WO2016107201A1 - 数字预失真方法、装置和计算机存储介质 - Google Patents

数字预失真方法、装置和计算机存储介质 Download PDF

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WO2016107201A1
WO2016107201A1 PCT/CN2015/088305 CN2015088305W WO2016107201A1 WO 2016107201 A1 WO2016107201 A1 WO 2016107201A1 CN 2015088305 W CN2015088305 W CN 2015088305W WO 2016107201 A1 WO2016107201 A1 WO 2016107201A1
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orthogonal
model structure
model
digital predistortion
polynomial
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PCT/CN2015/088305
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English (en)
French (fr)
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卢燕琼
袁静
宁东方
戴征坚
潘卫明
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中兴通讯股份有限公司
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Publication of WO2016107201A1 publication Critical patent/WO2016107201A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/38—Synchronous or start-stop systems, e.g. for Baudot code
    • H04L25/40—Transmitting circuits; Receiving circuits
    • H04L25/49—Transmitting circuits; Receiving circuits using code conversion at the transmitter; using predistortion; using insertion of idle bits for obtaining a desired frequency spectrum; using three or more amplitude levels ; Baseband coding techniques specific to data transmission systems

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  • the present invention relates to the field of digital signal processing, and more particularly to digital predistortion methods, apparatus, and computer storage media.
  • Digital Pre-Distortion is an important part of the digital IF digital signal demodulation process.
  • Digital IF processing is an indispensable part of the transmitter.
  • the transmitter is widely used in Global System for Mobile Communications (GSM), Personal Handy-phone System (PHS), and code division multiple access.
  • GSM Global System for Mobile Communications
  • PHS Personal Handy-phone System
  • code division multiple access In modern wireless communication systems of various formats such as (CDMA, Code Division Multiple Access) and Wideband Code Division Multiple Access (WCDMA), both base stations and repeaters are indispensable and extremely important. of.
  • the function of digital pre-distortion is to extract the corresponding model parameters according to the characteristics of the power amplifier, and then react the model parameters to the baseband digital signal to improve the linearity of the transmitted signal after the power amplifier, effectively suppressing the third-order intermodulation spurs.
  • the purpose is to ensure high efficiency and high quality output of the transmitted signal.
  • Embodiments of the present invention are directed to a digital predistortion method, apparatus, and computer storage medium, which are intended to effectively ensure the stability of DPD iterations while ensuring the accuracy and robustness of predistortion.
  • an embodiment of the present invention provides a digital predistortion method, where the digital predistortion method includes:
  • the orthogonal model structure is selected according to the determined model parameter values and the corresponding parameter intervals.
  • the acquiring at least one orthogonal model structure of the digital signal includes:
  • At least one orthogonal model structure of the digital signal is obtained in accordance with the structure of the orthogonal polynomial.
  • the orthogonal polynomial is at least one of a modulus orthogonal polynomial, a Legendre orthogonal polynomial, a Chebyshev orthogonal polynomial, a Laguerre orthogonal polynomial, and an Hermitian orthogonal polynomial.
  • the orthogonal model structure is an R matrix and/or a table; and the model parameter value is a condition number of the R matrix, a column vector of the R matrix, an eigenvalue of the R matrix, and at least a peak value of the table.
  • the model parameter value is a condition number of the R matrix, a column vector of the R matrix, an eigenvalue of the R matrix, and at least a peak value of the table.
  • the selecting the optimal orthogonal model structure according to the determined model parameter value and the corresponding parameter interval includes:
  • the orthogonal model structure corresponding to the model parameter value is selected.
  • the embodiment of the invention further provides a digital predistortion device, the digital predistortion device comprising:
  • a calculation module configured to determine a model parameter value and a corresponding parameter interval according to at least one orthogonal model structure acquired by the generating module
  • the selection module is configured to select an orthogonal model structure according to the model parameter value determined by the calculation module and the corresponding parameter interval.
  • the generating module is configured to acquire at least one orthogonal model structure of the digital signal according to the structure of the orthogonal polynomial.
  • the orthogonal polynomial is at least one of a modulus orthogonal polynomial, a Legendre orthogonal polynomial, a Chebyshev orthogonal polynomial, a Laguerre orthogonal polynomial, and an Hermitian orthogonal polynomial.
  • the orthogonal model structure is an R matrix and/or a table; and the model parameter value is a condition number of the R matrix, a column vector of the R matrix, an eigenvalue of the R matrix, and at least a peak value of the table.
  • the model parameter value is a condition number of the R matrix, a column vector of the R matrix, an eigenvalue of the R matrix, and at least a peak value of the table.
  • the selecting module is configured to select, if the calculated model parameter value satisfies a preset optimal condition and a parameter interval corresponding to the orthogonal model structure is within a preset parameter interval threshold range, The model parameter value corresponds to an orthogonal model structure.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the digital predistortion method according to the embodiment of the invention.
  • the digital predistortion method, device and computer storage medium provided by the embodiments of the present invention obtain at least one orthogonal model structure of a digital signal; and determine model parameter values and corresponding parameter intervals according to the acquired at least one orthogonal model structure According to the determined model parameter value and the corresponding parameter interval, the orthogonal model structure is selected.
  • the embodiment of the invention effectively guarantees the stability of the DPD iteration and ensures the accuracy and robustness of the pre-distortion.
  • FIG. 1 is a schematic flow chart of a first embodiment of a digital predistortion method according to the present invention
  • FIG. 2 is a schematic flow chart of a second embodiment of a digital predistortion method according to the present invention.
  • FIG. 3 is a schematic flow chart of a third embodiment of a digital predistortion method according to the present invention.
  • FIG. 4 is a schematic diagram of functional modules of an embodiment of a digital predistortion apparatus according to the present invention.
  • FIG. 5 is a schematic diagram of an application scenario of a digital predistortion system according to an embodiment of the present invention.
  • FIG. 1 is a schematic flowchart of a first embodiment of a digital predistortion method according to the present invention.
  • the digital predistortion method includes the following steps:
  • the digital predistortion method is applied to a digital predistortion device.
  • the digital predistortion device constructs various models of the input digital signal according to the structure of the orthogonal polynomial to generate various orthogonal model structures, and the orthogonal model structure may be an R matrix or a lookup table (LUT).
  • the orthogonal polynomials are modulo orthogonal polynomials, Legendre orthogonal polynomials, Chebyshev orthogonal polynomials, Laguerre orthogonal polynomials, Hermitian orthogonal polynomials At least one orthogonal polynomial.
  • the digital predistortion device calculates a model parameter value according to the generated at least one orthogonal model structure. For example, the digital predistortion device calculates a corresponding matrix condition number according to the generated R matrix, and estimates between the arbitrary two columns of the matrix. Correlation, calculate the eigenvalue corresponding to the matrix R, And estimating the density of the distribution of the feature values.
  • the digital predistortion device can also calculate the peak parameter of the table based on the generated LUT table.
  • the digital predistortion device calculates a corresponding parameter interval according to at least one orthogonal model structure, for example, a parameter interval corresponding to each of the R matrix and the LUT table.
  • S300 Select an orthogonal model structure according to the determined model parameter value and the corresponding parameter interval.
  • the digital predistortion device selects the best R matrix or LUT according to the corresponding matrix condition number of the R matrix, the correlation and eigenvalue between any two columns of the matrix, the density of the eigenvalue distribution, and the peak parameter of the table. Table to find the DPD iterative model structure under optimal robustness.
  • the matrix R is constructed by the orthogonal model structure and the forward feedback two-way digital signals, and the corresponding coefficients are calculated, and the required tables are obtained by fitting the coefficients. Complete the entire digital pre-distortion process.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the digital predistortion method according to the embodiment of the invention.
  • the digital predistortion method provided by the embodiment effectively ensures the stability of the DPD iteration and ensures the accuracy and robustness of the predistortion.
  • FIG. 2 is a schematic flowchart of a second embodiment of a digital pre-distortion method according to the present invention.
  • the step S100 includes:
  • Step S100A Acquire at least one orthogonal model structure of the digital signal according to the structure of the orthogonal polynomial.
  • the orthogonal model structure of the digital predistortion device is generated according to the structure of an orthogonal polynomial, which may be a modulus orthogonal polynomial, a Legendre orthogonal polynomial, a Chebyshev orthogonal polynomial, Laguerre positive At least one of a polynomial and an Hermitian orthogonal polynomial.
  • the orthogonal polynomial is a general term for an orthogonal function system composed of polynomials. among them,
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the modulus orthogonal polynomial, and the recursive formula used includes but is not limited to the following formula:
  • l is a recursive sequence of natural numbers
  • k is a natural number of functions
  • x is a forward digital signal
  • the entire formula represents a recursive relationship of functions for the three variables l, k, and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the Legendre orthogonal polynomial, and the recursive formula used includes but is not limited to the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to a Chebyshev orthogonal polynomial structure, and the recursive formula used includes, but is not limited to, the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the Laguerre orthogonal polynomial, and the recursive formula used includes, but is not limited to, the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to an Hermitian orthogonal polynomial structure, and the recursive formula used includes but is not limited to the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the digital predistortion method according to the embodiment of the invention.
  • FIG. 3 is a schematic flowchart of a third embodiment of a digital pre-distortion method according to the present invention.
  • the step S300 includes:
  • Step S300A If the calculated model parameter value satisfies the preset optimal condition and the parameter interval corresponding to the orthogonal model structure is within a preset parameter interval threshold range, then the orthogonal model corresponding to the model parameter value is selected. structure.
  • each orthogonal model structure has its own applicable range, and each model parameter value is calculated according to the collected digital signal, wherein the model parameter value satisfies the preset optimal condition by the final predistortion improvement effect. And the stability of the iteration is determined.
  • the satisfying the preset optimal condition includes: determining that the preset optimal condition is met when the obtained DPD iteration has the highest degree of stability and the model parameter value is the smallest. For example, when the model parameter value is a matrix condition number, if the obtained digital predistortion iterative stability is the best, the matrix condition number minimum model parameter value is selected as the model parameter value satisfying the preset optimal condition.
  • the digital predistortion device detects the parameter interval of the R matrix or the LUT table, and if the calculated model parameter value is optimal and the parameter interval corresponding to the orthogonal model structure is within a preset parameter interval threshold range
  • the orthogonal model structure is the optimal orthogonal model structure.
  • the preset parameter interval threshold range may be changed in real time according to actual requirements, so that the parameter interval threshold range is within the optimal parameter interval range.
  • the preset parameter interval threshold range of the LUT table is preset to 20 to 50, and the parameter interval threshold range can be modified to 30 to 40 according to actual needs.
  • the predistortion structure is constructed according to various orthogonal model polynomials through the parameter segments corresponding to the optimal orthogonal model, and the parameter intervals corresponding to the optimal model are mapped by performance indicators. It effectively guarantees the stability of the DPD iteration while ensuring the accuracy and robustness of the predistortion.
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the digital predistortion method according to the embodiment of the invention.
  • FIG. 4 is a schematic diagram of a functional module of an embodiment of a digital predistortion apparatus according to the present invention.
  • the digital predistortion apparatus provided in this embodiment includes:
  • the generating module 10 is configured to acquire at least one orthogonal model structure of the digital signal
  • the calculating module 20 is configured to determine a model parameter value and a corresponding parameter interval according to the at least one orthogonal model structure acquired by the generating module 10;
  • the selection module 30 is configured to select an orthogonal model structure according to the model parameter value determined by the calculation module 20 and the corresponding parameter interval.
  • the generating module 10 of the digital predistortion device constructs various models of the input digital signals according to the structure of the orthogonal polynomial to generate various orthogonal model structures, and the orthogonal model structure may be R.
  • the matrix may also be a LUT table, and the orthogonal model structure may be generated according to the structure of the orthogonal polynomial, or may be generated by other methods, the orthogonal polynomial is a modulus orthogonal polynomial, Legendre orthogonal polynomial, and cut At least one orthogonal polynomial of the Bechev orthogonal polynomial, the Laguerre orthogonal polynomial, and the Hermite orthogonal polynomial.
  • the calculation module 20 of the digital predistortion device calculates a model parameter value according to the generated at least one orthogonal model structure. For example, the digital predistortion device calculates a corresponding matrix condition number according to the generated R matrix, and estimates the matrix arbitrary. The correlation between the two columns, the eigenvalues corresponding to the matrix R are calculated, and the density of the eigenvalue distribution is estimated. The digital predistortion device can also calculate the peak parameter of the table based on the generated LUT table. Digital predistortion device based The various orthogonal model structures calculate corresponding parameter intervals, such as the corresponding parameter intervals of the R matrix and the LUT table.
  • the selection module 30 of the digital predistortion device selects the best according to the corresponding matrix condition number of the R matrix, the correlation and eigenvalue between any two columns of the matrix, the density of the eigenvalue distribution, and the peak parameter of the table.
  • R matrix or LUT table to find the DPD iterative model structure with the best robustness.
  • the digital predistortion device provided in this embodiment effectively ensures the stability of the DPD iteration and ensures the accuracy and robustness of the predistortion.
  • the digital predistortion apparatus provided in this embodiment, as an implementation manner, the generating module 10 is configured to acquire at least one orthogonal model structure of the digital signal according to the structure of the orthogonal polynomial.
  • the orthogonal model structure of the generating module 10 of the digital predistortion device is generated according to the structure of an orthogonal polynomial, which may be a modulus orthogonal polynomial, a Legendre orthogonal polynomial, a Chebyshev orthogonal polynomial, At least one of a Laguer orthogonal polynomial and an Hermitian orthogonal polynomial.
  • the orthogonal polynomial is a general term for an orthogonal function system composed of polynomials. among them,
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the modulus orthogonal polynomial, and the recursive formula used includes, but is not limited to, the following formula:
  • l is a recursive sequence of natural numbers
  • k is a natural number of functions
  • x is a forward digital signal
  • the entire formula represents a recursive relationship of functions for the three variables l, k, and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the Legendre orthogonal polynomial, and the recursive formula used includes but is not limited to the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to a Chebyshev orthogonal polynomial structure, and the recursive formula used includes, but is not limited to, the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to the structure of the Laguerre orthogonal polynomial, and the recursive formula used includes, but is not limited to, the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the digital predistortion apparatus of the present embodiment generates the input digital signal according to an Hermitian orthogonal polynomial structure, and the recursive formula used includes but is not limited to the following formula:
  • n denotes a natural number recursive sequence
  • x denotes a forward digital signal
  • the entire formula represents a function recursive relationship with respect to two variables of n and x.
  • the selection module 30 is configured to: if the calculated model parameter value satisfies a preset optimal condition and the orthogonal model structure When the parameter interval is within the preset parameter interval threshold range, the orthogonal model structure corresponding to the model parameter value is selected.
  • each orthogonal model structure has its own applicable range, and each model parameter value is calculated according to the collected digital signal, wherein the model parameter value satisfies the preset optimal condition by the final predistortion improvement effect. And the stability of the iteration is determined.
  • the satisfying the preset optimal condition includes: determining that the preset optimal condition is met when the obtained DPD iteration has the highest degree of stability and the model parameter value is the smallest. For example, when the model parameter value is a matrix condition number, if the obtained digital predistortion iterative stability is the best, then select The matrix condition number minimum model parameter value is used as a model parameter value that satisfies a preset optimal condition.
  • the selection module 30 of the digital predistortion device detects the parameter interval of the R matrix or the LUT table, and if the calculated model parameter value satisfies the preset optimal condition and the parameter corresponding to the orthogonal model structure When the interval is within the preset parameter interval threshold range, then the orthogonal model structure is the optimal orthogonal model structure.
  • the preset parameter interval threshold range may be changed in real time according to actual requirements, so that the preset parameter interval threshold range is within the optimal parameter interval range.
  • the preset parameter interval threshold range of the LUT table is preset to 20 to 50, and the parameter interval threshold range can be modified to 30 to 40 according to actual needs.
  • the digital predistortion device constructs a predistortion structure according to various orthogonal model polynomials through various parameter intervals corresponding to the optimal orthogonal model, and maps the parameter intervals corresponding to the optimal model through performance indicators. It effectively guarantees the stability of the DPD iteration while ensuring the accuracy and robustness of the predistortion.
  • the generating module 10, the calculating module 20, and the selecting module 30 may be implemented by a central processing unit (CPU, Central Processing Unit) in the digital predistortion apparatus. ), digital signal processor (DSP, Digital Signal Processor) or programmable gate array (FPGA, Field-Programmable Gate Array) implementation.
  • CPU Central Processing Unit
  • DSP Digital Signal Processor
  • FPGA Field-Programmable Gate Array
  • FIG. 5 is a schematic diagram of an application scenario of a digital predistortion system according to an embodiment of the present invention.
  • the digital predistortion system further includes a baseband digital signal module 11 and a shaping filtering and interpolation module 12 on the basis of the digital predistortion device.
  • a peak clipping module 13 a digital predistortion device, a modulation module 14, a digital to analog converter (DAC) module 15, a power amplification (PA) module 16 and an antenna module 17, the baseband digital signal
  • the module 11, the shaping filter and interpolation module 12, the peak clipping module 13, the digital predistortion device, the modulation module 14, the DAC module 15, the PA module 16, and the antenna module 17 are connected in series, wherein
  • the baseband digital signal module 11 is configured to generate a baseband digital signal
  • the shaping filtering and interpolation module 12 is configured to perform pulse rate shaping on the baseband digital signal and perform variable rate processing on the digital signal;
  • the peak clipping module 13 is configured to perform a reduced peak-to-average ratio processing on the intermediate frequency digital signal
  • the modulation module 14 is configured to perform encryption processing on the digital pre-distorted digital signal
  • the DAC module 15 is configured to perform digital-to-analog conversion processing on the digital signal to convert the digital signal into an analog signal;
  • the PA module 16 is configured to amplify an analog signal
  • the antenna feeder module 17 is configured to transmit an amplified analog signal into the air.
  • the digital predistortion system provided in this embodiment, after the digital signal is cut by the baseband digital signal module, the shaping filtering and interpolation module, and the peak clipping module, is input to the digital predistortion device for digital predistortion processing, and is subjected to the modulation module.
  • Encryption, digital-to-analog conversion of the DAC module, and the transmission of the PA module and the antenna module provide a stable guarantee for the stable high-quality output of the transmitted signal, ensuring good linearity of the transmitted signal after the power amplifier.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention can take the form of a hardware embodiment, a software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) including computer usable program code.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • the embodiment of the present invention obtains at least one orthogonal model structure of the digital signal; determines the model parameter value and the corresponding parameter interval according to the acquired at least one orthogonal model structure; according to the determined model parameter value and the corresponding parameter interval, Select the orthogonal model structure.
  • the embodiment of the invention effectively guarantees the stability of the DPD iteration and ensures the accuracy and robustness of the pre-distortion.

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Abstract

本发明实施例公开了一种数字预失真方法，通过获取数字信号的至少一种正交模型结构；根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；根据确定的模型参量数值和对应的参量区间，选择正交模型结构。本发明实施例还公开了一种数字预失真装置和计算机存储介质。

Description

数字预失真方法、装置和计算机存储介质 技术领域
本发明涉及数字信号处理领域，尤其涉及数字预失真方法、装置和计算机存储介质。
背景技术
数字预失真技术(DPD，Digital Pre-Distortion)是数字中频数字信号解调处理中很重要的一部分。数字中频处理是发射机中不可缺少的一环，发射机广泛应用于全球移动通信系统(GSM，Global System for Mobile Communications)、个人手持电话系统(PHS，Personal Handy-phone System)、码分多址(CDMA，Code Division Multiple Access)和宽带码分多址(WCDMA，Wideband Code Division Multiple Access)等各种制式的现代无线通信系统中，无论是基站还是直放站，都是不可或缺且极其重要的。而数字预失真的作用是根据功率放大器的特性提取相应的模型参量，然后把模型参量反作用在基带数字信号上，达到改善功率放大器后发射信号线性度的目的，有效地抑制三阶互调杂散的目的，保证了发射信号的高效率高质量输出。
在数字预失真处理过程中，为了提高数字域上模型参量拟合的精度，尝试采用各种数学模型来提升，在参量精度高的模型中，不能有效保证DPD迭代的稳定性，这样必然会导致在实际应用中，互调指标有波动的可能，对发射信号的稳定高质量输出造成了不可持续的隐患。另外，在现有技术上，数字预失真采用经典模型来拟合，这样来做不能同时保证精度和鲁棒性，而且，对现在超宽带功放特性的模型更难把握。因此，亟待采用一种技术来提高数字预失真的鲁棒性，以确保功率放大器后发射信号的良好线 性度。
发明内容
本发明实施例期望提供一种数字预失真方法、装置和计算机存储介质，旨在有效保证DPD迭代的稳定性以及同时保证预失真的精度和鲁棒性。
为实现上述目的，本发明实施例提供一种数字预失真方法，所述数字预失真方法包括：
获取数字信号的至少一种正交模型结构；
根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；
根据确定的模型参量数值和对应的参量区间，选择正交模型结构。
作为一种实施方式，所述获取数字信号的至少一种正交模型结构包括：
按照正交多项式的结构获取数字信号的至少一种正交模型结构。
作为一种实施方式，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
作为一种实施方式，所述正交模型结构为R矩阵和/或表格；所述模型参量数值为R矩阵的条件数、R矩阵的列向量、R矩阵的特征值、表格的峰值中的至少一种参量数值。
作为一种实施方式，所述根据确定的模型参量数值和对应的参量区间，选择最佳的正交模型结构包括：
若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
本发明实施例还提供一种数字预失真装置，所述数字预失真装置包括：
生成模块，配置为获取数字信号的至少一种正交模型结构；
计算模块，配置为根据所述生成模块获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；
选择模块，配置为根据所述计算模块确定的模型参量数值和对应的参量区间，选择正交模型结构。
作为一种实施方式，所述生成模块，配置为按照正交多项式的结构获取数字信号的至少一种正交模型结构。
作为一种实施方式，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
作为一种实施方式，所述正交模型结构为R矩阵和/或表格；所述模型参量数值为R矩阵的条件数、R矩阵的列向量、R矩阵的特征值、表格的峰值中的至少一种参量数值。
作为一种实施方式，所述选择模块，配置为若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行本发明实施例所述的数字预失真方法。
本发明实施例提供的数字预失真方法、装置和计算机存储介质，通过获取数字信号的至少一种正交模型结构；根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；根据确定的模型参量数值和对应的参量区间，选择正交模型结构。本发明实施例有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。
附图说明
图1为本发明数字预失真方法第一实施例的流程示意图；
图2为本发明数字预失真方法第二实施例的流程示意图；
图3为本发明数字预失真方法第三实施例的流程示意图；
图4为本发明数字预失真装置一实施例的功能模块示意图；
图5为本发明实施例的数字预失真系统应用场景示意图。
本发明实施例目的的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
本发明实施例提供一种数字预失真方法，参照图1，图1为本发明数字预失真方法第一实施例的流程示意图，在第一实施例中，所述数字预失真方法包括以下步骤：
S100、获取数字信号的至少一种正交模型结构。
这里，所述数字预失真方法应用于数字预失真装置中。所述数字预失真装置按照正交多项式的结构对输入的数字信号进行各种模型的构架，生成各种正交模型结构，所述正交模型结构可以是R矩阵，也可以是查找表(LUT，Look-up table)表格，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
S200、根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间。
这里，数字预失真装置根据生成的至少一种正交模型结构，计算出模型参量数值，例如数字预失真装置根据生成的R矩阵，计算出相应的矩阵条件数、估计出矩阵任意两列之间的相关性、计算出矩阵R对应的特征值、 以及估计出特征值分布的疏密性。所述数字预失真装置也可以根据生成的LUT表格，计算出表格的峰值参量。所述数字预失真装置根据至少一种正交模型结构计算出对应的参量区间，例如R矩阵和LUT表格各自对应的参量区间。
S300、根据确定的模型参量数值和对应的参量区间，选择正交模型结构。
这里，数字预失真装置根据R矩阵的相应的矩阵条件数、矩阵任意两列之间的相关性和特征值、特征值分布的疏密性和表格的峰值参量，选择最佳的R矩阵或LUT表格，从而找出最佳鲁棒性下的DPD迭代模型结构。
进一步地，选择出正交模型结构后，由所述正交模型结构和前向反馈两路数字信号来构造矩阵R，计算获得对应的系数，由所述系数进行拟合获得所需要的表格，完成整个数字预失真的过程。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行本发明实施例所述的数字预失真方法。
本实施例提供的数字预失真方法有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。
如图2所示，图2为本发明数字预失真方法第二实施例的流程示意图，在第一实施例的基础上，所述步骤S100包括：
步骤S100A、按照正交多项式的结构获取数字信号的至少一种正交模型结构。
这里，数字预失真装置的正交模型结构按照正交多项式的结构生成，所述正交多项式可以为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种。所述正交多项式是由多项式构成的正交函数系的通称。其中，
作为第一种实施方式，本实施例数字预失真装置对输入的数字信号按照模值正交多项式的结构生成，采用的递推公式包括但不限于下述公式：
Figure PCTCN2015088305-appb-000001
其中，l表示自然数递推序列，k表示函数自然数角标，x表示前向数字信号，整个公式表示一个关于l、k和x三个变量的函数递推的关系。
作为第二种实施方式，本实施例数字预失真装置对输入的数字信号按照勒让德正交多项式的结构生成，采用的递推公式包括但不限于下述公式：
(n+1)Pn+1(x)＝(2n+1)xPn(x)-nPn-1(x)(n＝1,2,…)  (2)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第三种实施方式，本实施例数字预失真装置对输入的数字信号按照切比雪夫正交多项式结构生成，采用的递推公式包括但不限于下述公式：
Tn+1(x)＝2xTn(x)-Tn-1(x)(n＝1,2,…)  (3)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第四种实施方式，本实施例数字预失真装置对输入的数字信号按照拉盖尔正交多项式的结构生成，采用的递推公式包括但不限于下述公式：
Ln+1(x)＝(1+2n-x)Ln(x)-n2Ln-1(x)(n＝1,2,…)  (4)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第五种实施方式，本实施例数字预失真装置对输入的数字信号按照埃尔米特正交多项式结构来生成，采用的递推公式包括但不限于下述公式：
Hn+1(x)＝2xHn(x)-2nHn-1(x)(n＝1,2,…)  (5)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行本发明实施例所述的数字预失真方法。
如图3所示，图3为本发明数字预失真方法第三实施例的流程示意图，在第一实施例的基础上，所述步骤S300包括：
步骤S300A、若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
具体的，每个正交模型结构均有自身的适用范围，根据采集回来的数字信号来计算每个模型参量数值，其中，所述模型参量数值是否满足预设最优条件由最终预失真改善效果和迭代的稳定性来决定。作为一种实施方式，所述满足预设最优条件，包括：当获得的DPD迭代的稳定程度最高、且所述模型参量数值最小时，确定满足预设最优条件。比如，当所述模型参量数值为矩阵条件数时，若获得的数字预失真迭代稳定性最好，则选取所述矩阵条件数最小模型参量数值作为满足预设最优条件的模型参量数值。
本实施例中，数字预失真装置对R矩阵或LUT表格的参量区间进行检测，若计算出来的模型参量数值最佳和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则所述正交模型结构为最佳的正交模型结构。所述预设的参量区间阈值范围可以根据实际的需求实时进行更改，使参量区间阈值范围在最佳的参量区间范围之内。例如LUT表格的预设的参量区间阈值范围预设为20至50，而根据实际的需求，可将参量区间阈值范围修改为30至40。
本实施例提供的数字预失真方法，通过最佳正交模型对应的各参量区间，根据各种不同正交模型多项式构建预失真结构，通过性能指标来映射最佳模型对应的参量区间。有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。
本发明实施例还提供了一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行本发明实施例所述的数字预失真方法。
如图4所示，图4为本发明数字预失真装置一实施例的功能模块示意图，本实施例提供的数字预失真装置，包括：
生成模块10，配置为获取数字信号的至少一种正交模型结构；
计算模块20，配置为根据所述生成模块10获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；
选择模块30，配置为根据所述计算模块20确定的模型参量数值和对应的参量区间，选择正交模型结构。
本实施例中，所述数字预失真装置的生成模块10按照正交多项式的结构对输入的数字信号进行各种模型的构架，生成各种正交模型结构，所述正交模型结构可以是R矩阵，也可以是LUT表格，所述正交模型结构可以按照正交多项式的结构生成，也可以通过其他方式生成，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
所述数字预失真装置的计算模块20根据生成的至少一种正交模型结构，计算出模型参量数值，例如数字预失真装置根据生成的R矩阵，计算出相应的矩阵条件数、估计出矩阵任意两列之间的相关性、计算出矩阵R对应的特征值，以及估计出特征值分布的疏密性。所述数字预失真装置也可以根据生成的LUT表格，计算出表格的峰值参量。数字预失真装置根据 各种正交模型结构计算出对应的参量区间，例如R矩阵和LUT表格各自对应的参量区间。
所述数字预失真装置的选择模块30根据R矩阵的相应的矩阵条件数、矩阵任意两列之间的相关性和特征值、特征值分布的疏密性和表格的峰值参量，选择最佳的R矩阵或LUT表格，从而找出最佳鲁棒性下的DPD迭代模型结构。
本实施例提供的数字预失真装置，有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。
参见图4，本实施例提供的数字预失真装置，作为一种实施方式，所述生成模块10配置为按照正交多项式的结构获取数字信号的至少一种正交模型结构。
所述数字预失真装置的生成模块10的正交模型结构按照正交多项式的结构生成，所述正交多项式可以为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种。所述正交多项式是由多项式构成的正交函数系的通称。其中，
作为第一种实施方式，本实施例数字预失真装置对输入的数字信号按照模值正交多项式的结构来生成，采用的递推公式包括但不限于下述公式：
Figure PCTCN2015088305-appb-000002
其中，l表示自然数递推序列，k表示函数自然数角标，x表示前向数字信号，整个公式表示一个关于l、k和x三个变量的函数递推的关系。
作为第二种实施方式，本实施例数字预失真装置对输入的数字信号按照勒让德正交多项式的结构生成，采用的递推公式包括但不限于下述公式：
(n+1)Pn+1(x)＝(2n+1)xPn(x)-nPn-1(x)(n＝1,2,…)  (7)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第三种实施方式，本实施例数字预失真装置对输入的数字信号按照切比雪夫正交多项式结构生成，采用的递推公式包括但不限于下述公式：
Tn+1(x)＝2xTn(x)-Tn-1(x)(n＝1,2,…)  (8)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第四种实施方式，本实施例数字预失真装置对输入的数字信号按照拉盖尔正交多项式的结构生成，采用的递推公式包括但不限于下述公式：
Ln+1(x)＝(1+2n-x)Ln(x)-n2Ln-1(x)(n＝1,2,…)  (9)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
作为第五种实施方式，本实施例数字预失真装置对输入的数字信号按照埃尔米特正交多项式结构生成，采用的递推公式包括但不限于下述公式：
Hn+1(x)＝2xHn(x)-2nHn-1(x)(n＝1,2,…)  (10)
其中，n表示自然数递推序列，x表示前向数字信号，整个公式表示一个关于n和x两个个变量的函数递推的关系。
参见图4，本实施例提供的数字预失真装置，作为一种实施方式，所述选择模块30，配置为若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
具体的，每个正交模型结构均有自身的适用范围，根据采集回来的数字信号来计算每个模型参量数值，其中，所述模型参量数值是否满足预设最优条件由最终预失真改善效果和迭代的稳定性来决定。作为一种实施方式，所述满足预设最优条件，包括：当获得的DPD迭代的稳定程度最高、且所述模型参量数值最小时，确定满足预设最优条件。比如，当所述模型参量数值为矩阵条件数时，若获得的数字预失真迭代稳定性最好，则选取 所述矩阵条件数最小模型参量数值作为满足预设最优条件的模型参量数值。
本实施例中，所述数字预失真装置的选择模块30对R矩阵或LUT表格的参量区间进行检测，若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则所述正交模型结构为最佳的正交模型结构。所述预设的参量区间阈值范围可以根据实际的需求实时进行更改，使预设的参量区间阈值范围在最佳的参量区间范围之内。例如LUT表格的预设的参量区间阈值范围预设为20至50，而根据实际的需求，可将参量区间阈值范围修改为30至40。
本实施例提供的数字预失真装置，通过最佳正交模型对应的各参量区间，根据各种不同正交模型多项式构建预失真结构，通过性能指标来映射最佳模型对应的参量区间。有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。
本实施例所述的数字预失真装置中，所述生成模块10、计算模块20和所述选择模块30在实际应用中，可由所述数字预失真装置中的中央处理器(CPU，Central Processing Unit)、数字信号处理器(DSP，Digital Signal Processor)或可编程门阵列(FPGA，Field－Programmable Gate Array)实现。
如图5所示，图5为本发明实施例的数字预失真系统应用场景示意图，所述数字预失真系统在数字预失真装置的基础上还包括基带数字信号模块11、成型滤波和插值模块12、削峰模块13、数字预失真装置、调制模块14、数字模拟转换(DAC，Digital to Analog Converter)模块15、功率放大(PA，Power Amplifier)模块16和天馈模块17，所述基带数字信号模块11、成型滤波和插值模块12、削峰模块13、数字预失真装置、调制模块14、DAC模块15、PA模块16和天馈模块17按序串联，其中，
所述基带数字信号模块11，配置为产生基带数字信号；
所述成型滤波和插值模块12，配置为对基带数字信号进行脉冲成型和数字信号进行变速率处理；
所述削峰模块13，配置为对中频数字信号进行降低峰均比处理；
所述调制模块14，配置为对数字预失真后数字信号进行加密处理；
所述DAC模块15，配置为对数字信号进行数模转换处理，将数字信号转换为模拟信号；
所述PA模块16，配置为放大模拟信号；
所述天馈模块17，配置为将放大的模拟信号发射到空中。
本实施例提供的数字预失真系统，数字信号通过基带数字信号模块、成型滤波和插值模块、削峰模块的削峰后，输入到数字预失真装置进行数字预失真处理后，并经过调制模块的加密、DAC模块的数模转换、PA模块的广大和天馈模块的发射，对发射信号的稳定高质量输出作了有效保证，确保了功率放大器后发射信号的良好线性度。
本领域内的技术人员应明白，本发明的实施例可提供为方法、系统、或计算机程序产品。因此，本发明可采用硬件实施例、软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本发明是参照根据本发明实施例的方法、设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现 在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
以上所述，仅为本发明的较佳实施例而已，并非用于限定本发明的保护范围。
工业实用性
本发明实施例通过获取数字信号的至少一种正交模型结构；根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；根据确定的模型参量数值和对应的参量区间，选择正交模型结构。本发明实施例有效保证了DPD迭代的稳定性、同时保证了预失真的精度和鲁棒性。

Claims (11)

  1. 一种数字预失真方法，所述数字预失真方法包括：
    获取数字信号的至少一种正交模型结构；
    根据获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；
    根据确定的模型参量数值和对应的参量区间，选择正交模型结构。
  2. 如权利要求1所述的数字预失真方法，其中，所述获取数字信号的至少一种正交模型结构，包括：
    按照正交多项式的结构获取数字信号的至少一种正交模型结构。
  3. 如权利要求2所述的数字预失真方法，其中，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
  4. 如权利要求1所述的数字预失真方法，其中，所述正交模型结构为R矩阵和/或表格；所述模型参量数值为R矩阵的条件数、R矩阵的列向量、R矩阵的特征值、表格的峰值中的至少一种参量数值。
  5. 如权利要求1至4任一项所述的数字预失真方法，其中，所述根据确定的模型参量数值和对应的参量区间，选择正交模型结构包括：
    若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
  6. 一种数字预失真装置，所述数字预失真装置包括：
    生成模块，配置为获取数字信号的至少一种正交模型结构；
    计算模块，配置为根据所述生成模块获取的至少一种正交模型结构，确定模型参量数值和对应的参量区间；
    选择模块，配置为根据所述计算模块确定的模型参量数值和对应的参 量区间，选择正交模型结构。
  7. 如权利要求6所述的数字预失真装置，其中，所述生成模块，配置为按照正交多项式的结构获取数字信号的至少一种正交模型结构。
  8. 如权利要求7所述的数字预失真装置，其中，所述正交多项式为模值正交多项式、勒让德正交多项式、切比雪夫正交多项式、拉盖尔正交多项式、埃尔米特正交多项式中的至少一种正交多项式。
  9. 如权利要求6所述的数字预失真装置，其中，所述正交模型结构为R矩阵和/或表格；所述模型参量数值为R矩阵的条件数、R矩阵的列向量、R矩阵的特征值、表格的峰值中的至少一种参量数值。
  10. 如权利要求6至9任一项所述的数字预失真装置，其中，所述选择模块，配置为若计算出来的模型参量数值满足预设最优条件和所述正交模型结构对应的参量区间在预设的参量区间阈值范围内时，则选择所述模型参量数值对应的正交模型结构。
  11. 一种计算机存储介质，所述计算机存储介质中存储有计算机可执行指令，所述计算机可执行指令用于执行权利要求1至5任一项所述的数字预失真方法。
PCT/CN2015/088305 2014-12-29 2015-08-27 数字预失真方法、装置和计算机存储介质 WO2016107201A1 (zh)

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