Calibration parameter determination method and device, equipment, storage medium and chip

Abstract

The present disclosure provides a calibration parameter determination method, comprising: determining a first output signal and a first matrix based on a preset bandwidth signal, the first matrix being an inverse matrix of an autocorrelation matrix of a primary function matrix, the primary function matrix corresponding to the preset bandwidth signal; and determining a first calibration parameter based on the preset bandwidth signal, the first output signal and the first matrix. According to the method disclosed by the invention, the calibration coefficient of the preset bandwidth signal is determined through the preset bandwidth signal, the first output signal and the first matrix, so that the determination rate of the first calibration coefficient is improved, and the accuracy of the first calibration coefficient is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of signal calibration, and in particular, to a method, apparatus, device, storage medium, and chip for determining calibration parameters. Background Art

[0002] Wireless communication systems generally require minimizing the non-linearity of transmitted signals while ensuring efficient use of energy. However, high efficiency and high linearity are contradictory in practical systems. The radio frequency power amplifier (RF-PA) is one of the most important and energy-consuming devices in a wireless communication system, and its design specifications are closely related to aspects such as the performance and cost of the transmitter. As a typical non-linear device, the PA also has an irreconcilable contradiction between operating efficiency and linearity.

[0003] At the same time, the power amplifier is one of the main devices causing non-linearity in a communication system. Ideally, there is a linear relationship between the input and output of the power amplifier. However, to improve the operating efficiency of the power amplifier, it is usually operated in a high-power range, resulting in gain compression and non-linearity. To compensate for the non-linearity of the transmitter and thus improve the efficiency and communication quality of the transmitter, many linearization techniques have been proposed, such as: feedforward, feedback, analog pre-distortion (APD) techniques, and digital pre-distortion (DPD) techniques. Among the above techniques, the DPD technique can achieve high-precision compensation for PA non-linear distortion in a more flexible manner and at a moderate cost by configuring pre-distortion devices in the digital domain, and thus has become one of the mainstream linearization techniques in communication systems. Summary of the Invention

[0004] The present disclosure provides a method, apparatus, device, storage medium, and chip for determining calibration parameters to determine the calibration coefficient of a preset bandwidth signal.

[0005] In a first aspect embodiment of the present disclosure, a method for determining calibration parameters is proposed. The method includes: determining a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; determining a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix.

[0006] In some embodiments, determining the first output signal based on the preset bandwidth signal includes: performing frequency conversion processing on the preset bandwidth signal to determine a first signal; performing sampling processing on the first signal to determine the first output signal.

[0007] In some embodiments, determining a first calibration parameter based on a preset bandwidth signal, a first output signal, and a first matrix includes: determining a first cross-correlation vector based on the preset bandwidth signal, the first output signal, and a basis function matrix; and determining the first calibration parameter based on the first cross-correlation vector and the first matrix.

[0008] In some embodiments, the method further includes: iterating on the first calibration parameter based on the preset bandwidth signal and the first matrix with a preset step size; and stopping the iteration when a preset number of iterations is reached to determine a second calibration parameter.

[0009] In some embodiments, iterating on the first calibration parameter based on the preset bandwidth signal and the first matrix with a preset step size includes: determining a first calibration signal based on the preset bandwidth signal and the first calibration parameter; determining a second output signal based on the first calibration signal; and determining a second calibration parameter based on the preset bandwidth signal, the second output signal, and the first matrix.

[0010] In some embodiments, determining a second calibration parameter based on the preset bandwidth signal, the second output signal, and the first matrix includes: determining a second cross-correlation vector based on the preset bandwidth signal, the second output signal, and the basis function matrix; and determining the second calibration parameter based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter.

[0011] An embodiment of the second aspect of the present disclosure provides a calibration parameter determination device, which includes: a first processing unit configured to determine a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is an inverse matrix of an autocorrelation matrix of a basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; and a second processing unit configured to determine a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix.

[0012] An embodiment of the third aspect of the present disclosure provides a communication device, which includes a processor and a memory. The memory stores a computer program, and the processor executes the computer program stored in the memory so that the device executes the method described in the first aspect above.

[0013] An embodiment of the fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause a computer to execute the method described in the first aspect of the present disclosure.

[0014] An embodiment of the fifth aspect of the present disclosure provides a chip, which includes at least one processor and a communication interface; the communication interface is configured to receive a signal input to the chip or a signal output from the chip, and the processor communicates with the communication interface and implements the method described in the first aspect of the present disclosure through logic circuits or by executing code instructions.

[0015] In summary, according to the calibration parameter determination method proposed by the present disclosure, based on a preset bandwidth signal, a first output signal and a first matrix are determined. The first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal. Based on the preset bandwidth signal, the first output signal and the first matrix, a first calibration parameter is determined. The method of the present disclosure determines the calibration coefficient of the preset bandwidth signal through the preset bandwidth signal, the first output signal and the first matrix, improving the determination rate of the first calibration coefficient and the accuracy of the first calibration coefficient.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure and do not constitute an improper limitation of the present disclosure.

[0018] Figure 1 It is a diagram of an application scenario of a calibration parameter determination method provided by an embodiment of the present disclosure;

[0019] Figure 2 It is a flowchart of a calibration parameter determination method provided by an embodiment of the present disclosure;

[0020] Figure 3 It is a flowchart of another calibration parameter determination method provided by an embodiment of the present disclosure;

[0021] Figure 4 It is a flow example diagram of a calibration parameter determination method provided by an embodiment of the present disclosure;

[0022] Figure 5 It is a flowchart of yet another calibration parameter determination method provided by an embodiment of the present disclosure;

[0023] Figure 6 It is a flowchart of another calibration parameter determination method provided by an embodiment of the present disclosure;

[0024] Figure 7 It is a flowchart of yet another calibration parameter determination method provided by an embodiment of the present disclosure;

[0025] Figure 8 It is a flow example diagram of yet another calibration parameter determination method provided by an embodiment of the present disclosure;

[0026] Figure 9 It is a flowchart of a calibration parameter application method provided by an embodiment of the present disclosure;

[0027] Figure 10Schematic structural diagram of a calibration parameter determination device provided by an embodiment of the present disclosure;

[0028] Figure 11 Schematic structural diagram of a communication device provided by an embodiment of the present disclosure;

[0029] Figure 12 Schematic structural diagram of a chip provided by an embodiment of the present disclosure. Detailed implementation manners

[0030] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the embodiments of the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present disclosure as detailed in the appended claims.

[0031] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the embodiments of the present disclosure. The singular forms "a" and "the" used in the embodiments of the present disclosure and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0032] It should be understood that although the terms first, second, third, etc. may be used in the embodiments of the present disclosure to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the embodiments of the present disclosure, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "when" as used herein may be interpreted as "when" or "when" or "in response to determining".

[0033] For ease of understanding, the background and application scenarios related to the present application are described.

[0034] The power amplifier is one of the main devices that cause the nonlinearity of communication systems. Ideally, there is a linear relationship between the input and output of the power amplifier. However, to improve the working efficiency of the power amplifier, it is usually operated in a high-power range, which leads to gain compression and nonlinearity. To compensate for the nonlinearity of the transmitter and thus improve the efficiency and communication quality of the transmitter, many linearization techniques have been proposed, such as feedforward, feedback, analog predistortion techniques, and DPD techniques. Among the above techniques, the DPD technique configures predistortion devices in the digital domain, enabling it to achieve high-precision compensation for PA nonlinear distortion in a more flexible manner and at a moderate cost, thus becoming one of the mainstream linearization techniques in communication systems currently.

[0035] A typical digital predistortion calibration scenario, for example Figure 1 As shown, in a scenario with DPD calibration: The forward digital predistortion calibration link is jointly composed of the digital predistortion DPD module 101, the analog-to-digital conversion module (Digital-to-Analog Convertor, DAC) 102, the quadrature modulation module 103, and the radio frequency power amplifier (Radio Frequency Power Amplifier, RF-PA) module 104. After the signal is processed by the DPD module in the forward digital predistortion calibration link, the nonlinear distortion of the RF-PA is pre-corrected. The pre-calibrated signal passes through the RF-PA to output an approximately linear radio frequency signal, thereby improving the quality of the transmitted signal and reducing the bit error rate of the transmitted signal. In a scenario without DPD calibration, the forward link is composed of modules 102, 103, and 104.

[0036] It can be understood that the description of the embodiments of the present disclosure is to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and does not constitute a limitation on the calibration parameter determination method, device, and storage medium proposed by the embodiments of the present disclosure. Those of ordinary skill in the art know that with the evolution of the system architecture and the emergence of new service scenarios, the technical solutions proposed by the embodiments of the present disclosure are equally applicable to similar technical problems.

[0037] Figure 2 It is a flowchart of a calibration parameter determination method provided by an embodiment of the present disclosure. As Figure 2 shown, the calibration parameter determination method includes steps 201-204.

[0038] Step 201, based on a preset bandwidth signal, determine a first output signal and a first matrix.

[0039] In some embodiments, Figure 2 The calibration parameter determination method of the embodiment can be executed by a terminal. For example, the terminal can include electronic devices such as mobile phones and tablets. Or, Figure 2The calibration parameter determination method of the embodiment can also be executed by a chip, which may include a SOC chip or other processing chips, and the present disclosure does not limit this.

[0040] Hereinafter, the present disclosure will be described by taking the terminal executing the above method as an example.

[0041] In some embodiments, the calibration parameter determination method can be executed by a transmitting device.

[0042] In some embodiments, a preset bandwidth signal can be input into a calibration path, and a first output signal can be determined through processes such as frequency conversion processing and sampling processing.

[0043] In some embodiments, the first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal. In other words, the first matrix can correspond to the preset bandwidth signal.

[0044] In some embodiments, the basis function matrices corresponding to preset bandwidth signals with the same signal length, and the corresponding first matrices can be the same, thereby reducing the amount of computation when determining calibration parameters and improving the calibration parameter determination rate.

[0045] In some embodiments, the first matrix can be stored in the execution entity executing this method to reduce the amount of computation when determining calibration parameters and improve the calibration parameter determination rate. Taking the execution entity executing this method as a terminal as an example for illustration, the first matrix can be stored in the terminal. At the same time, the terminal also stores a corresponding lookup table of the preset bandwidth signal and the first matrix. Then, the terminal can look up the first matrix corresponding to the first preset bandwidth signal in the above corresponding lookup table, but it is not limited thereto. The present disclosure does not limit the manner of determining the first matrix.

[0046] Step 202, determine a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix.

[0047] In some embodiments, a first cross-correlation vector of the preset bandwidth signal and the first output signal is determined based on the preset bandwidth signal and the first output signal, and then the first calibration parameter is determined based on the first cross-correlation vector and the first matrix corresponding to the preset bandwidth signal.

[0048] In summary, according to the calibration parameter determination method proposed by the present disclosure, it includes: determining a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; determining a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix. The method of the present disclosure determines the calibration coefficient of the preset bandwidth signal through the preset bandwidth signal, the first output signal, and the first matrix, improves the determination rate of the first calibration coefficient, and improves the accuracy of the first calibration coefficient.

[0049] Figure 4 A flow chart of a calibration parameter determination method proposed in an embodiment of the present disclosure is shown in FIG. Figure 4 As shown, in Figure 2 Based on the embodiment shown, Figure 2 Further explanation includes steps 401-404.

[0050] Step 401: Perform frequency conversion processing on a preset bandwidth signal to determine a first signal.

[0051] In some embodiments, the terminal may perform frequency conversion processing on the preset bandwidth signal to determine the first signal.

[0052] In some embodiments, the first signal is a signal obtained by frequency conversion processing of a preset bandwidth signal, wherein the first signal is an analog signal.

[0053] In some embodiments, the preset bandwidth signal may be a digital signal or an analog signal, which is not limited in the present disclosure.

[0054] In some embodiments of the present disclosure, the preset bandwidth signal may be converted from a digital signal to an analog signal by a device such as a signal source, so as to perform frequency conversion processing on the converted preset bandwidth signal.

[0055] For example, see Figure 4 , Figure 4 An example flow chart of a calibration coefficient determination method provided for an embodiment of the present disclosure, the preset bandwidth signal may be a pre-stored calibration signal extracted in step 402, and the terminal may send the pre-stored calibration signal extracted in 402 to a path to be calibrated, i.e., step 405, to perform frequency conversion processing on the pre-stored calibration signal to determine the first signal.

[0056] Step 402: Sampling the first signal to determine a first output signal.

[0057] In some embodiments, the terminal samples the first signal to determine the first output signal. In other words, the terminal may sample the preset bandwidth signal after frequency conversion to determine the first output signal.

[0058] In some embodiments, the first signal is a continuous signal and needs to be discretely sampled and converted into a digital baseband signal, ie, a first output signal.

[0059] In some embodiments, the sampling rate selected when sampling the first signal should satisfy the Nyquist sampling theorem, that is, the sampling rate should be greater than or equal to twice the highest frequency of the preset bandwidth signal to ensure that signal aliasing does not occur when sampling the preset bandwidth signal.

[0060] Exemplarily, refer to Figure 4 , the path to be calibrated can send the first output signal obtained in step 405 to the analog-to-digital conversion module for sampling processing, that is, step 406, to convert the first signal from a continuous signal to a discrete signal, and obtain the first output signal.

[0061] Step 403, determine the first cross-correlation vector based on the preset bandwidth signal, the first output signal, and the basis function matrix.

[0062] In some embodiments, the terminal can determine the autocorrelation matrix of the basis function based on the preset bandwidth signal, and then determine the first cross-correlation vector based on the preset bandwidth signal, the first output signal, and the autocorrelation matrix of the basis function matrix, so as to determine the first calibration parameter.

[0063] In some embodiments, the basis function matrix and the autocorrelation matrix of the basis function matrix correspond to the preset bandwidth signal. Optionally, the basis function matrix and the autocorrelation matrix of the basis function matrix can be stored in the execution entity that executes this method. The execution entity can find the basis function matrix corresponding to the preset bandwidth signal and the autocorrelation matrix of the basis function matrix in the corresponding table by looking up the corresponding table through the preset bandwidth signal, so as to reduce the computational amount when determining the calibration parameter and improve the rate of determining the calibration parameter.

[0064] In some embodiments, the first cross-correlation vector can be expressed as Φ H (x1)(y1 - x1), where Φ H (x1) represents the autocorrelation matrix of the basis function matrix, y1 represents the first output signal, and x1 represents the preset bandwidth signal.

[0065] Exemplarily, refer to Figure 4 , step 407 uses the sampled distortion signal (i.e., the first output signal) output by step 406 and the reference input in step 403 (the pre-stored calibration signal extracted by 402, i.e., the pre-stored bandwidth signal), and uses the autocorrelation matrix of the basis function matrix corresponding to the reference input to generate a cross-correlation vector (i.e., the first cross-correlation vector).

[0066] Step 404, determine the first calibration parameter based on the first cross-correlation vector and the first matrix.

[0067] In some embodiments, the terminal can determine the first calibration parameter based on the first cross-correlation vector and the first matrix.

[0068] In some embodiments, the first calibration parameter can be determined by a second-order algorithm. Among them, the second-order algorithm is, for example: Gauss-Newton algorithm, Projected Gradient Descent (PGD) algorithm, etc. The present disclosure does not limit this.

[0069] Exemplarily, refer to Figure 4 , step 408 determines the DPD coefficient based on the cross-correlation vector (i.e., the first cross-correlation vector) generated by step 407 and the pre-stored matrix (i.e., the first matrix) extracted by step 403.

[0070] In summary, according to the calibration parameter determination method proposed by the present disclosure, it includes: performing frequency conversion processing on a preset bandwidth signal to determine a first signal; performing sampling processing on the first signal to determine a first output signal; determining a first cross-correlation vector based on the preset bandwidth signal, the first output signal, and the basis function matrix; determining a first calibration parameter based on the first cross-correlation vector and the first matrix. The method of the present disclosure inputs the preset bandwidth signal into the calibration path to determine the first output signal, and uses the correlation of the first output signal of the preset bandwidth signal to determine the first cross-correlation vector through the preset bandwidth signal, the first output signal, and the basis function matrix, and then determines the first calibration parameter based on the first cross-correlation vector and the first matrix, improving the determination rate of the first calibration coefficient and the accuracy of the first calibration coefficient. In addition, the basis function matrix and the first matrix can be stored in the execution entity executing this method, reducing the amount of calculation during calibration parameter determination and further improving the determination rate of the first calibration coefficient.

[0071] Figure 5 is a flowchart of a calibration parameter determination method proposed by an embodiment of the present disclosure. As Figure 5 shown, on the basis of the embodiments shown in Figure 2 and 3 , further explained, when it is necessary to iterate the determined first calibration parameter to improve the accuracy of the first calibration parameter, steps 501 and 502 are further included.

[0072] Step 501, iterating the first calibration parameter based on the preset bandwidth signal and the first matrix with a preset step size.

[0073] In some embodiments, the first calibration parameter can be configured to the DPD module, and the preset bandwidth signal is sent into the DPD module to generate a first calibration signal calibrated by the first calibration parameter; and the first calibration signal is sent into the same to-be-calibrated path as above to determine a second output signal, and then a second cross-correlation vector is determined through the preset bandwidth signal, the second output signal, and the basis function matrix, so as to iterate the first calibration parameter using the second cross-correlation vector, the first matrix, and the preset step size.

[0074] Step 502, when the preset number of iterations is reached, stop the iteration to determine the second calibration parameter.

[0075] In some embodiments, the iteration can be stopped by a preset number of iterations, and the first calibration parameter after iteration is determined as the second calibration parameter.

[0076] In some embodiments, the preset number of iterations can be determined based on the computing power of the device executing this method. For example, for a device with greater computing power, the preset number of iterations can be more; for a device with smaller computing power, the preset number of iterations can be less. The preset number of iterations can also be determined based on the requirement for the accuracy of the calibration parameter. For example, the higher the requirement for the accuracy of the calibration parameter, the more the preset number of iterations; the lower the requirement for the accuracy of the calibration parameter, the fewer the preset number of iterations. The present disclosure does not limit the setting of the preset number of iterations.

[0077] In summary, the calibration parameter determination method proposed according to the present disclosure includes: iterating the first calibration parameter with a preset step size based on a preset bandwidth signal and a first matrix; when the preset number of iterations is reached, stopping the iteration to determine the second calibration parameter. The method of the present disclosure further improves the accuracy of the determined calibration parameter through iteration.

[0078] Figure 6 is a schematic flowchart of a calibration parameter determination method proposed for an embodiment of the present disclosure. As Figure 6 shown, based on the embodiment shown in Figure 5 step 501 is further explained, including steps 601-603.

[0079] Step 601, determine a first calibration signal based on a preset bandwidth signal and a first calibration parameter.

[0080] In some embodiments, the terminal can determine a first calibration signal based on a preset bandwidth signal and a first calibration parameter, laying a foundation for determining a second output signal.

[0081] In some embodiments, the determined first calibration parameter can be configured into the DPD module, and the preset bandwidth signal is input into the DPD module configured with the first calibration parameter to determine the first calibration signal. In other words, the first calibration signal is the preset bandwidth signal calibrated by the first calibration parameter.

[0082] In some embodiments, when the first calibration parameter is configured into the DPD module, the modeling of the DPD module can be expressed by the following formula:

[0083] z = Φ(x)·α (Equation 1)

[0084] where z represents the first calibration signal, α represents the first calibration coefficient, x represents the preset bandwidth signal, and Φ(x) represents the basis function matrix corresponding to the preset bandwidth signal.

[0085] Exemplarily, refer to Figure 4, when the preset number of iterations is not reached, the terminal can configure the DPD coefficients (i.e., the first calibration coefficients) determined in step 408 into the DPD module (i.e., step 410), and input the pre-stored calibration signal (i.e., the preset bandwidth signal) extracted in 402 into the DPD module (i.e., step 404) to determine the first calibration signal. It should be understood that when the terminal determines the first calibration parameter, at this time, there are no coefficients in the DPD module, and the terminal can skip step 404 and directly input the pre-stored calibration signal (i.e., the preset bandwidth signal) extracted in 402 into the calibration path (i.e., step 405).

[0086] Step 602, determine a second output signal based on the first calibration signal.

[0087] In some embodiments, the terminal can determine a second output signal based on the first calibration signal to determine a second calibration parameter.

[0088] In some embodiments, the terminal can perform frequency conversion processing on the first calibration signal and sample the frequency-converted first calibration signal to determine a second output signal.

[0089] In some embodiments, the second output signal is a signal obtained by performing frequency conversion processing and sampling processing on the first calibration signal.

[0090] In some embodiments, the first calibration signal is a continuous signal and needs to be discretely sampled and converted into a digital baseband signal, that is, the second output signal.

[0091] In some embodiments, the sampling rate selected when sampling the frequency-converted first calibration signal should satisfy the Nyquist sampling theorem, that is, the above sampling rate should be greater than or equal to twice the highest frequency of the frequency-converted first calibration signal to ensure that signal aliasing does not occur during sampling.

[0092] In some embodiments, if the first calibration signal passes through the path to be calibrated and the non-linear transfer function during sampling is f(·), then the second output signal can be expressed as:

[0093] y = f(z) = f(Φ(x)·α) (Equation 2)

[0094] where y represents the second output signal, z represents the first calibration signal, and f(·) represents the non-linear transfer function.

[0095] Exemplarily, referring to Figure 4 , the terminal can input the first calibration signal output in step 404 into the path to be calibrated (i.e., step 406) to implement frequency conversion processing on the first calibration signal. Then, sample the frequency-converted first calibration signal output in step 405 (i.e., step 406) to obtain a second output signal.

[0096] Step 603: Determine a second calibration parameter based on a preset bandwidth signal, a second output signal, and a first matrix.

[0097] In some embodiments, a second cross-correlation vector of the preset bandwidth signal and the second output signal is determined based on the preset bandwidth signal and the second output signal, and then the second calibration parameter is determined based on the second cross-correlation vector and the first matrix corresponding to the preset bandwidth signal.

[0098] In summary, the calibration parameter determination method proposed according to the present disclosure includes: determining a first calibration signal based on a preset bandwidth signal and a first calibration parameter; determining a second output signal based on the first calibration signal; and determining a second calibration parameter based on the preset bandwidth signal, the second output signal, and the first matrix. In the method of the present disclosure, a first calibration signal is generated through the preset bandwidth signal and the first calibration parameter, and the first calibration signal is sent into a to-be-calibrated path used when determining the first calibration parameter to obtain a second output signal. By using the correlation between the second output signal and the preset bandwidth signal, the second calibration parameter is determined through the preset bandwidth signal, the second output signal, and the first matrix to implement iteration of the first calibration parameter and improve the accuracy of the determined calibration parameter.

[0099] Figure 7 The flowchart of a calibration parameter determination method proposed for an embodiment of the present disclosure is as Figure 7 shown. Based on the embodiment shown in Figure 6 Step 603 is further explained, including Steps 701 and 702.

[0100] Step 701: Determine a second cross-correlation vector based on the preset bandwidth signal, the second output signal, and a basis function matrix.

[0101] In some embodiments, the terminal may determine an autocorrelation matrix of basis functions based on the preset bandwidth signal, and then determine a second cross-correlation vector based on the preset bandwidth signal, the second output signal, and the autocorrelation matrix of the basis function matrix to determine the second calibration parameter.

[0102] In some embodiments, the basis function matrix and the autocorrelation matrix of the basis function matrix correspond to the preset bandwidth signal. Optionally, the basis function matrix and the autocorrelation matrix of the basis function matrix may be stored in an execution entity executing this method. The execution entity may, by looking up a corresponding table through the preset bandwidth signal, look up the basis function matrix corresponding to the preset bandwidth signal and the autocorrelation matrix of the basis function matrix in the corresponding table to reduce the amount of computation when determining the calibration parameter and improve the calibration parameter determination rate.

[0103] In some embodiments, the second cross-correlation vector may be expressed as Φ H (x1)(y2 - x1), where ΦH (x1) represents the autocorrelation matrix of the basis function matrix, y2 represents the second output signal, and x1 represents the preset bandwidth signal.

[0104] Step 702: Determine a second calibration parameter based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter.

[0105] In some embodiments, the terminal can determine the second calibration parameter based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter to implement iteration of the first calibration parameter.

[0106] In some embodiments, the second calibration parameter can be determined by a second-order algorithm. For example, the second-order algorithm can be: the Gauss-Newton algorithm, the projected gradient descent algorithm, etc. The present disclosure does not limit this.

[0107] Taking the Gauss-Newton algorithm as an example for illustration, the second calibration parameter can be determined by the following formula:

[0108] α2 = α - μ(Φ H (x1)Φ(x1)) -1 Φ H (x1)(y2 - x1) (Equation 3)

[0109] Where α2 represents the second calibration parameter, α represents the first calibration parameter, μ represents the preset step size, (Φ H (x1)Φ(x1)) -1 represents the first matrix, Φ H (x1) represents the basis function matrix of the preset bandwidth signal, Φ H (x1)(y2 - x1 represents the second cross-correlation vector between the preset bandwidth signal and the first calibration signal, y2 represents the first calibration signal, and x1 represents the preset bandwidth signal.

[0110] In summary, the calibration parameter determination method proposed according to the present disclosure includes: determining a second cross-correlation vector based on the preset bandwidth signal, the second output signal, and the basis function matrix; determining a second calibration parameter based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter. By using the correlation between the preset bandwidth signal and the second output signal, the method of the present disclosure determines the second cross-correlation vector by using the basis function matrix of the preset bandwidth signal, and iterates the first calibration parameter with the preset step size based on the second cross-correlation vector, the first matrix, and the first calibration parameter, thereby realizing the determination of the second calibration parameter and further improving the accuracy of the determined calibration parameter.

[0111] The following is an exemplary description of the method of the present disclosure.

[0112] In some embodiments, the principle block diagram of a calibration parameter determination method is asFigure 8 as shown

[0113] Before using DPD, it is necessary to first pre-train the DPD coefficients (i.e., the above-mentioned first calibration parameters) for compensating the RF-PA non-linearity for the radio frequency power amplifier, that is, the calibration process. Among them, the ideal digital signal (i.e., the above-mentioned preset bandwidth signal) emitted by the signal source is first sent into the 801 predistortion module (this step can be skipped in the first training), passed through the 802 digital-to-analog converter and the 803 quadrature modulator, and then enters the 804 radio frequency power amplifier to generate non-linear distortion; in the feedback loop, the signal containing PA non-linear distortion (i.e., the above-mentioned first output signal) is sent into the feedback link through the 805 coupler, and the down-conversion of the analog signal is realized through the 806 quadrature demodulator. After passing through the 207 analog-to-digital converter (ADC), the received feedback analog signal is converted into a digital signal and sent into the 808 DPD coefficient extraction module to extract the DPD coefficients (i.e., the first calibration parameters) for correcting PA non-linearity in the current scenario. When iteration is required, after inputting the currently extracted DPD coefficients, the above process is repeated until the iteration ends.

[0114] In some embodiments, a flowchart example of a method for applying calibration parameters is as Figure 9 shown

[0115] In some embodiments, the terminal can, based on the service signal generated in step 913, execute step 914 to read the DPD coefficients (i.e., the above-mentioned first reference signal or second reference signal) corresponding to the service signal, and through step 915, input the DPD coefficients into the DPD forward module to perform pre-distortion operations on the current service signal, so as to output the DPD calibration signal output in step 916. Finally, the signal is successively subjected to steps 917-919 to enable the signal to pass through the remaining modules of the forward link, thereby realizing the calibration process of the service signal.

[0116] Therefore, the present solution has the following beneficial effects:

[0117] 1. The method of the present disclosure determines the calibration coefficients of the preset bandwidth signal through the preset bandwidth signal, the first output signal, and the first matrix, improving the determination rate of the first calibration coefficients and the accuracy of the first calibration coefficients.

[0118] 2. By pre-storing the preset bandwidth signal, the basis function matrix, the autocorrelation matrix of the basis function matrix, and the first matrix, the amount of computation for determining the calibration coefficients is reduced, and the determination rate of the calibration coefficients is improved.

[0119] 3. By utilizing the correlation between the preset bandwidth signal and the second output signal, determining the second cross-correlation vector using the basis function matrix of the preset bandwidth signal, and iterating the first calibration parameter at a preset step size based on the second cross-correlation vector, the first matrix, and the first calibration parameter, thereby realizing the determination of the second calibration parameter and further improving the accuracy of the determined calibration parameter.

[0120] Figure 10 FIG. 4 is a schematic structural diagram of a calibration parameter determination device 1000 provided by an embodiment of the present disclosure. The communication device includes:

[0121] A first processing unit 1010, configured to determine a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal;

[0122] A second processing unit 1020, configured to determine a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix.

[0123] In some embodiments, the first processing unit 1010 is further configured to perform frequency conversion processing on the preset bandwidth signal to determine a first signal; and perform sampling processing on the first signal to determine a first output signal.

[0124] In some embodiments, the second processing unit 1020 is further configured to determine a first cross-correlation vector based on the preset bandwidth signal, the first output signal, and the basis function matrix; and determine the first calibration parameter based on the first cross-correlation vector and the first matrix.

[0125] In some embodiments, the second processing unit 1020 is further configured to iterate the first calibration parameter at a preset step size based on the preset bandwidth signal and the first matrix; and stop iterating when a preset number of iterations is reached to determine a second calibration parameter.

[0126] In some embodiments, the second processing unit 1020 is further configured to determine a first calibration signal based on the preset bandwidth signal and the first calibration parameter; determine a second output signal based on the first calibration signal; and determine a second calibration parameter based on the preset bandwidth signal, the second output signal, and the first matrix.

[0127] In some embodiments, the second processing unit 1020 is further configured to determine a second cross-correlation vector based on the preset bandwidth signal, the second output signal, and the basis function matrix; and determine the second calibration parameter based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter.

[0128] In summary, the calibration parameter determination device proposed according to the present disclosure includes: a first processing unit configured to determine a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is the inverse matrix of the autocorrelation matrix of the basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; and a second processing unit configured to determine a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix. The method of the present disclosure determines the calibration coefficient of the preset bandwidth signal through the preset bandwidth signal, the first output signal, and the first matrix, improving the determination rate and accuracy of the first calibration coefficient.

[0129] Since the device provided in the embodiments of the present disclosure corresponds to the methods provided in the above several embodiments, the implementation manners of the methods are also applicable to the device provided in this embodiment and will not be described in detail in this embodiment.

[0130] In the above embodiments provided in the present application, the methods and devices provided in the embodiments of the present application are introduced. To implement the various functions in the methods provided in the embodiments of the present application, a communication device may include a hardware structure and software modules, and implement the above various functions in the form of a hardware structure, a software module, or a combination of a hardware structure and a software module. A certain function among the above various functions may be executed in the form of a hardware structure, a software module, or a combination of a hardware structure and a software module.

[0131] Figure 11 FIG. 1100 is a schematic structural diagram of a communication device 1100 provided in an embodiment of the present application. The communication device 1100 may be a network device, a terminal device, a chip, a chip system, or a processor that supports the network device to implement the above method, or a chip, a chip system, or a processor that supports the terminal device to implement the above method. The device may be used to implement the method described in the above method embodiment, and for specific reference, please refer to the description in the above method embodiment.

[0132] The communication device 1100 may include one or more processors 1101. The processor 1101 may be a general-purpose processor or a special-purpose processor, etc. For example, it may be a baseband processor or a central processing unit. The baseband processor may be used to process communication protocols and communication data, and the central processing unit may be used to control a communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU, or a CU, etc.), execute a computer program, and process data of the computer program.

[0133] Optionally, the communication device 1100 may further include one or more memories 1102, on which a computer program 1104 may be stored, and the processor 1101 executes the computer program 1104 so that the communication device 1100 performs the method described in the above method embodiment. Optionally, data may also be stored in the memory 1102. The communication device 1100 and the memory 1102 may be provided separately or integrated together.

[0134] Optionally, the communication device 1100 may further include a transceiver 1105 and an antenna 1106. The transceiver 1105 may be referred to as a transceiver unit, a transceiver, or a transceiver circuit, etc., and is used to implement a transceiver function. The transceiver 1105 may include a receiver and a transmitter, the receiver may be referred to as a receiver or a receiving circuit, etc., and is used to implement a receiving function; the transmitter may be referred to as a transmitter or a transmitting circuit, etc., and is used to implement a transmitting function.

[0135] Optionally, the communication device 1100 may further include one or more interface circuits 11011. The interface circuit 11011 is used to receive code instructions and transmit them to the processor 1101. The processor 1101 executes the code instructions to enable the communication device 1100 to execute the method described in the above method embodiment.

[0136] In one implementation, the processor 1101 may include a transceiver for implementing receiving and sending functions. For example, the transceiver may be a transceiver circuit, an interface, or an interface circuit. The transceiver circuit, interface, or interface circuit for implementing the receiving and sending functions may be separate or integrated. The above-mentioned transceiver circuit, interface, or interface circuit may be used for reading and writing code / data, or the above-mentioned transceiver circuit, interface, or interface circuit may be used for transmitting or delivering signals.

[0137] In one implementation, the processor 1101 may store a computer program 1103, which runs on the processor 1101 and enables the communication device 1100 to perform the method described in the above method embodiment. The computer program 1103 may be fixed in the processor 1101, in which case the processor 1101 may be implemented by hardware.

[0138] In one implementation, the communication device 1100 may include circuitry that can implement the functions of transmitting, receiving, or communicating in the foregoing method embodiments. The processors and transceivers described in this application may be implemented on an integrated circuit (IC), analog IC, radio frequency integrated circuit (RFIC), mixed-signal IC, application specific integrated circuit (ASIC), printed circuit board (PCB), electronic device, etc. The processors and transceivers may also be fabricated using various IC process technologies, such as complementary metal oxide semiconductor (CMOS), N-type metal oxide semiconductor (NMOS), P-type metal oxide semiconductor (PMOS), bipolar junction transistor (BJT), BiCMOS, silicon germanium (SiGe), gallium arsenide (GaAs), etc.

[0139] The communication device described in the above embodiments may be a network device or a terminal device, but the scope of the communication device described in this application is not limited thereto, and the structure of the communication device may not be limited by Figure 11 . The communication device may be an independent device or may be part of a larger device. For example, the communication device may be:

[0140] (1) An independent integrated circuit (IC), or chip, or chip system or subsystem;

[0141] (2) A collection of one or more ICs. Optionally, the IC collection may also include storage components for storing data and computer programs;

[0142] (3) An ASIC, such as a modem;

[0143] (4) A module that can be embedded in other devices;

[0144] (5) A receiver, terminal device, smart terminal device, cellular phone, wireless device, handset, mobile unit, vehicle-mounted device, network device, cloud device, artificial intelligence device, etc.;

[0145] (6) Others, etc.

[0146] For the case where the communication device can be a chip or a chip system, reference can be made to Figure 12 the schematic structural diagram of the chip shown.

[0147] An embodiment of the present disclosure also provides a chip, such as Figure 12 the chip shown includes at least one processor 1201 and a communication interface 1202. Among them, the communication interface 1202 is used to receive signals input to the chip or signals output from the chip, and the processor 1201 communicates with the communication interface 1202 and implements the method described in the above embodiments of the present disclosure through logic circuits or by executing code instructions.

[0148] Optionally, the chip further includes a memory 1203, and the memory 1203 is used to store necessary computer programs and data.

[0149] An embodiment of the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause a computer to execute the method described in the above embodiments of the present disclosure.

[0150] Those skilled in the art can also understand that the various illustrative logical blocks and steps listed in the embodiments of the present application can be implemented by electronic hardware, computer software, or a combination of both. Whether such a function is implemented by hardware or software depends on the specific application and the design requirements of the entire system. Those skilled in the art can use various methods to implement the functions for each specific application, but such implementation should not be construed as exceeding the scope protected by the embodiments of the present application.

[0151] It should be noted that the terms "first", "second", etc. in the specification, claims, and drawings of the present disclosure are used to distinguish similar objects and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of the present disclosure described herein can be implemented in an order different from those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0152] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0153] Any process or method description shown in a flowchart or otherwise described herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations, where functions may be executed in a manner that is not shown or discussed, including in a substantially simultaneous manner according to the functions involved or in a reverse order, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0154] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing a logical function, and can be embodied specifically in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processing module, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection portion having one or more wirings (control method), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0155] It should be understood that each part of the embodiments of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logic functions on data signals, application specific integrated circuits with appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0156] Those of ordinary skill in the art can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0157] In addition, in each embodiment of the present invention, each functional unit can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage media mentioned above can be read-only memories, magnetic disks or optical discs, etc.

[0158] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for determining calibration parameters, characterized in that, The method includes: Based on a preset bandwidth signal, determining a first output signal and a first matrix, where the first matrix is the inverse matrix of the autocorrelation matrix of a basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; Based on the preset bandwidth signal, the first output signal, and the first matrix, determining a first calibration parameter.

2. The method according to claim 1, characterized in that, Determining the first output signal based on the preset bandwidth signal includes: Performing frequency conversion processing on the preset bandwidth signal to determine a first signal; Performing sampling processing on the first signal to determine a first output signal.

3. The method according to claim 1, wherein The determining the first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix includes: Based on the preset bandwidth signal, the first output signal, and the basis function matrix, determining a first cross-correlation vector; Based on the first cross-correlation vector and the first matrix, determining a first calibration parameter.

4. The method according to claim 1, characterized in that, The method further includes: Based on the preset bandwidth signal and the first matrix, iterating the first calibration parameter with a preset step size; When a preset number of iterations is reached, stopping the iteration to determine a second calibration parameter.

5. The method according to claim 4, wherein The iterating the first calibration parameter with a preset step size based on the preset bandwidth signal and the first matrix includes: Based on the preset bandwidth signal and the first calibration parameter, determining a first calibration signal; Based on the first calibration signal, determining a second output signal; Based on the preset bandwidth signal, the second output signal, and the first matrix, determining the second calibration parameter.

6. The method according to claim 5, wherein The determining the second calibration parameter based on the preset bandwidth signal, the second output signal, and the first matrix includes: Based on the preset bandwidth signal, the second output signal, and the basis function matrix, determining a second cross-correlation vector; Based on the second cross-correlation vector, the first matrix, the preset step size, and the first calibration parameter, determining the second calibration parameter.

7. A calibration parameter determination device, characterized in that It includes: A first processing unit, configured to determine a first output signal and a first matrix based on a preset bandwidth signal, where the first matrix is the inverse matrix of the autocorrelation matrix of a basis function matrix, and the basis function matrix corresponds to the preset bandwidth signal; A second processing unit, configured to determine a first calibration parameter based on the preset bandwidth signal, the first output signal, and the first matrix.

8. A communication device, characterized in that, The device includes a processor and a memory. Among them, a computer program is stored in the memory, and the processor executes the computer program stored in the memory to enable the device to execute: the method described in claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to enable the computer to execute the method described in claims 1-6.

10. A chip, characterized in that, It includes at least one processor and a communication interface; the communication interface is used to receive signals input to the chip or signals output from the chip, and the processor communicates with the communication interface and implements the method described in claims 1-6 through logic circuits or by executing code instructions.

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