred embodiment, the initial OFDM signal after inverse DPD processing is obtained based on the initial OFDM signal after nonlinear distortion compensation and the conjugate parameter set corresponding to the model parameter set of the BL-DPD module. The initial OFDM signal after nonlinear distortion compensation is subjected to sequential digital-to-analog conversion, upconverting, and power amplification processing to obtain the initial OFDM signal after power amplification. The initial OFDM signal after power amplification is subjected to sequential power attenuation, down-converting, and analog-to-digital conversion processing to obtain the initial OFDM signal after analog-to-digital conversion. This includes obtaining the initial OFDM signal after inverse DPD processing based on the initial OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the model parameter set.

[0024] In one preferred embodiment, iterative corrections are made to the model parameter set based on a target distortion compensation error signal and a preset sine and error variable step size-least mean squares algorithm. Each time you modify the model parameter set, Currently, we acquire sample OFDM signals after nonlinear distortion compensation, corresponding to each of several historical time points adjacent to the initial OFDM signal after nonlinear distortion compensation. Based on the hysteresis distortion compensation error signals corresponding to each of multiple nonlinear distortion-compensated sample OFDM signals, the average value of the distortion compensation error signal of the initial nonlinear distortion-compensated OFDM signal at the current time is obtained, The second target step size factor is obtained based on the error term corresponding to the mean value of the distortion compensation error signal, the target distortion compensation error signal at the current time, and the historical distortion compensation error signal at the previous historical time adjacent to the current time. This includes modifying the model parameter set at the current time based on the second target step size factor, the conjugate distortion compensation error signal corresponding to the target distortion compensation error signal at the current time, and the initial OFDM signal after analog-to-digital conversion, and obtaining and executing the modified model parameter set.

[0025] In one preferred embodiment, the method for compensating the nonlinear distortion of the signal is as follows: This further includes iteratively modifying the model parameter set of the BL-DPD module based on a set period time.

[0026] In a second embodiment, embodiments of the present disclosure further provide a nonlinear compensation fusion model comprising a BL-DPD module, a BL-CFR module, and an error compensation module, The BL-DPD module, BL-CFR module, and error compensation module are connected in parallel. The basis functions used by the BL-DPD module and the BL-CFR module are the same, and the error compensation module is used to perform error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module.

[0027] In one preferred embodiment, the basis functions used by the BL-DPD module and the BL-CFR module are the same.

[0028] In one preferred embodiment, the nonlinear compensation fusion model is Based on the initial OFDM signal, a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module are obtained. It is used to obtain an initial OFDM signal after nonlinear distortion compensation, based on the first OFDM signal, the second OFDM signal, and the third OFDM signal.

[0029] In one preferred embodiment, the nonlinear compensation fusion model further In offline mode, it is used to extract model parameter sets for the BL-DPD module, BL-CFR module, and error compensation module based on a preset low-noise variable step-size-least mean squares algorithm.

[0030] In one preferred embodiment, the nonlinear compensated fusion model is further used in online mode to refresh the model parameter set for the nonlinear compensated fusion model based on a preset sine and error variable step size-least mean squares algorithm and a set period time.

[0031] In one preferred embodiment, the nonlinear compensation fusion model is, specifically, In online mode, it is used to refresh the model parameter set only for the BL-DPD module in a nonlinear compensated fusion model, based on a preset sine and error variable step size-least mean squares algorithm and a set period time.

[0032] In a third aspect, embodiments of the present disclosure further provide an OFDM communication system comprising the nonlinear compensation fusion model described in the second aspect, a first branch, a second branch, a third branch, a fourth branch, In the nonlinear compensated fusion model, the BL-DPD module and the first branch are used in offline mode to iteratively modify the initial parameter set of the BL-DPD module and obtain the model parameter set of the BL-DPD module. In the nonlinear compensated fusion model, the BL-CFR module and the second branch are used in offline mode to iteratively modify the initial parameter set of the BL-CFR module and obtain the model parameter set of the BL-CFR module. The nonlinear compensated fusion model and the third bifurcation are used in offline mode to iteratively modify the initial parameter set of the error compensation module and obtain the model parameter set of the error compensation module. The nonlinear compensated fusion model and the fourth bifurcation are used in online mode to iteratively modify the model parameter set of the BL-DPD module.

[0033] In one preferred embodiment, the first branch comprises, in order, a digital-to-analog converter (DAC), an upconverter, a power amplifier (PA), an attenuator, a bandpass filter (BPF), a downconverter, an analog-to-digital converter (ADC), a training network (POST-BL-DPD) module, and a preset low-noise variable step-size-least mean squares algorithm module.

[0034] In one preferred embodiment, the second branch comprises a sequentially installed CFR module, a training network POST-BL-DPD module, and a preset low-noise variable step-size-least mean squares algorithm module.

[0035] In one preferred embodiment, the third branch comprises sequentially installed low-pass filters (LPFs) and a preset low-noise variable step-size-least mean squares algorithm module.

[0036] In one preferred embodiment, the fourth branch comprises, in order, a DAC, an upconverter, a PA, an attenuator, a BPF, a downconverter, an ADC, a training network POST-BL-DPD module, and a preset sine and error variable step size-least mean squares algorithm module.

[0037] In a fourth embodiment, an embodiment of the present disclosure provides an electronic device comprising a processor and a memory, wherein program code is stored in the memory, and when the program code is executed by the processor, the processor is caused to perform the steps of the nonlinear distortion compensation method for a signal described in the first embodiment.

[0038] In a fifth embodiment, an embodiment of the present disclosure provides a computer-readable storage medium containing program code, which, when executed by an electronic device, causes the electronic device to perform steps of the nonlinear distortion compensation method for a signal described in the first embodiment.

[0039] In a sixth embodiment, an embodiment of the present disclosure provides a computer program product which, when invoked by a computer, causes the computer to perform steps of the nonlinear distortion compensation method for signals described in the first embodiment.

[0040] The beneficial effects of this disclosure are as follows: In the nonlinear distortion compensation method for signals provided in the embodiments of this disclosure, DPD processing, CFR processing, and error compensation processing are performed on the initial OFDM signal based on a preset nonlinear compensation fusion model, thereby obtaining an initial OFDM signal after nonlinear distortion compensation based on a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module. In this way, by arranging the BL-DPD module, BL-CFR module, and error compensation module in parallel in the preset nonlinear compensation fusion model, the technical drawbacks of the prior art, where the DPD module is applied after the CFR module, which increases the requirements for the sampling rate of the ADC / DAC in the OFDM system, increases the hardware and algorithm convergence speed, and increases the difficulty and cost of realizing the system, are avoided. Therefore, the requirements for the sampling rate of the ADC / DAC are effectively reduced, and the DPD compensation capability for the nonlinearity of the power amplifier is improved, thereby further improving the communication capability and sensing capability of the OFDM system.

[0041] Furthermore, other features and advantages of this disclosure are described in the specification below, and some of them will be apparent from the specification or understood by implementing this disclosure. The purposes and other advantages of this disclosure can be realized and obtained by the configurations specifically shown in the specification, claims, and drawings described herein. [Brief explanation of the drawing]

[0042] To more clearly illustrate the technical means according to the embodiments of this disclosure, the drawings required for the embodiments are briefly described below. However, the drawings described below are merely a part of the embodiments of this disclosure, and it will be apparent to those skilled in the art that other drawings can be obtained from these drawings without requiring any creative effort.

[0043] [Figure 1] Figure 1 is a schematic diagram of the OFDM communication system provided in the embodiments of this disclosure. [Figure 2] Figure 2 is a schematic diagram illustrating the implementation flow of the nonlinear distortion compensation method for signals provided in the embodiments of this disclosure. [Figure 3] Figure 3 is a schematic diagram of the logic for processing the initial OFDM signal provided in the embodiments of this disclosure. [Figure 4] Figure 4 is a schematic flowchart illustrating a method for obtaining a model parameter set for a BL-DPD module provided in an embodiment of this disclosure. [Figure 5] Figure 5 is a schematic logic diagram illustrating how to acquire a sample OFDM signal after inverse DPD processing, as provided in the embodiments of this disclosure. [Figure 6] Figure 6 is a schematic diagram illustrating the implementation flow of a method for modifying the initial parameter set in offline mode, as provided in the embodiments of this disclosure. [Figure 7] Figure 7 is a schematic flowchart illustrating a method for obtaining a model parameter set for a BL-CFR module provided in an embodiment of this disclosure. [Figure 8] Figure 8 is a schematic flowchart illustrating a method for obtaining a model parameter set for an error compensation module provided in an embodiment of this disclosure. [Figure 9] Figure 9 is a schematic flowchart illustrating the implementation flow of a method for modifying a model parameter set in online mode, as provided in an embodiment of this disclosure. [Figure 10] Figure 10 is a schematic logic diagram illustrating how to acquire the initial OFDM signal after inverse DPD processing, as provided in the embodiments of this disclosure. [Figure 11] Figure 11 is a schematic diagram of a detailed implementation flow based on Figure 9 provided in the embodiments of this disclosure. [Figure 12] Figure 12 is a schematic diagram of the configuration of an electronic device provided in an embodiment of this disclosure. [Modes for carrying out the invention]

[0044] To further clarify the purpose, technical means, and advantages of the embodiments of this disclosure, the technical means of this disclosure will be described clearly and in detail below with reference to the drawings of the embodiments of this disclosure. It will be clear that the embodiments described are merely some, and not all, embodiments of the technical means of this disclosure. All other embodiments that a person skilled in the art could obtain without creative effort based on the embodiments described in this disclosure are all covered by the technical means of this disclosure.

[0045] In this disclosure, “multiple” is understood to mean “at least two.” The term “and / or” is solely for the purpose of describing the relationship between the associated objects, indicating that three types of relationships exist. For example, A and / or B can represent three situations: A existing alone, A and B existing simultaneously, and B existing alone. A being connected to B can represent two situations: A being directly connected to B, and A being connected to B via C. In this disclosure, terms such as “first,” “second,” etc., are used to distinguish the purpose of the explanation and should be understood as not indicating or suggesting relative importance or order.

[0046] The design concept of the embodiments of this disclosure will be briefly explained below. OFDM technology is a multi-carrier modulation technique that divides a carrier into multiple mutually orthogonal subcarriers, resolving frequency selective fading and narrowband interference. Therefore, OFDM signals are the global 5G standard (5G NR, 5th Generation Mobile Networks New Radio) communication signals based on a new OFDM air interface design, offering more choices for time slots, subcarriers, etc., within each subframe. This allows for application not only in different communication scenarios but also in different sensing scenarios.

[0047] Therefore, signals modulated using OFDM technology, i.e., OFDM signals, typically have characteristics such as a non-stationary envelope, wide bandwidth, and high PAPR. However, when an OFDM signal passes through a PA, nonlinear distortion is unavoidable.

[0048] Initially, a simple power backoff method was typically used to ensure good linearity in the signal output from the power amplifier. However, this method reduces the efficiency of the power amplifier and wastes resources. To improve the efficiency of the power amplifier, it is usually operated near its saturation point. However, this causes serious in-band distortion, increasing the bit error rate of the communication system, as well as out-of-band spread spectrum and interference with adjacent channels.

[0049] Currently, to mitigate the effects of nonlinear distortion in PAs, the advantages of both CFR and DPD technologies can be utilized, and by combining CFR and DPD technologies, the application needs and objectives of improving power amplifier efficiency and linearity can be simultaneously satisfied.

[0050] Specifically, in technical means that combine conventional CFR technology and DPD technology, the DPD module is usually applied after the CFR module. However, by cascading the CFR module and the DPD module, the DPD module is applied after the CFR module. As a result, the PAPR of the signal, which has been peak-clipped and reduced via the CFR module, increases again after passing through the DPD module. Furthermore, due to the nonlinearity of the power amplifier, spread spectrum occurs in the output signal. When implementing DPD, the bandwidth of the feedback receiving channel is 3 to 5 times the bandwidth of the input signal, and if the bandwidth is 400 MHz or more, the sampling rate of the ADC in the feedback receiving channel must be at least 4 Gsps. Such high-speed sampling ADCs not only increase the demands on hardware and algorithm convergence speed, but also increase the difficulty and cost of system implementation.

[0051] In light of this, by effectively reducing the sampling rate of the ADC / DAC and minimizing the impact of peak clipping (CFR) on the DPD effect, 5G To improve the communication and sensing capabilities of an NR (e.g., an OFDM system), embodiments of the present disclosure provide a nonlinear distortion compensation method, which specifically involves inputting an OFDM signal into a preset nonlinear compensation fusion model, the nonlinear compensation fusion model comprising a BL-DPD module, a BL-CFR module, and an error compensation module, wherein the error compensation module is used to perform error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module, and further includes acquiring a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module for an initial OFDM signal, and finally acquiring an initial OFDM signal after compensating for nonlinear distortion based on the first OFDM signal, the second OFDM signal, and the third OFDM signal.

[0052] In particular, preferred embodiments of the present disclosure will be described below with reference to the drawings of the specification. The preferred embodiments described herein are used solely to describe and interpret the present disclosure and are not intended to limit the present disclosure. It is understood that embodiments and features of the embodiments herein can be combined in any way that does not conflict with the present disclosure.

[0053] As shown in Figure 1, Figure 1 is a schematic diagram of the configuration of an OFDM communication system provided in an embodiment of the present disclosure, the OFDM communication system comprising a nonlinear compensation fusion model, a first branch, a second branch, a third branch, and a fourth branch.

[0054] The nonlinear compensation fusion model comprises a BL-DPD module, a BL-CFR module, and an error compensation module ECM. The BL-DPD module, BL-CFR module, and error compensation module ECM are connected in parallel, and the error compensation module ECM is used to perform error compensation on the OFDM signals output from the BL-DPD module and BL-CFR module.

[0055] Preferably, the basis functions used by the BL-DPD module and the BL-CFR module are the same.

[0056] The first branch comprises, in order, a DAC, an up-converter, a PA, an attenuator 1 / G, a band-pass filter (BPF), a down-converter, an ADC, a POST-BL-DPD training network module, and a preset low-noise variable step size-least mean square (LNVSS-LMS) algorithm module.

[0057] The second branch comprises sequentially installed CFR modules, a training network POST-BL-DPD module, and a preset low-noise variable step-size-least mean squares algorithm module.

[0058] The third branch comprises sequentially placed low-pass filters (LPFs) and a preset low-noise variable step-size-least mean squares algorithm module.

[0059] The fourth branch comprises, in order, a DAC, an upconverter, a PA, a 1 / G attenuator, a BPF, a downconverter, an ADC, a POST-BL-DPD training network module, and a preset Sine and Error Variable Step Size-Least Mean Square (SEVSS-LMS) algorithm module.

[0060] As described above, the only difference between the first and fourth branches is that the first branch uses the LNVSS-LMS algorithm, while the fourth branch uses the SEVSS-LMS algorithm. The LNVSS-LMS algorithm effectively suppresses the susceptibility of the step size factor function to noise by adjusting the change in the step size factor function based on parameters such as the error energy at the current time, the absolute error energy of the error at the previous time, and the mean value. This not only improves the noise suppression capability of the LNVSS-LMS algorithm, but also allows the parameter values ​​to be adjusted to be smaller than the error value at that time, thereby obtaining a smaller step size and a smaller steady-state error. The SEVSS-LMS algorithm controls the variable step size factor function by adjusting three parameters. As a result, the variable step size factor function automatically increases the step size in the initial stage when the error signal is large, resulting in a faster convergence speed. In the steady state, it can maintain a small step size, resulting in a slower convergence speed and a smaller error.

[0061] Furthermore, the above nonlinear compensation fusion model is also called the Compensation Band Limited-CFR-DPD (CBL-CFR-DPD) model.

[0062] Furthermore, the first, second, and third branches described above can share the same preset low-noise variable step-size-least mean squares algorithm module to reduce the overhead of the electrical circuit. The number of preset low-noise variable step-size-least mean squares algorithm modules is not limited in the embodiments of this disclosure.

[0063] In the embodiments of this disclosure, the nonlinear compensation fusion model is used to obtain an initial OFDM signal after nonlinear distortion compensation by performing DPD processing, CFR processing, and error compensation processing on the initial OFDM signal, respectively, and acquiring a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module, based on the first OFDM signal, the second OFDM signal, and the third OFDM signal.

[0064] In the nonlinear compensated fusion model, the BL-DPD module and the first branch are used in offline mode to iteratively modify the initial parameter set of the BL-DPD module and obtain the model parameter set of the BL-DPD module, that is, to extract the kernel parameters of the BL-DPD module in offline mode, where offline mode means that the initial OFDM signal is not received, i.e., the module / model (pre)training mode.

[0065] In the nonlinear compensated fusion model, the BL-CFR module and the second branch are used in offline mode to iteratively modify the initial parameter set of the BL-CFR module to obtain the model parameter set of the BL-CFR module, that is, to extract the kernel parameters of the BL-CFR module in offline mode.

[0066] The nonlinear compensation fusion model and the third bifurcation are used in offline mode to iteratively modify the initial parameter set of the error compensation module ECM to obtain the model parameter set of the error compensation module ECM, that is, to extract the kernel parameters of the error compensation module ECM in offline mode.

[0067] The nonlinear compensated fusion model and the fourth branch are used in online mode to iteratively modify the model parameter set of the BL-DPD module, that is, to effectively refresh the parameters of the nonlinear compensated fusion model (i.e., the CBL-CFR-DPD model) in online mode, thereby ultimately ensuring post-cascaded pre-distortion of the entire OFDM communication system, effectively improving the nonlinear distortion of the power amplifier of the OFDM signal, and improving the overall efficiency of the OFDM communication system. Here, online mode represents the reception of the initial OFDM signal, i.e., real-time operation mode.

[0068] Preferably, the nonlinear compensated fusion model is further used to extract model parameter sets for the BL-DPD module, BL-CFR module, and error compensation module in offline mode based on a preset low-noise variable step-size-least mean squares algorithm, and / or to refresh the model parameter set for the nonlinear compensated fusion model in online mode based on a preset sine and error variable step-size-least mean squares algorithm and a set period time. Preferably, the nonlinear compensated fusion model is specifically used to refresh the model parameter set only for the BL-DPD module in the nonlinear compensated fusion model in online mode based on a preset sine and error variable step-size-least mean squares algorithm and a set period time.

[0069] In Figure 1, "Mode" is understood to be a state selection module, and therefore the corresponding state may be either offline mode or online mode.

[0070] Based on the OFDM communication system described above, a new type of nonlinear compensation fusion model (i.e., a CBL-CFR-DPD integrated model) is constructed. The BL-DPD module and BL-CFR module are integrated into a single model using the error compensation module ECM. By utilizing a mechanism to extract and refresh each module's parameters (i.e., the model parameter set) in an "offline + online" manner, the order of the band-limiting filter is effectively reduced, the overall complexity of the nonlinear compensation fusion model is reduced, and the overall accuracy of the nonlinear compensation fusion model is ensured. In offline mode, parameters are extracted / modified for the BL-DPD module, BL-CFR module, and ECM module based on the LNVSS-LMS self-adaptive algorithm. In online mode, parameters are effectively refreshed / modified only for the BL-DPD module based on the SEVSS-LMS self-adaptive algorithm. Furthermore, this nonlinear compensation fusion model involves more addition and subtraction operations on several coefficients compared to a system that only uses the DPD module. As a result, the execution complexity of both is almost the same, and compared to conventional technical methods that apply the CFR module and DPD module independently, the execution complexity is reduced, and the compensation capability of the digital predistortor for the nonlinearity of the broadband power amplifier can be effectively improved.

[0071] The following describes a method for compensating for nonlinear distortion of signals provided in exemplary embodiments of this disclosure, based on the OFDM communication system described above, with reference to the drawings. The architecture of the system described above is provided for the purpose of easily understanding the spirit and principles of this disclosure, and the embodiments of this disclosure are not limited thereto.

[0072] Referring to Figure 2, Figure 2 is an implementation flow chart of a nonlinear distortion compensation method for signals provided in an embodiment of the present disclosure, which is applied to the OFDM communication system described above, and the detailed implementation flow of the method is as follows.

[0073] S201: Input the initial OFDM signal into the preset nonlinear compensated fusion model.

[0074] Here, the nonlinear compensation fusion model comprises a BL-DPD module, a BL-CFR module, and an error compensation module ECM, where the error compensation module ECMH is used to perform error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module.

[0075] Note that the basis functions used by the BL-DPD module and the BL-CFR module are the same, but the model parameter sets (i.e., coefficients) are different.

[0076] S202: For the initial OFDM signal, the first OFDM signal processed by the BL-DPD module, the second OFDM signal processed by the BL-CFR module, and the third OFDM signal processed by the error compensation module are acquired, respectively.

[0077] In one preferred embodiment, referring to Figure 3, when step S202 is performed, the nonlinear compensation fusion model modulates the initial OFDM signal based on the model parameter sets converged in the offline modes of the BL-DPD module, BL-CFR module, and error compensation module ECM, respectively, and acquires the first OFDM signal, the second OFDM signal, and the third OFDM signal, respectively, where the offline mode represents the absence of receiving the initial OFDM signal. Using this method, the initial OFDM signal is processed by three parallel modules, effectively avoiding the technical drawbacks of the prior art, where the DPD module is applied after the CFR module, which increases the demands on the ADC / DAC sampling rate in the OFDM system, as well as the demands on hardware and algorithm convergence speed, thereby increasing the difficulty and cost of system implementation.

[0078] JPEG0007846794000001.jpg37170

[0079] JPEG0007846794000002.jpg29170

[0080] JPEG0007846794000003.jpg37169

[0081] JPEG0007846794000004.jpg30170

[0082] JPEG0007846794000005.jpg38170

[0083] JPEG0007846794000006.jpg24170

[0084] Therefore, as described above, the above model parameter set is 1. Combinations of parameters consisting of kernel coefficients, nonlinear order, memory depth, and order of low-order LPF of the BL-DPD module, 2. Combinations of parameters consisting of kernel coefficients, nonlinear order, memory depth, and order of low-order LPF of the BL-CFR module, 3. Combinations of parameters consisting of kernel coefficients, nonlinear order, and memory depth of the error compensation module ECM, It includes one of the following.

[0085] S203: Based on the first OFDM signal, the second OFDM signal, and the third OFDM signal, an initial OFDM signal after nonlinear distortion compensation is obtained.

[0086] Specifically, when step S203 is executed, the nonlinear compensation fusion model can obtain a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module, and then obtain an initial OFDM signal after nonlinear distortion compensation based on the first OFDM signal, the second OFDM signal, and the third OFDM signal.

[0087] JPEG0007846794000007.jpg63169

[0088] The converged model parameter sets for the BL-DPD module, BL-CFR module, and error compensation module in offline mode are obtained through the nonlinear compensation fusion model and the first bifurcation, the nonlinear compensation fusion model and the second bifurcation, and the nonlinear compensation fusion model and the third bifurcation, respectively.

[0089] In one preferred embodiment, referring to Figure 4, if the combination of parameters in the model parameter set consists of the kernel coefficients of the BL-DPD module, the nonlinear order, the memory depth, and the order of the low-order LPF, the model parameter set is obtained as follows.

[0090] S401: A sample OFDM signal in offline mode is input to the BL-DPD module, and the sample OFDM signal after DPD processing is obtained.

[0091] For example, when step S401 is executed, it is assumed that the sample OFDM signal in offline mode is s(n), and the kernel processing of the BL-DPD module is performed to obtain the sample OFDM signal x(n) after DPD processing.

[0092] S402: Based on the sample OFDM signal after DPD processing and the conjugate parameter set corresponding to the initial parameter set of the BL-DPD module, the sample OFDM signal after inverse DPD processing is obtained.

[0093] In one preferred embodiment, referring to Figure 5, when step S402 is performed, the OFDM communication system, upon acquiring a sample OFDM signal after DPD processing, performs digital-to-analog conversion, up-converting, and power amplification processing sequentially on the sample OFDM signal after DPD processing via a first branch in offline mode, thereby acquiring a sample OFDM signal after power amplification. Then, performs power attenuation, down-converting, and analog-to-digital conversion processing sequentially on the sample OFDM signal after power amplification, thereby acquiring a sample OFDM signal after analog-to-digital conversion. Finally, based on the sample OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the initial parameter set, a sample OFDM signal after inverse DPD processing can be acquired.

[0094] JPEG0007846794000008.jpg66170

[0095] JPEG0007846794000009.jpg24169

[0096] JPEG0007846794000010.jpg35170

[0097] S403: The target DPD error signal is obtained based on the sample OFDM signal in offline mode and the sample OFDM signal after inverse DPD processing.

[0098] JPEG0007846794000011.jpg23170

[0099] JPEG0007846794000012.jpg13169

[0100] S404: Target DPD error signal and preset low-noise variable step size - Iteratively modify the initial parameter set until the absolute value of the target DPD error signal is smaller than the set threshold for the DPD error signal, based on the least mean squares algorithm.

[0101] JPEG0007846794000013.jpg57169

[0102] JPEG0007846794000014.jpg25170

[0103] S601: Acquire sample OFDM signals corresponding to each of multiple historical time points adjacent to the current sample OFDM signal in offline mode.

[0104] Exemplary, when step S601 is performed, the OFDM communication system obtains sample OFDM signals s(i) corresponding to each of several historical time points adjacent to the currently offline sample OFDM signal s(n), for example, obtaining the first N sample OFDM signals s(i), where i is an integer ∈ (1, N).

[0105] S602: Based on the historical DPD error signal corresponding to each of the multiple sample OFDM signals, the average value of the DPD error signal of the sample OFDM signal at the current time in offline mode is obtained.

[0106] JPEG0007846794000015.jpg25169

[0107] JPEG0007846794000016.jpg13170

[0108] S603: Obtain the first target step size factor based on the average value of the DPD error signal, the step size factor at the previous historical time adjacent to the current time, the target DPD error signal at the current time, and the historical DPD error signal at the previous historical time.

[0109] JPEG0007846794000017.jpg23170

[0110] JPEG0007846794000018.jpg70170

[0111] Furthermore, α and β mentioned above are predetermined according to the actual situation, and the formula for calculating the first target step size factor can be used as the formula for updating the first target step size factor.

[0112] S604: Based on the first target step size factor, the conjugate DPD error signal corresponding to the target DPD error signal at the current time, and the sample OFDM signal after analog-to-digital conversion, the initial parameter set at the current time is corrected, and the corrected initial parameter set is obtained.

[0113] JPEG0007846794000019.jpg23170

[0114] JPEG0007846794000020.jpg36170

[0115] It is clear that by the method described in steps S601 to S604 above, iterative correction of the initial parameter set is achieved in offline mode, thereby enabling the BL-DPD module to complete nonlinear distortion compensation to the initial OFDM signal according to a more precise model parameter set.

[0116] S405: The initial parameter set after iterative correction will be used as the model parameter set for the BL-DPD module.

[0117] Specifically, when step S405 is executed, if it is determined that the absolute value of the current target DPD error signal is smaller than the set threshold value of the DPD error signal, the initial parameter set after iterative correction at this time can be used as the model parameter set for the BL-DPD module, and this model parameter set can be assigned to the BL-DPD module.

[0118] Preferably, before performing step S404, if the absolute value of the target DPD error signal is greater than or equal to the threshold value of the DPD error signal, the initial parameter set is used as the model parameter set for the BL-DPD module.

[0119] Therefore, by using the method described in steps S401 to S405 above, the OFDM communication system selects the Mode as offline mode, processes the sample OFDM signal with a nonlinear compensation fusion model and a first branch, and trains the POST-BL-DPD module using the LNVSS-LMS self-adaptive algorithm, thereby realizing the modification and extraction of the model parameter set of the BL-DPD module.

[0120] In one preferred embodiment, referring to Figure 7, if the combination of parameters in the model parameter set consists of the kernel coefficients of the BL-CFR module, the nonlinear order, the memory depth, and the order of the low-order LPF, the model parameter set is obtained as follows.

[0121] S701: Sample OFDM signals in offline mode are sequentially input to the BL-DPD module and the preset CFR module to obtain the sample OFDM signals after DPD-CFR processing.

[0122] For example, when step S701 is executed, assuming that the sample OFDM signal in offline mode is s(n), the BL-DPD module kernel processing obtains the sample OFDM signal x(n) after DPD processing, and the sample OFDM signal x(n) after DPD processing is processed by the preset CFR module to obtain the sample OFDM signal x_c(n) after DPD-CFR processing.

[0123] S702: The sample OFDM signal after CFR processing is obtained based on the sample OFDM signal in offline mode and the conjugate parameter set corresponding to the initial parameter set of the BL-CFR module.

[0124] JPEG0007846794000021.jpg23170

[0125] JPEG0007846794000022.jpg35169

[0126] JPEG0007846794000023.jpg48170

[0127] JPEG0007846794000024.jpg8170

[0128] S703: The target CFR error signal is obtained based on the sample OFDM signal after DPD-CFR processing and the sample OFDM signal after CFR processing.

[0129] JPEG0007846794000025.jpg23169

[0130] JPEG0007846794000026.jpg18170

[0131] S704: Target CFR error signal and preset low-noise variable step size - Iteratively modify the initial parameter set based on a least mean squares algorithm until the absolute value of the target CFR error signal is smaller than the set threshold for the CFR error signal.

[0132] JPEG0007846794000027.jpg58169

[0133] JPEG0007846794000028.jpg38170

[0134] S705: The initial parameter set after iterative correction will be used as the model parameter set for the BL-CFR module.

[0135] Specifically, when step S705 is executed, if it is determined that the absolute value of the current target CFR error signal is smaller than the set threshold value of the CFR error signal, the initial parameter set after iterative correction at this time can be used as the model parameter set for the BL-CFR module, and this model parameter set can be assigned to the BL-CFR module.

[0136] Preferably, before performing step 704, if the absolute value of the target CFR error signal is greater than or equal to the threshold value of the CFR error signal, the initial parameter set is used as the model parameter set for the BL-CFR module.

[0137] Therefore, based on the method described in steps S701 to S705 above, in the OFDM communication system, the Mode is selected as offline mode, a nonlinear compensation fusion model and a second branch processing are performed on the sample OFDM signal, and the POST-BL-CFR module is trained using the LNVSS-LMS self-adaptive algorithm, thereby realizing the modification and extraction of the model parameter set of the BL-CFR module.

[0138] In one preferred embodiment, referring to Figure 8, if the combination of parameters in the model parameter set consists of the kernel coefficients, nonlinear order, and memory depth of the error compensation module ECM, the model parameter set is obtained as follows.

[0139] S801: Sample OFDM signals in offline mode are input to a nonlinear compensation fusion model and a preset higher-order LPF, respectively, to obtain the sample OFDM signals after nonlinear distortion compensation and the sample OFDM signals after filtering.

[0140] Furthermore, when acquiring the model parameter set for the error compensation module ECM, that is, when performing the method described in steps S801 to S804, the sample OFDM signal in offline mode is small, i.e., has a small width, and is in the linear region of PA.

[0141] Furthermore, to reduce the complexity of the model, the BL-DPD module and BL-CFR module are generated by low-order FIR processing. To compensate for signal loss due to the low-order FIR, error compensation parameters are trained offline using high-order FIR, effectively reducing the order of the band-limiting FIR. This reduces the overall complexity of the nonlinear strain fusion model while ensuring the accuracy and performance of the entire model.

[0142] JPEG0007846794000029.jpg28170

[0143] JPEG0007846794000030.jpg73170

[0144] JPEG0007846794000031.jpg30169

[0145] However, h represents the coefficient of the preset higher-order LPF, and L^' represents the order of the preset higher-order LPF, preferably L^' being 91 or higher.

[0146] S802: The target compensation error signal is obtained based on the sample OFDM signal after nonlinear distortion compensation and the sample OFDM signal after filtering.

[0147] JPEG0007846794000032.jpg24170

[0148] JPEG0007846794000033.jpg19170

[0149] S803: Target compensation error signal and preset low-noise variable step size - Based on the least mean squares algorithm, the initial parameter set of the error compensation module is iteratively modified until the absolute value of the target compensation error signal is smaller than the set threshold of the compensation error signal.

[0150] JPEG0007846794000034.jpg58169

[0151] JPEG0007846794000035.jpg35170

[0152] S804: The initial parameter set after iterative correction will be used as the model parameter set for the error compensation module.

[0153] Specifically, when step S804 is executed, if it is determined that the absolute value of the current target compensation error signal is smaller than the set threshold of the compensation error signal, the initial parameter set after iterative correction at this time can be used as the model parameter set for the error compensation module ECM, and this model parameter set can be assigned to the error compensation module ECM.

[0154] Preferably, before step S804 is executed, if the absolute value of the target compensation error signal is greater than or equal to the threshold value of the compensation error signal, the initial parameter set is used as the model parameter set for the error compensation module ECM.

[0155] Therefore, based on the method described in steps 801 to S804 above, in the OFDM communication system, the Mode is selected as offline mode, a nonlinear compensation fusion model and a third branch processing are performed on the sample OFDM signal, and the CBL-CFR-DPD module is trained using the LNVSS-LMS self-adaptive algorithm, thereby realizing the modification and extraction of the model parameter set of the error compensation module ECM.

[0156] Furthermore, referring to Figure 9, the OFDM communication system can, after acquiring the initial OFDM signal after nonlinear distortion compensation using a nonlinear compensation fusion model, refresh / modify the model parameter set of the BL-DPD module, and the specific operation flow is as follows.

[0157] S901: The initial OFDM signal after inverse DPD processing is obtained based on the initial OFDM signal after nonlinear distortion compensation and the conjugate parameter set corresponding to the model parameter set of the BL-DPD module.

[0158] In one preferred embodiment, referring to Figure 10, the OFDM communication system can acquire an initial OFDM signal after nonlinear distortion compensation, then, via a fourth branch in online mode, sequentially perform digital-to-analog conversion, up-converting, and power amplification processing on the initial OFDM signal after nonlinear distortion compensation to acquire an initial OFDM signal after power amplification, and then sequentially perform power attenuation, down-converting, and analog-to-digital conversion processing on the initial OFDM signal after power amplification to acquire an initial OFDM signal after analog-to-digital conversion, and finally, acquire an initial OFDM signal after inverse DPD processing based on the initial OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the model parameter set.

[0159] JPEG0007846794000036.jpg71170

[0160] JPEG0007846794000037.jpg22170

[0161] JPEG0007846794000038.jpg46170

[0162] S902: The target strain compensation error signal is obtained based on the initial OFDM signal after nonlinear strain compensation and the initial OFDM signal after inverse DPD processing.

[0163] JPEG0007846794000039.jpg22170

[0164] JPEG0007846794000040.jpg19170

[0165] S903: Based on the target distortion compensation error signal and a preset sine and error variable step size - least mean squares algorithm, the model parameter set is iteratively modified until the absolute value of the target distortion compensation error signal is less than the set distortion compensation error threshold.

[0166] JPEG0007846794000041.jpg64169

[0167] JPEG0007846794000042.jpg96170

[0168] Furthermore, the technical means of constructing the new CBL-CFR-DPD integration utilizes a mechanism for extracting and refreshing each module parameter "offline + online," thereby effectively improving the engineering capability of the digital predistortor to compensate for nonlinearities in broadband PAs. In offline mode, extraction of each module parameter is completed, effectively increasing operational efficiency, while in online mode, effective refreshing of the CBL-CFR-DPD module parameters is completed, enabling rapid predistortion processing for broadband signals. The error compensation module (ECM) then substantially integrates the BL-DPD module and the BL-CFR module into a single module. As a result, although this model involves more addition and subtraction calculations of several coefficients compared to a system that only runs the DPD module, the execution complexity of both is almost the same, and the execution complexity is reduced compared to the conventional technical means of applying the CFR module and DPD module independently.

[0169] JPEG0007846794000043.jpg23170

[0170] S1101: At the present time, acquire sample OFDM signals after nonlinear distortion compensation, corresponding to each of several historical time points adjacent to the initial OFDM signal after nonlinear distortion compensation.

[0171] JPEG0007846794000044.jpg33170

[0172] S1102: Based on the hysteresis distortion compensation error signals corresponding to each of the multiple nonlinear distortion-compensated sample OFDM signals, the average value of the distortion compensation error signal of the initial nonlinear distortion-compensated OFDM signal at the current time is obtained.

[0173] JPEG0007846794000045.jpg25169

[0174] JPEG0007846794000046.jpg12168

[0175] S1103: The second target step size factor is obtained based on the error term corresponding to the mean value of the distortion compensation error signal, the target distortion compensation error signal at the current time, and the historical distortion compensation error signal at the previous historical time adjacent to the current time.

[0176] JPEG0007846794000047.jpg22169

[0177] JPEG0007846794000048.jpg52170

[0178] S1104: Based on the second target step size factor, the conjugate distortion compensation error signal corresponding to the target distortion compensation error signal at the current time, and the initial OFDM signal after analog-to-digital conversion, the model parameter set at the current time is modified, and the modified model parameter set is obtained.

[0179] JPEG0007846794000049.jpg22170

[0180] JPEG0007846794000050.jpg35169

[0181] Based on the method described in steps S1101 to S1104 above, it is clear that iterative correction of the model parameter set of the BL-DPD module is achieved in online mode, thereby enabling the BL-DPD module to subsequently complete nonlinear distortion compensation to the OFDM signal according to a more precise model parameter set.

[0182] Preferably, in online mode, the OFDM communication system can iteratively modify the model parameter set of the BL-DPD module based on a set period time, that is, it can perform online-mode branching (i.e., nonlinear compensation fusion model and fourth branching) on ​​the initial OFDM signal based on a preset period T.

[0183] Furthermore, if it is determined that the absolute value of the current target distortion compensation error signal is smaller than the set threshold for distortion compensation error, the iteratively corrected model parameter set at this point can be made the new model parameter set for the BL-DPD module, and this model parameter set can be assigned to the BL-DPD module.

[0184] Therefore, based on the method described in steps S901 to S903 above, the OFDM communication system switches the Mode to online mode, performs online branching (nonlinear compensation fusion model and fourth branching) on ​​the initial OFDM signal based on the preset period T, and uses the SEVSS-LMS self-adaptive algorithm to perform an effective refresh / modification on the parameters of the nonlinear compensation fusion model (i.e., the CBL-CFR-DPD model) (i.e., the model parameter set of the BL-DPD module).

[0185] As described above, in the nonlinear distortion compensation method for signals provided in the embodiments of this disclosure, DPD processing, CFR processing, and error compensation processing are performed on the initial OFDM signal based on a preset nonlinear compensation fusion model, thereby obtaining an initial OFDM signal after nonlinear distortion compensation based on a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module.

[0186] Thus, by arranging the BL-DPD module, BL-CFR module, and error compensation module in parallel in the preset nonlinear compensation fusion model, the technical drawbacks of the conventional technology, where the DPD module is applied after the CFR module, are avoided. This increases the demands on the ADC / DAC sampling rate in the OFDM system, as well as the demands on hardware and algorithm convergence speed, thereby increasing the difficulty and cost of system implementation. As a result, not only are the demands on the ADC / DAC sampling rate effectively reduced, but the communication and sensing capabilities of the OFDM system are further improved by enhancing the DPD's ability to compensate for the nonlinearity of the power amplifier.

[0187] Based on the same inventive concept, embodiments of the present disclosure further provide a nonlinear compensation fusion model comprising a BL-DPD module, a BL-CFR module, and an error compensation module. The BL-DPD module, BL-CFR module, and error compensation module are connected in parallel. The basis functions used by the BL-DPD module and the BL-CFR module are the same, and the error compensation module is used to perform error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module.

[0188] In one preferred embodiment, the basis functions used by the BL-DPD module and the BL-CFR module are the same.

[0189] In one preferred embodiment, the nonlinear compensation fusion model is Based on the initial OFDM signal, a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module are obtained. It is used to obtain an initial OFDM signal after nonlinear distortion compensation, based on the first OFDM signal, the second OFDM signal, and the third OFDM signal.

[0190] In one preferred embodiment, the nonlinear compensation fusion model further In offline mode, it is used to extract model parameter sets for the BL-DPD module, BL-CFR module, and error compensation module based on a preset low-noise variable step-size-least mean squares algorithm.

[0191] In one preferred embodiment, the nonlinear compensation fusion model further, In online mode, it is used to refresh the model parameter set for a nonlinear compensated fusion model based on a preset sine and error variable step size-least mean squares algorithm and a set period time.

[0192] In one preferred embodiment, the nonlinear compensation fusion model is, specifically, In online mode, it is used to refresh the model parameter set only for the BL-DPD module in a nonlinear compensated fusion model, based on a preset sine and error variable step size-least mean squares algorithm and a set period time.

[0193] Based on the same inventive concept, embodiments of the present disclosure provide an OFDM communication system comprising a nonlinear compensation fusion model and a first branch, a second branch, a third branch, and a fourth branch. In the nonlinear compensated fusion model, the BL-DPD module and the first branch are used in offline mode to iteratively modify the initial parameter set of the BL-DPD module and obtain the model parameter set of the BL-DPD module. In the nonlinear compensated fusion model, the BL-CFR module and the second branch are used in offline mode to iteratively modify the initial parameter set of the BL-CFR module and obtain the model parameter set of the BL-CFR module. The nonlinear compensated fusion model and the third bifurcation are used in offline mode to iteratively modify the initial parameter set of the error compensation module and obtain the model parameter set of the error compensation module. The nonlinear compensated fusion model and the fourth bifurcation are used in online mode to iteratively modify the model parameter set of the BL-DPD module.

[0194] In one preferred embodiment, the first branch comprises, in order, a digital-to-analog converter (DAC), an upconverter, a power amplifier (PA), an attenuator, a bandpass filter (BPF), a downconverter, an analog-to-digital converter (ADC), a training network (POST-BL-DPD) module, and a preset low-noise variable step-size-least mean squares algorithm module.

[0195] In one preferred embodiment, the second branch comprises a sequentially installed CFR module, a training network POST-BL-DPD module, and a preset low-noise variable step-size-least mean squares algorithm module.

[0196] In one preferred embodiment, the third branch comprises sequentially installed low-pass filters (LPFs) and a preset low-noise variable step-size-least mean squares algorithm module.

[0197] In one preferred embodiment, the fourth branch comprises, in order, a DAC, an upconverter, a PA, an attenuator, a BPF, a downconverter, an ADC, a training network POST-BL-DPD module, and a preset sine and error variable step size-least mean squares algorithm module.

[0198] Based on the same technical concept, embodiments of the present disclosure further provide electronic devices that can implement steps of a nonlinear distortion compensation method for signals provided in the above embodiments of the present disclosure. In one embodiment, the electronic device may be a server, a terminal device, or other electronic device. Referring to Figure 12, the electronic device is: The present invention comprises at least one processor 1201 and memory 1202 connected to at least one processor 1201. In embodiments of this disclosure, the specific connection medium between the processor 1201 and memory 1202 is not limited, and in Figure 12, the processor 1201 and memory 1202 are connected by a bus 1200 as an example. The bus 1200 is shown by a thick line in Figure 12, and the connection methods between other components are merely a general description and are not limiting. The bus 1200 can be divided into an address bus, a data bus, a control bus, etc., and for illustrative purposes, it is shown by only one thick line in Figure 12, but this does not mean that there is only one bus or only one type of bus. Alternatively, the processor 1201 may be called a controller, and the name is not limiting.

[0199] In embodiments of this disclosure, the memory 1202 stores instructions that can be executed by at least one processor 1201, and the at least one processor 1201 can execute the above-described signal nonlinear distortion compensation method by executing the instructions stored in the memory 1202. The processor 1201 can realize the functions of each module in the corresponding device.

[0200] Here, the processor 1201 is the control center of the device, connecting each part of the entire control device through various interfaces and lines, running or executing instructions stored in the memory 1202, and monitoring the entire device by retrieving data (each function and processing data of the device) stored in the memory 1202.

[0201] In one possible design, the processor 1201 may comprise one or more processing units, and the processor 1201 may integrate an application processor and a modem processor, the application processor mainly handling the operating system, user interface and applications, etc., and the modem processor mainly handling wireless communication. It is understood that the modem processor does not have to be integrated into the processor 1201. In some embodiments, the processor 1201 and memory 1202 may be implemented on the same chip, and in some embodiments, they may be implemented on separate chips, respectively.

[0202] The processor 1201 may be a general-purpose processor such as a CPU, a digital signal processing unit, a dedicated integrated circuit, a field-programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, which can implement or execute each method, step and logic block diagram disclosed in embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the nonlinear distortion compensation method for signals disclosed in relation to embodiments of this disclosure may be performed directly by the hardware processor or by a combination of hardware modules and software modules within the processor.

[0203] Memory 1202 can be used as a non-volatile computer-readable storage medium to store non-volatile software programs, non-volatile computer executable programs, and modules. Memory 1202 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory 1202 is any other medium accessible by a computer that carries or stores desired program code having the form of instructions or data structures. Memory 1202 in embodiments of this disclosure may be any other device capable of implementing circuitry or storage functions for storing program instructions and / or data.

[0204] By designing and programming the processor 1201, code corresponding to the nonlinear distortion compensation method for signals described in the embodiments above can be written to the chip, thereby enabling the chip to execute the steps of the nonlinear distortion compensation method for signals according to the embodiment shown in Figure 2 during execution. The method for designing and programming the processor 1201 is well known to those skilled in the art and is therefore omitted from this description.

[0205] Based on the same inventive concept, embodiments of the present disclosure further provide a storage medium in which computer instructions are stored, and when the computer instructions are executed on a computer, the computer is made to execute the above-described nonlinear distortion compensation method for signals.

[0206] In some preferred embodiments, the Disclosure further provides a program product capable of implementing each aspect of a method for compensating for nonlinear distortion of a signal, the program product comprising program code, which, when executed on a device, causes the control device to perform steps of a method for compensating for nonlinear distortion of a signal according to each exemplary embodiment of the Disclosure described herein.

[0207] While the above detailed description mentions several units or subunits of the apparatus, such classifications are merely illustrative and not mandatory. In practice, according to embodiments of this disclosure, the features and functions of two or more units described above can be embodied in a single unit. Conversely, the features and functions of a single unit described above can be embodied by multiple units.

[0208] Furthermore, although the operation of the method of this disclosure is described in a specific order in the drawings, it is not required or suggested that these operations must be performed in that specific order, or that the desired results cannot be achieved unless all operations are performed. Additionally, or preferably, some steps can be omitted, multiple steps can be performed in combination with one step, and / or one step can be divided into multiple steps.

[0209] Those skilled in the art will understand that embodiments of the present disclosure can provide methods, systems, or computer program products. The present disclosure can be implemented as hardware, software, or a combination of hardware and software. The present disclosure can also be implemented as a computer program product executable on one or more computer-available storage media (including, but not limited to, disk memory, CD-ROM, optical memory, etc.) containing computer-available program code.

[0210] This disclosure describes methods, devices (systems), and computer program products according to embodiments of this disclosure with reference to flowcharts and / or block diagrams. It should be understood that computer program instructions realize each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams. To generate a server, these computer program instructions are provided to a processor of a general-purpose computer, a dedicated computer, an embedded processor, or other programmable data processing device to generate a server, thereby enabling instructions executed by the processor of the computer or other programmable data processing device to generate a device for realizing one or more flows in a flowchart and / or one or more blocks in a block diagram.

[0211] The program code for performing the operations of this disclosure can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and also including traditional procedural programming languages ​​such as the C language or similar programming languages. The program code can run entirely on a user computing device, partially on a user computing device, run as a standalone package, run partially on a user computing device and partially on a remote computing device, or run entirely on a remote computing device or server.

[0212] In the case of remote computing devices, the remote computing device may connect to a user computing device via any type of network, including a local area network (LAN) or wide area network (WAN), or it may connect to an external computing device (for example, via the Internet by an Internet service provider).

[0213] These computer program instructions can be stored in computer-readable memory that can operate a computer or other programmable data processing device in a specific manner, thereby generating a product that includes an instruction device that implements a function specified in one or more flows of a flowchart and / or one or more blocks of a block diagram.

[0214] These computer program instructions can be loaded into a computer or other programmable data processing device and execute a series of operational steps on the computer or other programmable device to generate processing for the computer implementation, thereby providing steps to realize one or more flows in a flowchart and / or one or more blocks in a block diagram.

[0215] It will be apparent to those skilled in the art that they can make various modifications and changes to this disclosure, without departing from the spirit and scope of this disclosure. Thus, if such modifications and changes to this disclosure fall within the claims of this disclosure or their equivalent technical scope, this disclosure is intended to include such modifications and changes.

Claims

1. A method for compensating for nonlinear distortion of a power amplifier signal, The method involves inputting an initial orthogonal wave frequency division multiplexed OFDM signal into a preset nonlinear compensation fusion model of a power amplifier signal, wherein the nonlinear compensation fusion model of the power amplifier signal comprises a frequency band limiting-digital pre-distortion BL-DPD module, a frequency band limiting-crest factor reduction BL-CFR module, and an error compensation module, wherein the error compensation module performs error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module. The initial OFDM signal is obtained as follows: a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module. The method is characterized by including obtaining an initial OFDM signal after nonlinear distortion compensation based on the first OFDM signal, the second OFDM signal, and the third OFDM signal. A method for compensating for nonlinear distortion in power amplifier signals.

2. The basis functions used by the BL-DPD module and the BL-CFR module are the same, characterized in that The method for compensating for nonlinear distortion of a power amplifier signal according to claim 1.

3. With respect to the initial OFDM signal, the acquisition of a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module is as follows: The method is characterized by modulating the initial OFDM signal based on the model parameter set converged in the offline modes of the BL-DPD module, the BL-CFR module, and the error compensation module, and acquiring the first OFDM signal, the second OFDM signal, and the third OFDM signal, respectively. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 1.

4. The aforementioned model parameter set is: The combination of parameters consisting of the kernel coefficients, nonlinear order, memory depth, and order of the low-order low-pass filter (LPF) of the BL-DPD module, The combination of parameters consisting of the kernel coefficients, nonlinear order, memory depth, and order of the low-order LPF of the BL-CFR module, The combination of parameters consisting of the kernel coefficient, nonlinear order, and memory depth of the error compensation module, A feature that includes any one of the following: The method for compensating for nonlinear distortion of a power amplifier signal according to claim 3.

5. If the combination of parameters in the aforementioned model parameter set consists of the kernel coefficients, nonlinear order, memory depth, and order of the low-order LPF of the BL-DPD module, then the aforementioned model parameter set is: The sample OFDM signal in offline mode is input to the BL-DPD module, and the sample OFDM signal after DPD processing is obtained. Based on the sample OFDM signal after DPD processing and the conjugate parameter set corresponding to the initial parameter set of the BL-DPD module, the sample OFDM signal after inverse DPD processing is obtained. Based on the sample OFDM signal in the offline mode and the sample OFDM signal after the inverse DPD processing, a target DPD error signal is obtained. Based on the target DPD error signal and a preset low-noise variable step size-least mean squares algorithm, the initial parameter set is iteratively modified until the absolute value of the target DPD error signal is smaller than the set threshold of the DPD error signal. The initial parameter set after iterative correction is used as the model parameter set of the BL-DPD module, and is obtained by this method. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 4.

6. Based on the sample OFDM signal after DPD processing and the conjugate parameter set corresponding to the initial parameter set of the BL-DPD module, obtaining the sample OFDM signal after inverse DPD processing is possible. The sample OFDM signal after the DPD processing is subjected to digital-to-analog conversion, upconverting, and power amplification processing in sequence to obtain the sample OFDM signal after power amplification. The sample OFDM signal after power amplification is subjected to power attenuation, down-converting, and analog-to-digital conversion processing in sequence to obtain the sample OFDM signal after analog-to-digital conversion. The method is characterized by including obtaining the sample OFDM signal after inverse DPD processing based on the sample OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the initial parameter set, The method for compensating for nonlinear distortion of a power amplifier signal according to claim 5.

7. Iteratively modifying the initial parameter set based on the target DPD error signal and the preset low-noise variable step size-least mean squares algorithm means that each time the initial parameter set is modified, Currently, the sample OFDM signal is acquired for each of multiple historical time points adjacent to the sample OFDM signal in the aforementioned offline mode. Based on the historical DPD error signals corresponding to each of the multiple sample OFDM signals, the average value of the DPD error signals of the sample OFDM signals at the current time in offline mode is obtained, Based on the average value of the DPD error signal, the step size factor at the previous historical time adjacent to the current time, the target DPD error signal at the current time, and the historical DPD error signal at the previous historical time, a first target step size factor is obtained. The method is characterized by including modifying the initial parameter set at the current time based on the first target step size factor, the conjugate DPD error signal corresponding to the target DPD error signal at the current time, and the sample OFDM signal after analog-to-digital conversion, and obtaining and executing the modified initial parameter set. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 5.

8. Before iteratively modifying the initial parameter set based on the target DPD error signal and the preset low-noise variable step size-least mean squares algorithm, The present invention further includes, if the absolute value of the target DPD error signal is greater than or equal to the threshold value of the DPD error signal, the initial parameter set is used as the model parameter set for the BL-DPD module. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 5.

9. If the combination of parameters in the aforementioned model parameter set consists of the kernel coefficients, nonlinear order, memory depth, and order of the low-order LPF of the BL-CFR module, then the aforementioned model parameter set is: The sample OFDM signal in offline mode is sequentially input to the BL-DPD module and the preset CFR module, and the sample OFDM signal after DPD-CFR processing is obtained. Based on the sample OFDM signal in the offline mode and the conjugate parameter set corresponding to the initial parameter set of the BL-CFR module, the sample OFDM signal after CFR processing is obtained. Based on the sample OFDM signal after DPD-CFR processing and the sample OFDM signal after CFR processing, a target CFR error signal is obtained. Based on the target CFR error signal and a preset low-noise variable step size-least mean squares algorithm, the initial parameter set is iteratively modified until the absolute value of the target CFR error signal becomes smaller than the set threshold of the CFR error signal. The initial parameter set after iterative correction is obtained by using the model parameter set of the BL-CFR module, characterized in that The method for compensating for nonlinear distortion of a power amplifier signal according to claim 4.

10. Before iteratively modifying the initial parameter set based on the target CFR error signal and the preset low-noise variable step size-least mean squares algorithm, The present invention further includes, if the absolute value of the target CFR error signal is greater than or equal to the threshold value of the CFR error signal, the initial parameter set is used as the model parameter set of the BL-CFR module. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 9.

11. If the combination of parameters in the aforementioned model parameter set consists of the kernel coefficients, nonlinear order, and memory depth of the error compensation module, then the aforementioned model parameter set is: The sample OFDM signal in offline mode is input to the nonlinear compensation fusion model and the preset higher-order LPF of the power amplifier signal, respectively, to obtain the sample OFDM signal after nonlinear distortion compensation and the sample OFDM signal after filtering. Based on the sample OFDM signal after nonlinear distortion compensation and the sample OFDM signal after filtering, a target compensation error signal is obtained. Based on the target compensation error signal and a preset low-noise variable step size-least mean squares algorithm, the initial parameter set of the error compensation module is iteratively modified until the absolute value of the target compensation error signal is smaller than the set threshold of the compensation error signal. The initial parameter set after iterative correction is used as the model parameter set of the error compensation module, and is obtained by this method, The method for compensating for nonlinear distortion of a power amplifier signal according to claim 4.

12. Before iteratively modifying the initial parameter set of the error compensation module based on the target compensation error signal and the preset low-noise variable step size-least mean squares algorithm, The feature further includes using the initial parameter set as the model parameter set of the error compensation module if the absolute value of the target compensation error signal is greater than or equal to the threshold value of the compensation error signal. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 11.

13. After obtaining an initial OFDM signal after nonlinear distortion compensation based on the first OFDM signal, the second OFDM signal, and the third OFDM signal, Based on the initial OFDM signal after nonlinear distortion compensation and the conjugate parameter set corresponding to the model parameter set of the BL-DPD module, the initial OFDM signal after inverse DPD processing is obtained. Based on the initial OFDM signal after nonlinear distortion compensation and the initial OFDM signal after inverse DPD processing, a target distortion compensation error signal is obtained. The method further includes iteratively modifying the model parameter set based on the target distortion compensation error signal and a preset sine-variable step size-least mean squares algorithm until the absolute value of the target distortion compensation error signal is less than a set threshold for distortion compensation error, The method for compensating for nonlinear distortion of a power amplifier signal according to claim 1.

14. Based on the initial OFDM signal after nonlinear distortion compensation and the conjugate parameter set corresponding to the model parameter set of the BL-DPD module, obtaining the initial OFDM signal after inverse DPD processing is: The initial OFDM signal after nonlinear distortion compensation is subjected to digital-to-analog conversion, upconverting, and power amplification processing in sequence to obtain the initial OFDM signal after power amplification. The initial OFDM signal after power amplification is subjected to power attenuation, down-converting, and analog-to-digital conversion processing in sequence to obtain the initial OFDM signal after analog-to-digital conversion. The method is characterized by including obtaining the initial OFDM signal after inverse DPD processing based on the initial OFDM signal after analog-to-digital conversion and the conjugate parameter set corresponding to the model parameter set, The method for compensating for nonlinear distortion of a power amplifier signal according to claim 13.

15. Performing iterative modifications to the model parameter set based on the target distortion compensation error signal and a preset sine and error variable step size-least mean squares algorithm is: Each time the aforementioned model parameter set is modified, Currently, the process involves acquiring sample OFDM signals after nonlinear distortion compensation, corresponding to each of several historical time points adjacent to the initial OFDM signal after nonlinear distortion compensation. Based on the hysteresis distortion compensation error signals corresponding to each of the multiple nonlinear distortion-compensated sample OFDM signals, the average value of the distortion compensation error signal of the initial nonlinear distortion-compensated OFDM signal at the current time is obtained. Based on the error term corresponding to the average value of the aforementioned distortion compensation error signal, the target distortion compensation error signal at the current time, and the historical distortion compensation error signal at the previous historical time adjacent to the current time, a second target step size factor is obtained. The method is characterized by modifying the model parameter set at the current time based on the second target step size factor, the conjugate distortion compensation error signal corresponding to the target distortion compensation error signal at the current time, and the initial OFDM signal after analog-to-digital conversion, and obtaining and executing the modified model parameter set. The method for compensating for nonlinear distortion of a power amplifier signal according to claim 13.

16. The nonlinear distortion compensation method for the power amplifier signal is as follows: The method further includes iteratively modifying the model parameter set of the BL-DPD module based on a set period time, The method for compensating for nonlinear distortion of a power amplifier signal according to claim 13.

17. A nonlinear compensation fusion model for a power amplifier signal, It comprises a BL-DPD module, a BL-CFR module, and an error compensation module. The BL-DPD module, the BL-CFR module, and the error compensation module are connected in parallel, and the error compensation module is used to perform error compensation on the OFDM signals output from the BL-DPD module and the BL-CFR module. A nonlinear compensation fusion model for power amplifier signals.

18. The basis functions used by the BL-DPD module and the BL-CFR module are the same, characterized in that The nonlinear compensation fusion model of a power amplifier signal according to claim 17.

19. The nonlinear compensation fusion model of the power amplifier signal is, Based on the initial OFDM signal, a first OFDM signal processed by the BL-DPD module, a second OFDM signal processed by the BL-CFR module, and a third OFDM signal processed by the error compensation module are obtained. It is characterized by being used to obtain an initial OFDM signal after nonlinear distortion compensation based on the first OFDM signal, the second OFDM signal, and the third OFDM signal. A nonlinear compensation fusion model for a power amplifier signal according to claim 17.

20. The aforementioned nonlinear compensation fusion model of the power amplifier signal further It is characterized by being used in offline mode to extract model parameter sets for the BL-DPD module, the BL-CFR module, and the error compensation module based on a preset low-noise variable step size-least mean squares algorithm. The nonlinear compensation fusion model of a power amplifier signal according to claim 17.

21. The aforementioned nonlinear compensation fusion model for the power amplifier signal further, It is characterized by being used in online mode to refresh the model parameter set for the nonlinear compensation fusion model of the power amplifier signal based on a preset sine and error variable step size-least mean squares algorithm and a set period time, The nonlinear compensation fusion model of a power amplifier signal according to claim 17.

22. The nonlinear compensation fusion model of the power amplifier signal is, In online mode, it is used to refresh the model parameter set only for the BL-DPD module in the nonlinear compensation fusion model of the power amplifier signal, based on the preset sine and error variable step size-least mean squares algorithm and the set period time. The nonlinear compensation fusion model of a power amplifier signal according to claim 21.

23. OFDM communication system, A nonlinear compensation fusion model of a power amplifier signal according to any one of claims 17 to 22, comprising a first branch, a second branch, a third branch, and a fourth branch, In the nonlinear compensation fusion model of the power amplifier signal, the BL-DPD module and the first branch are used in offline mode to iteratively modify the initial parameter set of the BL-DPD module and to obtain the model parameter set of the BL-DPD module. In the nonlinear compensation fusion model of the power amplifier signal, the BL-CFR module and the second branch are used in offline mode to iteratively modify the initial parameter set of the BL-CFR module and to obtain the model parameter set of the BL-CFR module. The nonlinear compensation fusion model of the power amplifier signal and the third branch are used in offline mode to iteratively modify the initial parameter set of the error compensation module and to obtain the model parameter set of the error compensation module. The nonlinear compensation fusion model of the power amplifier signal and the fourth branch are used in online mode to iteratively modify the model parameter set of the BL-DPD module, characterized in that OFDM communication system.

24. The first branch is characterized by comprising, in order, a digital-to-analog converter (DAC), an upconverter, a power amplifier (PA), an attenuator, a bandpass filter (BPF), a downconverter, an analog-to-digital converter (ADC), a training network (POST-BL-DPD) module, and a preset low-noise variable step size-least mean squares algorithm module. The OFDM communication system according to claim 23.

25. The second branch is characterized by comprising, in order, a CFR module, a training network POST-BL-DPD module, and a preset low-noise variable step size-least mean squares algorithm module. The OFDM communication system according to claim 23.

26. The third branch is characterized by comprising a sequentially installed low-pass filter (LPF) and a preset low-noise variable step size - least mean squares algorithm module. The OFDM communication system according to claim 23.

27. The fourth branch is characterized by comprising, in order, the DAC, the upconverter, the PA, the attenuator, the BPF, the downconverter, the ADC, the training network POST-BL-DPD module, and a preset sine and error variable step size-least mean squares algorithm module. The OFDM communication system according to claim 24.

28. An electronic device comprising memory, a processor, and a computer program stored in memory and executable by the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 16 is realized. electronic equipment.

29. A computer-readable storage medium in which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 16 are realized. Computer-readable storage medium.

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