Digital Predistortion Method and System for Processing Secondary Components of Harmonic Multiband Transmitters

Abstract

The present invention belongs to the technical field of wireless communication systems, and discloses a digital predistortion method and system capable of processing secondary components of a harmonic multi-band transmitter, including performing component analysis on the power amplifier output spectrum according to the selection of the non-linear characteristics of the power amplifier and the frequency of the input signal carrier; aliasing analysis, performing aliasing analysis according to the information of the carrier frequency and the signal bandwidth, and calling the resampled signals of each frequency band to confirm the signal quality; predicting the regenerated intermodulation components; multiplying all the basis functions near a carrier by corresponding frequency coefficients and then putting them into a non-linear model. The present invention uses an independent computing unit to perform model calculation and compensation on the harmonics and intermodulation components that may be aliased with the carrier, and predicts and compensates the secondary regenerated components of the predistorted signal and the carrier, so as to obtain better multi-band linearization performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communication systems, and in particular, relates to a digital predistortion method and system capable of processing secondary components of a harmonic multi-band transmitter. Background Art

[0002] Currently, with the rapid development of communication technologies, wireless communication systems need to meet more stringent capacity requirements. There is a need for communication systems to have higher communication rates, lower latency responses, and a larger number of concurrent users. At the same time, in order to achieve the overall goal of carbon peak, wireless base stations also need to have higher working efficiency. To meet the demand for communication bandwidth, carrier aggregation technology is adopted in current 4G and 5G communication systems, that is, a method of concurrently transmitting signals on different frequency carriers. This is also because the current spectrum resources are very precious, and the spectrum available to communication systems is scattered in various frequency bands. Therefore, in order to achieve a faster data transmission rate, transmitting using multiple frequency bands simultaneously can transmit more information. On the other hand, since current commercial base stations need to be compatible with multiple communication systems simultaneously, multi-band transmitters that support multiple frequency bands show cost advantages. However, since a multi-band transmitter simultaneously transmits signals of multiple frequencies, complex nonlinear distortions occur due to nonlinearity after the signals pass through a power amplifier, generating a large number of nonlinear components. Traditional digital predistortion techniques generally only consider odd-order intermodulation between carriers because only the intermodulation components generated by odd-order intermodulation will appear near the carriers. However, carrier aggregation in a larger bandwidth range has broken the limitation that only odd-order intermodulation distortion components will appear near the carriers. When the frequency selection exceeds the multiple frequency layer, the harmonic components of the carrier signal will also approach the carrier of the power amplifier output signal. Especially when multiple carrier frequencies are close to an integer multiple relationship, the harmonics and other intermodulation components will approach or even overlap with the carrier signal, which cannot be processed by traditional digital predistortion models, making it impossible for traditional multi-band transmitters to be compatible with simultaneous transmissions under specific frequency relationships. In order to enable the base station to be compatible with multiple protocols or carrier aggregation under such frequency selections, the transmitter can only amplify the signal through a multi-channel structure. However, a multi-power amplifier transmitter requires higher hardware costs and power consumption. Therefore, a linearization scheme for multi-band transmitters that can handle carrier frequencies close to an integer multiple is needed.

[0003] Through the above analysis, the problems and defects of the prior art are as follows:

[0004] (1) Traditional digital predistortion techniques generally only consider odd-order intermodulation between carriers, and carrier aggregation in a larger bandwidth range has broken the limitation that only odd-order intermodulation distortion components will appear near the carriers.

[0005] (2) When multiple carrier frequencies are close to an integer multiple relationship, harmonics and other intermodulation components will also be close to or even overlap with the carrier signal. These situations cannot be handled by traditional digital predistortion models, making traditional multi-band transmitters unable to be compatible with simultaneous transmissions under specific frequency relationships.

[0006] (3) In order for the base station to be compatible with multiple protocols or carrier aggregation under such frequency selections simultaneously, the transmitter can only amplify the signal through a multi-channel structure. However, a multi-power amplifier transmitter requires higher hardware costs and power consumption. Summary of the Invention

[0007] Aiming at the problems existing in the prior art, the present invention provides a digital predistortion method and system capable of processing secondary components of a harmonic multi-band transmitter.

[0008] The present invention is implemented as follows. A digital predistortion method capable of processing secondary components of a harmonic multi-band transmitter, where the model calculation and predistortion signal generation of the method are both completed in the baseband processor of the transmitter; through pre-performed frequency component analysis and signal bandwidth analysis, the frequencies and nonlinear models of the secondary components in the output signal of the power amplifier and the nonlinear models of the regenerated spectrum components after prediction compensation are obtained, and these models are used to perform nonlinear compensation on the output signal of the power amplifier at multiple frequency points, so that the multi-band transmitter obtains linear output characteristics.

[0009] Further, it includes:

[0010] Step 1, perform component analysis on the output spectrum of the power amplifier according to the nonlinear characteristics of the power amplifier and the selection of the frequency of the input signal carrier;

[0011] Step 2, perform aliasing analysis, perform aliasing analysis according to the information of the carrier frequency and signal bandwidth, and call the sampled-back signal of each frequency band to confirm the signal quality;

[0012] Step 3, predict the regenerated intermodulation components;

[0013] Step 4, multiply all the basis functions near a carrier by the corresponding frequency coefficients and then put them into a nonlinear model.

[0014] Further, in the component analysis of the power amplifier output spectrum in Step 1, if the harmonic or difference frequency component of the signal is close to other carrier signals, start the corresponding intermodulation component compensation algorithm;

[0015] If there is no situation where harmonics, difference frequencies, etc. are close to the carrier, directly call the traditional multi-band predistortion module to perform compensation.

[0016] Further, in Step 2, if the carrier signal and the intermodulation component are aliased, call the predistortion model corresponding to the frequency to compensate the distortion components of each frequency.

[0017] Further, the method adopted for aliasing analysis in the second step is: analyzing the frequency composition of the power amplifier output signal through polynomial calculation based on the frequencies of each carrier signal.

[0018] Further, the method adopted for the aliasing analysis specifically includes:

[0019] The power amplifier model uses a polynomial model of a specified order: generally analyzed up to the 3rd to 5th order. If there is a multiple relationship of more than 5 times between the carrier frequencies, a polynomial of a higher order needs to be used for analysis; multiple signal carriers are respectively x1(t)sin(ω1t), x2(t)sin(ω2t) …… x n (t)sin(ω n t), and the input value polynomial y = a1x + a2x 2 + a3x 3 Analyze the frequency composition of the output signal and take the components near each carrier frequency.

[0020] Further, the predistortion model is a non - linear compensation model. In the non - linear compensation model, the compensation for each carrier signal uses the traditional multi - band memory polynomial model, and the distortion components corresponding to other frequency points are obtained using the basis function substitution method: Since the frequency of each distortion component is obtained by the non - linearity of the carrier signal, the frequency points of the distortion components must be obtained by the linear combination of multiple carrier frequencies, that is: ω x = b1ω x + b2ω x + … + b n ω n Each basis function of the corresponding non - linear compensation function has a phase part and is written in the product form corresponding to the linear combination of frequencies, that is:

[0021]

[0022] where b is an integer. When b is negative, x b =(x * ) -b .

[0023] Further, in the fourth step, the training of the predistortion parameters is carried out using the direct learning or iterative learning control method.

[0024] Another object of the present invention is to provide a digital predistortion capable of processing the secondary components of a harmonic multi - band transmitter. The digital predistortion system capable of processing the secondary components of a harmonic multi - band transmitter includes:

[0025] A spectrum component analysis module, which is used to perform component analysis of the power amplifier output spectrum according to the non-linear characteristics of the power amplifier and the selection of the frequency of the input signal carrier;

[0026] An aliasing analysis module, which is used to perform aliasing analysis according to the information of the carrier frequency and the signal bandwidth, and call the resampled signals of each frequency band to confirm the signal quality.

[0027] Combined with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0028] First, in view of the technical problems existing in the above-mentioned prior art and the difficulty of solving the problems, closely combined with the technical solutions to be protected by the present invention and the results and data in the R & D process, etc., analyze in detail and profoundly how the technical solutions of the present invention solve the technical problems and the creative technical effects brought after solving the problems. The specific description is as follows:

[0029] The present invention uses an independent computing unit to perform model calculation and compensation on the harmonics and intermodulation components that may be aliased with the carrier, and predict and compensate the second-generation regeneration components of the predistortion signal and the carrier, so as to obtain much better multi-band linearization performance. When the frequency relationship between multi-carrier signals approaches an integer multiple, the harmonic distortion of the power amplifier will approach the carrier, and spectrum aliasing may also occur. Moreover, the distortion components such as the corresponding difference frequency components will also approach the lower-frequency carrier signals, so there will be complex non-linear intermodulation components near each carrier. Traditional multi-band digital predistortion technology cannot handle such complex non-linear intermodulation components. Especially in the case of aliasing, after compensating the non-linear intermodulation of the existing frequencies, due to the non-linear intermodulation between the predistortion signal and the carrier again, second-generation regeneration components will be generated. If the second-generation regeneration components are still relatively close to the carrier in this case, then the second-generation regeneration components must be predicted and compensated, so that the multi-band transmitter can obtain high-quality linear output.

[0030] Second, regarding the technical solution as a whole or from the perspective of the product, the technical effects and advantages of the technical solution to be protected by the present invention are specifically described as follows:

[0031] The key technical solution to be protected in the present invention is the prediction and compensation technology for regenerative intermodulation components. When no nonlinear compensation is performed, there are no distortion components at the frequencies of these regenerative intermodulations. These regenerative intermodulations are generated by the second-order intermodulation of the predistortion signal and the carrier signal. When the input signal is the original signal, no regenerative intermodulation components can be detected in the sampled output signal. Therefore, the compensation of regenerative intermodulation components must use an algorithm with the characteristic of iterative parameter correction to train the predistortion signal. And due to the severe aliasing scenario, the regenerative intermodulation components are also close to the carrier or even aliased with the carrier components. At this time, the compensation of regenerative intermodulation components is also important for the linearity of the multi-band transmitter. Therefore, this prediction and compensation structure is of great significance to the linearization of the multi-band transmitter.

[0032] Third, as the creative auxiliary evidence of the claims of the present invention, it is also reflected in the following important aspects: The present invention is a predistortion structure for a multi-band transmitter, which can be effectively applied to the current mobile communication base stations. Since 5G multi-mode base stations need to be compatible with multiple communication standards and frequencies at the same time, there are multiple sets of frequencies available for mobile communication providers under Sub-6GHz. If a single-radio-channel multi-band transmitter can be used, it can greatly reduce the hardware and maintenance costs. The multi-band linearization technology in the present invention can provide excellent linearity guarantee for the multi-band transmitter. In summary, the present invention has great commercial value and market potential. Brief Description of the Drawings

[0033] Figure 1 It is a flowchart of a digital predistortion method for processing secondary components of a harmonic multi-band transmitter provided by an embodiment of the present invention;

[0034] Figure 2 It is a schematic diagram of the predistortion modeling and simulation results of a predistortion structure with secondary component compensation provided by an embodiment of the present invention. Detailed Embodiments

[0035] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0036] In order to enable those skilled in the art to fully understand how the present invention is specifically implemented, this part is an explanatory embodiment that expands and explains the technical solutions of the claims.

[0037] As Figure 1 shown, the digital predistortion method for processing secondary components of a harmonic multi-band transmitter provided by an embodiment of the present invention includes:

[0038] S101, perform component analysis of the power amplifier output spectrum according to the nonlinear characteristics of the power amplifier and the selection of the frequency of the input signal carrier;

[0039] S102, Aliasing analysis, perform aliasing analysis based on the information of the carrier frequency and the signal bandwidth, and call the resampled signals of each frequency band to confirm the signal quality;

[0040] S103, Predict the regenerated intermodulation components;

[0041] S104, Multiply all the basis functions near a carrier by the corresponding frequency coefficients and put them into a nonlinear model.

[0042] In the embodiment of the present invention,

[0043] Step 1: Perform component analysis on the power amplifier output spectrum according to the nonlinear characteristics of the power amplifier and the carrier frequency of the input signal. Generally, select the corresponding nonlinear analysis order according to the difference in carrier frequencies. If the carrier spacing does not exceed the octave layer, only odd-order nonlinearities need to be considered. If it exceeds the octave layer, the corresponding multiple of nonlinear orders needs to be increased. The output signal frequency components will be distributed in the form of a linear combination of several carriers, and the sum of the linear combination coefficients is at most equal to the nonlinear order.

[0044] Step 2: Aliasing analysis, based on the power amplifier output signal frequency components analyzed in Step 1, find the secondary components whose frequencies are close to the signal carrier, and then estimate the spectral bandwidth of the corresponding secondary components according to the carrier signal bandwidth and the nonlinear order generated by the secondary components. Further, judge whether aliasing occurs based on the spectral bandwidth of the carrier signal and the frequency interval between the carrier and the secondary components. If aliasing occurs, go to Step 3; if no aliasing occurs, go to Step 4.

[0045] Step 3, Predict the regenerated intermodulation components. If it is judged in Step 3 that intermodulation components and the carrier have been aliased, at this time, the predistortion signal of the intermodulation components will undergo nonlinear intermodulation with the carrier again to generate regenerated intermodulation components. And due to the aliasing on the spectrum, the regenerated intermodulation components are also close to the carrier signal. At this time, it is necessary to calculate the nonlinear model of the regenerated intermodulation components corresponding to the corresponding frequencies according to the frequency generation expression of the regenerated intermodulation components.

[0046] Step 4, Predistortion signal calculation, multiply all the nonlinear basis functions near the carriers by the corresponding frequency coefficients and put them into a nonlinear model, and calculate the predistortion function through the iterative learning control method or the direct learning method. During the predistortion training process, the output signal of the transmitter needs to be continuously collected by the resampling channel for model training.

[0047] The digital predistortion method for processing secondary components of a harmonic multi-band transmitter provided by the embodiment of the present invention specifically includes:

[0048] (1) Analyze the components of the power amplifier output spectrum according to the non-linear characteristics of the power amplifier and the selection of the frequency of the input signal carrier. If there are harmonic or difference frequency components of the signal close to other carrier signals, start the corresponding intermodulation component compensation algorithm. If there is no such situation as harmonics or difference frequencies close to the carrier, directly call the traditional multi-band predistortion module for compensation.

[0049] (2) Aliasing analysis: Perform aliasing analysis based on the information of the carrier frequency and the signal bandwidth, and call the resampled signals of each frequency band to confirm the signal quality. If the carrier signal and the intermodulation component are aliased, call the predistortion model corresponding to the frequency to compensate for the distortion components of each frequency.

[0050] (3) Method for aliasing analysis: Analyze the frequency composition of the power amplifier output signal through polynomial calculation based on the frequencies of each carrier signal. The power amplifier model can use a polynomial model with a limited order: generally analyze up to the 3rd to 5th order. If there is a multiple relationship of more than 5 times between the carrier frequencies, a polynomial of a higher order needs to be used for analysis. Assume there are multiple signal carriers, which are x1(t)sin(ω1t), x2(t)sin(ω2t) …… x n (t)sin(ω n t), and the input value polynomial y = a1x + a2x 2 + a3x 3 Analyze the frequency composition of the output signal and take the components near each carrier frequency.

[0051] (4) Structure of the non-linear compensation model. The compensation for each carrier signal can use the traditional multi-band memory polynomial model. For the distortion components at other frequency points, the basis function substitution method is used to obtain them: Since the frequency of each distortion component is obtained by non-linearity of the carrier signal, the frequency points of the distortion components must be obtained by linear combination of multiple carrier frequencies, that is: ω x = b1ω x + b2ω x +…+ b n ω n Each basis function of the corresponding non-linear compensation function has a phase part and can be written in the product form corresponding to the linear combination of frequencies, that is: (b is an integer. Here, when b is negative, x b -(x * ) -b )

[0052] (5) Predict the regenerative intermodulation components. When calculating the frequencies of the nonlinear components before, it was calculated without the input of the predistortion signal. However, when there is a predistortion signal, these compensation components artificially added at the frequency points of the original nonlinear distortion components will pass through the power amplifier's nonlinearity and intermodulate with the carrier signal again to form regenerative intermodulation components. These components will also appear near the carrier and even overlap with the carrier when the overlap between the carrier and the intermodulation components is relatively severe, thus affecting the effect of nonlinear compensation. Therefore, supplementing the regenerative compensation model for the corresponding frequencies can greatly improve the nonlinear correction ability of this compensation structure under necessary circumstances.

[0053] (6) After determining the model, multiply all the basis functions near a carrier (including the basis functions of the regenerative intermodulation components) by the corresponding frequency coefficients and put them into a nonlinear model. The training of the predistortion parameters can be carried out using direct learning or iterative learning control methods. The advantage of the direct learning method is that it does not interrupt the signal transmission and is convenient for correcting the model parameters at any time. The iterative learning control method has higher accuracy and better compensation effect, but it requires training the predistortion signal and will interrupt the communication function during the training process.

[0054] To prove the creativity and technical value of the technical solution of the present invention, this part is an application embodiment of the technical solution of the claims on a specific product or related technology.

[0055] The digital predistortion method for processing the secondary components of a harmonic multi-band transmitter provided by the embodiment of the present invention can be applied to a mobile communication multi-band wireless transmitter.

[0056] It should be noted that the embodiments of the present invention can be implemented through hardware, software, or a combination of software and hardware. The hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those of ordinary skill in the art can understand that the above devices and methods can be implemented using computer-executable instructions and / or included in the processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The devices and their modules of the present invention can be implemented by hardware circuits of programmable hardware devices such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or field programmable gate arrays and programmable logic devices, can also be implemented by software executed by various types of processors, or can be implemented by a combination of the above hardware circuits and software, such as firmware.

[0057] Some positive effects have been achieved during the research and development or use of the embodiments of the present invention. Compared with the prior art, it indeed has great advantages. The following content will be described in combination with the data, charts, etc. in the experimental process.

[0058] Taking a dual-band transmitter as an example, the carrier frequencies of the two frequency bands are respectively set to 700 MHz and 1395 MHz, and the signal bandwidth is set to 20 MHz. Then the aliasing analysis module starts to run: Since the second carrier frequency is very close to the second harmonic of the first carrier, there will be second-order distortion components with center frequencies of 1400 MHz and 695 MHz approaching the carrier, and at the same time, fourth-order distortion components with center frequencies of 705 MHz and 1385 MHz will appear on the other side. Since the signal bandwidth is 20 MHz, aliasing will inevitably occur, so it is necessary to predict the regenerative intermodulation components.

[0059] The predicted intermodulation regeneration components here refer to the new intermodulation components generated at the positions of 1405 MHz and 690 MHz, as well as 710 MHz and 1380 MHz due to the re-intermodulation of the compensation signal and the carrier signal after compensating for the intermodulation components of 1400 MHz, 695 MHz, 705 MHz, and 1385 MHz. Then the number of non-linear components that need to participate in the compensation structure increases from 6 (including 2 carriers, 2 second-order components, and 2 fourth-order components) to 10 (4 more predicted intermodulation regeneration components). The model for each frequency band can be written as:

[0060]

[0061] Among them b1 and b2 are respectively the frequency linear combination coefficients, and Δω r is the frequency offset coefficient.

[0062] If the iterative learning control is used to train the predistortion parameters, first use the iterative learning control technology to adjust the signal, and optimize the output signal through the feedback iteration method to obtain the ideal predistortion input signal:

[0063] z(n) = z(n) + (y(n) - y′(n))u

[0064] Finally, use the least squares method to calculate the parameter vector of the predistortion model:

[0065] υ = (X H X) -1 X H z(n)

[0066] where X is the Vandermonde matrix composed of all in-band non-linear basis functions.

[0067] If the direct learning mode is used, v is directly initialized as a vector with the first item being 1 and other items being 0, and the parameter iteration update is performed through the following parameter update formula:

[0068] v (k+1) = v (k) + μ(X H X) -1 X H (x - y)

[0069] where y is the output signal of the power amplifier for extraction.

[0070] Figure 2 The following is the simulation result using Matlab software. The simulation process is as follows: The signals used are single-band signals with a bandwidth of 20 MHz for OFDM dual-band signals, and the frequencies of the two carriers are 700 MHz and 1395 MHz respectively. Since the frequencies of the two carriers are close to a two-fold relationship, the harmonic components and difference frequency components of the signal will appear near the carriers and overlap after passing through the power amplifier model. After training the ideal predistortion signal through iterative learning control, nonlinear models with and without predicted secondary components are used for modeling respectively. The signals reconstructed by the models are re-input into the power amplifier model to obtain two sets of output signals. The nonlinear model with predicted secondary components has a linearity improvement of nearly 10 dB. Similar conclusions can also be obtained from the comparison of the modeling accuracy in Table 1. Using the normalized mean square error to judge the modeling accuracy of the models, it can be seen that the modeling accuracy of the model with predicted secondary components is better than that of the model without secondary components in both frequency bands.

[0071] Table 1. Comparison of ILC (Iterative Learning Control) Signal Modeling Accuracy (NMSE)

[0072] Carrier 1 Carrier 2 Without secondary components -42.5 -44.5 With secondary components -45.1 -52.9

[0073] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope disclosed by the present invention and within the spirit and principle of the present invention should be covered by the protection scope of the present invention.

Claims

1. A digital predistortion method for processing the secondary components of a harmonic multi-band transmitter, characterized in that, The model calculation and predistortion signal generation of the method are both completed in the transmitter baseband processor; through pre - conducted frequency component analysis and signal bandwidth analysis, the frequencies and nonlinear models of the secondary components in the output signal of the power amplifier and the nonlinear models of the regenerated spectral components after prediction compensation are obtained. These models are used to perform nonlinear compensation on the power amplifier output signal at multiple frequency points, so that the multi - band transmitter obtains linear output characteristics; It includes: Step 1, perform component analysis of the power amplifier output spectrum according to the nonlinear characteristics of the power amplifier and the selection of the frequency of the input signal carrier; Step 2, aliasing analysis, perform aliasing analysis according to the information of the carrier frequency and signal bandwidth, and call the back - sampled signals of each frequency band to confirm the signal quality; Step 3, predict the regenerated intermodulation components; Step 4, multiply all the basis functions near a carrier by the corresponding frequency coefficients and then put them into a nonlinear model; In the component analysis of the power amplifier output spectrum in Step 1, if the harmonic or difference - frequency components of the signal are close to other carrier signals, start the corresponding intermodulation component compensation algorithm; If there is no situation where the harmonic difference frequency is close to the carrier, directly call the traditional multi - band predistortion module for compensation.

2. The digital predistortion method for processing the secondary components of a harmonic multi-band transmitter according to claim 1, wherein In Step 2, if the carrier signal and the intermodulation component are aliased, call the predistortion model corresponding to the frequency to compensate the distortion components of each frequency; The method adopted in the aliasing analysis in Step 2 is: calculate the frequency composition analysis of the power amplifier output signal through polynomial calculation according to the frequencies of each carrier signal.

3. The digital predistortion method for processing the secondary components of a harmonic multi-band transmitter according to claim 2, characterized in that The method adopted in the aliasing analysis specifically includes: The power amplifier model uses a polynomial model with a limited order: generally analyze up to the 3rd to 5th order. If there is a multiple relationship of more than 5 times between the carrier frequencies, a polynomial of a higher order needs to be used for analysis; multiple signal carriers are respectively x1(t)sin(ω1t), x2(t)sin(ω2t)……x n (t)sin(ω n t), input - value polynomials y = a1x + a2x 2 + a3x 3 Analyze the frequency composition of the output signal and take the components near each carrier frequency.

4. The digital predistortion method for processing the secondary components of a harmonic multi-band transmitter according to claim 1, characterized in that The pre-distortion model is a non-linear compensation model. In the non-linear compensation model, the compensation for each carrier signal uses the traditional multi-band memory polynomial model, and the distortion components corresponding to other frequency points are obtained by the basis function substitution method: Since the frequency of each distortion component is obtained by the non-linearity of the carrier signal, the frequency points of the distortion components must be obtained by the linear combination of multiple carrier frequencies, that is: ω x = b1ω x + b2ω x + … + b n ω n ; Each basis function corresponding to the nonlinear compensation function has a phase part and is written in the product form corresponding to the linear combination of frequencies, that is: where b is an integer, and when b is negative, x b =(x*) -b .

5. The digital predistortion method for processing the secondary components of a harmonic multi-band transmitter according to claim 1, characterized in that, In Step 4, the training of the predistortion parameters is carried out by using the direct learning or iterative learning control method.

6. A computer device, characterized in that, The computer device includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor executes the steps of the digital predistortion method for processing the secondary components of the harmonic multi - band transmitter as described in any one of claims 1 - 5.

7. A computer - readable storage medium stores a computer program. When the computer program is executed by a processor, the processor executes the steps of the digital predistortion method for processing the secondary components of the harmonic multi - band transmitter as described in any one of claims 1 - 5.

8. An information data processing terminal, characterized in that The information data processing terminal is used to implement the steps of the digital predistortion method for processing the secondary components of the harmonic multi - band transmitter as described in any one of claims 1 - 5.

Images