WO2012174842A1 - Appareil et procédé de correction de distorsion pour système non linéaire - Google Patents

Appareil et procédé de correction de distorsion pour système non linéaire Download PDF

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Publication number
WO2012174842A1
WO2012174842A1 PCT/CN2011/084583 CN2011084583W WO2012174842A1 WO 2012174842 A1 WO2012174842 A1 WO 2012174842A1 CN 2011084583 W CN2011084583 W CN 2011084583W WO 2012174842 A1 WO2012174842 A1 WO 2012174842A1
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Prior art keywords
signal
correction
link data
parameter identification
main link
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PCT/CN2011/084583
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English (en)
Chinese (zh)
Inventor
宁东方
韦兆碧
张烈
游爱民
向际鹰
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中兴通讯股份有限公司
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Publication of WO2012174842A1 publication Critical patent/WO2012174842A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/36—Modulator circuits; Transmitter circuits
    • H04L27/366—Arrangements for compensating undesirable properties of the transmission path between the modulator and the demodulator
    • H04L27/367—Arrangements for compensating undesirable properties of the transmission path between the modulator and the demodulator using predistortion
    • H04L27/368—Arrangements for compensating undesirable properties of the transmission path between the modulator and the demodulator using predistortion adaptive predistortion

Definitions

  • the present invention relates to the field of communications, and in particular to a nonlinear system distortion correcting apparatus and method.
  • BACKGROUND With the development of mobile communication, spectrum resources are increasingly scarce. In order to improve spectrum utilization efficiency, high-efficiency modulation methods are often used. However, these modulation methods generate intermodulation interference when the power amplifier operates close to the saturation region. This causes the power amplifier to produce severe nonlinear distortion.
  • One way to solve the problem of nonlinear distortion in power amplifiers is to use power back-off techniques, which in turn leads to low efficiency and high power consumption of the power amplifier. Therefore, the trade-off between frequency utilization and power amplifier efficiency requires some processing technology to correct the nonlinear distortion of the power amplifier.
  • Digital pre-distortion technology is the primary choice for current nonlinear system distortion correction because of its low cost and good performance. .
  • the characteristics of the power amplifier change with the ambient temperature and the aging of the device. Therefore, in order to improve the improvement effect of the nonlinear distortion of the power amplifier, the correction parameters need to be adaptive.
  • the existing digital predistortion processing methods usually adopt an indirect learning structure to adapt the correction parameters. For example, an inverse model (ie, a correction parameter) is established to make the output of the power amplifier approach the input of the power amplifier through the response of the model. Because of the method in the process of establishing the inverse model, the noise distribution in the signal causes the model parameters to finally converge to one. There is a bias value.
  • the present invention provides a nonlinear system distortion correcting apparatus and method to solve the above problems.
  • a non-linear system distortion correction apparatus including: an adaptor module, a pre-corrector module, wherein the adaptor module includes: a data acquisition unit configured to collect main link data and Feedback link data; a signal processing unit configured to perform pre-processing on the collected main link data and feedback link data; and a correction parameter identification unit configured to perform pre-processed main link data and feedback link data Parameter identification, obtaining correction parameters of the nonlinear system;
  • the pre-corrector module is configured to perform pre-correction processing on the main link data according to the correction parameters.
  • the correction parameter identification unit comprises: a matrix construction subunit, configured to construct a parameter identification matrix and a target matrix according to the distortion correction model, the pre-corrected signal, and the preprocessed main link data and the feedback link data; the pseudo inverse calculation subunit , the pseudo-inverse matrix is set to calculate the parameter identification matrix; the parameter identification sub-unit is set to perform parameter identification according to the target matrix, the pseudo-inverse matrix of the parameter identification matrix and a predetermined parameter identification algorithm, and the correction parameters of the nonlinear system are obtained.
  • the above distortion correction model includes one of the following: a general memory polynomial model, a Wiener model, a Hammerstein model, a Volterra model, a neural network, a wavelet network; and/or an algorithm for calculating a pseudo-inverse matrix of a parameter identification matrix and a target matrix, including one of the following : singular value decomposition, QR decomposition, Cholesky decomposition; and/or, the predetermined parameter identification algorithm includes one of the following: a least squares algorithm, a recursive least squares algorithm, and a least mean square algorithm.
  • the pre-corrector module includes: an address indexing unit configured to perform linear or non-linear mapping on the amplitude or power of the main link signal to generate index address information; and a correction signal generating unit configured to search for the index address information in the correction parameter
  • the content of the distortion correction signal is generated; the pre-correction processing unit is configured to perform pre-correction processing on the main link signal according to the distortion correction signal.
  • the address indexing unit performs linear or non-linear mapping on the amplitude or power of the main link signal, and the mapping algorithm for generating the index address information may include: Or f a ( x ), where a is the address information of the correction signal, and
  • 2 are the modulus and power of the signal, /. ( ⁇ ) is a mapping function, or is or; the algorithm for pre-correction processing of the main link signal by the pre-correction processing unit according to the distortion correction signal may include: y(n) F ux (U, X) ,
  • X [x(n), x(n _ 1), ... , x(n - J)] , where is the distortion correction signal vector found according to the index address information, the main link signal vector, f To correct the maximum delay of the signal, J is the maximum delay of the main link signal, "for the signal sampling time serial number, _y is the pre-corrected signal; ⁇ ( ⁇ ) is the pre-correction function.
  • a nonlinear system distortion correction method including: collecting primary link data and feedback link data; and performing pre-processing on the collected primary link data and feedback link data;
  • the pre-processed main link data and the feedback link data are subjected to parameter identification, and the correction parameters of the nonlinear system are obtained; and the main link data is pre-corrected according to the correction parameters.
  • the parameter identification is performed according to the preprocessed main link data and the feedback link data, and the correction parameters of the nonlinear system are obtained: according to the distortion correction model, the pre-corrected signal, and the preprocessed main link data and the feedback link.
  • the data constructs the parameter identification matrix and the target matrix; calculates the pseudo-inverse matrix of the parameter identification matrix; performs parameter identification according to the target matrix, the pseudo-inverse matrix of the parameter identification matrix and the predetermined parameter identification algorithm, and obtains the correction parameters of the nonlinear system.
  • the above distortion correction model includes one of the following: a general memory polynomial model, a Wiener model, a Hammerstein model, a Volterra model, a neural network, a wavelet network; and/or an algorithm for calculating a pseudo-inverse matrix of a parameter identification matrix and a target matrix, including one of the following : singular value decomposition, QR decomposition, Cholesky decomposition; and/or, the predetermined parameter identification algorithm includes one of the following: a least squares algorithm, a recursive least squares algorithm, and a least mean square algorithm.
  • Performing pre-correction processing on the main link data according to the correction parameter includes: linearly or non-linearly mapping the amplitude or power of the main link signal to generate index address information; searching for the content corresponding to the index address information in the correction parameter, Generating a distortion correction signal; pre-correcting the main link signal according to the distortion correction signal.
  • the linear or non-linear mapping of the amplitude or power of the primary link signal, the mapping algorithm for generating the index address information may include: Or f a ( x ), where a is the address information of the correction signal, and
  • the distortion correction signal vector obtained by searching according to the index address information is the main link signal vector
  • f the maximum delay of the correction signal
  • J the maximum delay of the main link signal
  • _y is the pre-corrected signal
  • ⁇ ( ⁇ ) is the pre-correction function.
  • FIG. 1 is a block diagram showing a configuration of a nonlinear system distortion correcting apparatus according to an embodiment of the present invention
  • FIG. 2 is a block diagram showing a configuration of a nonlinear system distortion correcting apparatus according to a first preferred embodiment of the present invention
  • FIG. 4 is a schematic structural diagram of a nonlinear system distortion correction apparatus according to a second preferred embodiment of the present invention
  • FIG. 4 is a schematic structural diagram of a nonlinear system distortion correction apparatus according to an example of the present invention
  • 6 is a basic structural diagram of a pre-corrector according to an example of the present invention
  • FIG. 7 is a basic structural diagram of an adaptor according to an example of the present invention
  • FIG. 8 is a detailed structural diagram of a power amplifier pre-correcting apparatus according to an example 1 of the present invention
  • 9 is a detailed structural diagram of a power amplifier pre-correcting apparatus according to Example 2 of the present invention
  • FIG. 10 is a flowchart of a nonlinear system distortion correcting method according to an embodiment of the present invention
  • FIG. 10 is a flowchart of a nonlinear system distortion correcting method according to an embodiment of the present invention
  • FIG. 11 is a nonlinear diagram according to a preferred embodiment of the present invention.
  • Flow chart of the system distortion correction method BEST MODE FOR CARRYING OUT THE INVENTION
  • FIG. 1 is a block diagram showing the structure of a nonlinear system distortion correcting apparatus according to an embodiment of the present invention. As shown in FIG.
  • the nonlinear system distortion correction apparatus includes: an adaptor module 12 and a pre-corrector module 14 , wherein the adaptor module 12 includes: a data acquisition unit 122 configured to collect the main Link data and feedback link data; signal processing unit 124, coupled to data acquisition unit 122, configured to pre-process the collected primary link data and feedback link data; calibration parameter identification unit 126, coupled to signal processing The unit 124 is configured to perform parameter identification according to the preprocessed main link data and the feedback link data to obtain a calibration parameter of the nonlinear system; the precorrector module 14 is connected to the adaptor module 12, and is set according to the calibration parameter. Pre-correction processing of the main link data.
  • the above device adopts an adaptive method based on forward iteration, and uses the main link data and the feedback link data as the data basis for calculating the correction parameters, solves the spectrum diffusion problem caused by the nonlinear distortion of the power amplifier, and improves the correction.
  • the identification accuracy of the parameters may also be referred to as an unpre-corrected signal or an input signal of the pre-corrector module 14, and the feedback link data may also be referred to as a signal passing through a nonlinear system or an output signal of a nonlinear system. .
  • the preprocessing performed by the signal processing unit 124 is the same as the preprocessing performed in the prior art to obtain the correction parameters, and may include: general processing such as frequency shifting, filtering, signal correction, etc., and parameter identification can be performed by preprocessing. Before, the basic data is sorted for subsequent processing. For the identification of the correction parameters, after the main link data is introduced by the device according to the embodiment, the parameter identification can be performed according to various manners. In this embodiment, a preferred implementation manner is provided, and FIG. 2 is based on A block diagram of a nonlinear system distortion correction apparatus according to a first preferred embodiment of the present invention, as shown in FIG.
  • the correction parameter identification unit 126 may further include: a matrix construction sub-unit 1262, configured to be based on a distortion correction model, pre-corrected Constructing a parameter identification matrix and a target matrix by using the signal and the preprocessed main link data and the feedback link data;
  • the pseudo inverse calculation subunit 1264 is connected to the matrix construction subunit 1262, and is configured to calculate a pseudo inverse matrix of the parameter identification matrix;
  • the parameter identification subunit 1266 is connected to the matrix construction subunit 1262 and the pseudo inverse calculation subunit 1264, and is set according to The target matrix, the pseudo-inverse matrix of the parameter identification matrix and the predetermined parameter identification algorithm are used for parameter identification, and the correction parameters of the nonlinear system are obtained.
  • the calibration parameter identification is divided into three steps.
  • the parameter identification matrix which is the parameter identification matrix and the target matrix.
  • the parameter identification matrix and the target matrix are the pre-processed main link signals, the pre-processed feedback signals and the pre-processing.
  • the corrected signal ie, the input signal of the nonlinear system
  • the pseudo inverse matrix of the parameter identification matrix is calculated; finally, the predetermined parameter identification algorithm is used for the target matrix and the parameter identification matrix.
  • the pseudo inverse matrix is used for parameter identification, and the correction parameters of the nonlinear system are obtained.
  • the distortion correction model may include one of the following: a general memory polynomial model, a Wiener model, a Hammerstein model, a Volterra model, a neural network, a wavelet network; a P/or, a parameter identification matrix and a pseudo-inverse matrix of the target matrix.
  • the algorithm may include one of the following: singular value decomposition, QR decomposition, Cholesky decomposition; and/or, the predetermined parameter identification algorithm may include one of the following: a least squares algorithm, a recursive least squares algorithm, a least mean square algorithm.
  • the models and algorithms that can be used include, but are not limited to, the above-mentioned models and algorithms, and can be expanded and matched according to specific needs.
  • FIG. 3 is a nonlinearity according to a second preferred embodiment of the present invention.
  • the pre-corrector module 14 may further include: an address indexing unit 142 configured to linearly or non-linearly map the amplitude or power of the main link signal to generate index address information; the correction signal generating unit 144, The connection to the address indexing unit 142 is configured to search for the content corresponding to the index address information in the above-mentioned correction parameter to generate a distortion correction signal.
  • the pre-correction processing unit 146 is connected to the correction signal generation unit 144, and is configured to be paired according to the distortion correction signal.
  • the link signal is pre-corrected. Pre-correction can also be completed in three steps. First, linear or non-linear mapping of the amplitude or power of the main link signal is performed to generate index address information.
  • the index is searched for in the correction parameter generated by the positive parameter identification unit 126.
  • the content corresponding to the address information generates a distortion correction signal.
  • the main link signal is pre-corrected according to the distortion correction signal to obtain a pre-corrected signal to cancel the nonlinear distortion generated by the subsequent nonlinear system.
  • the address indexing unit 142 performs linear or non-linear mapping on the amplitude or power of the primary link signal, and the mapping algorithm for generating the indexed address information may include: Or f a ( x ), where a is the address information of the correction signal, and
  • ( ⁇ ) is a mapping function, or is or;
  • the address indexing unit 142 linearly maps the amplitude or power of the main link signal or the nonlinear mapping as a mapping function/. The choice of ( ⁇ ), and the specific choice of the mapping function needs to be determined according to the actual situation.
  • the pre-correction processing unit 146 performs the key processing of the main link signal according to the distortion correction signal, and also the selection of the pre-correction function ⁇ 0, which needs to be determined according to the actual situation.
  • the above preferred embodiments will be described in detail below with reference to examples.
  • the nonlinear system in the figure is mainly a power amplifier.
  • the power amplifier is used to amplify the signal, and also produces the amplitude and phase of the signal.
  • Nonlinear distortion which causes signal envelope distortion in the time domain, causing spectral spread in the frequency domain, resulting in poor leakage power degradation and signal demodulation index.
  • the correction parameter is based on the input digital signal of the power amplifier and the coupled feedback digital signal, and the nonlinear correction parameter of the power amplifier is obtained by establishing an inverse model of the power amplifier.
  • the shortcoming of the above scheme is that in the process of constructing the power amplifier inverse model, the distribution characteristics of the observed noise in the feedback signal are changed, which affects the parameter identification accuracy of the power amplifier inverse model. In the case where the linear index requires high, the nonlinear distortion correction property Can not meet the requirements.
  • FIG. 5 is a block diagram showing the configuration of a nonlinear system distortion correcting apparatus according to an example of the present invention, and also showing the position of the apparatus in the communication system.
  • the entire nonlinear distortion correction device includes: a signal generator module, a pre-corrector module, a DAC module, an ADC module, a nonlinear system module, an adaptor module, and a control signal module.
  • the signal generator module, the DAC module, and the ADC module are basic functional modules that need to be added in the specific implementation process of the present example to provide original signals and perform digital-to-analog conversion;
  • the nonlinear system modules are modules that cause nonlinear distortion.
  • the signal generator module generates a primary link signal, a digital signal to be nonlinearly processed.
  • the main link signal generated by the signal generator module is pre-corrected by the pre-corrector processing of the pre-corrector module, and the pre-corrected signal is subjected to digital-to-analog conversion and processing by a nonlinear system to obtain a nonlinear system.
  • the output signal after the analog signal of the nonlinear system is subjected to analog-to-digital conversion, obtains a feedback data signal.
  • the adaptor module After pre-processing the signal of the main link signal and the feedback digital signal, the distortion model of the nonlinear system is established, and the parameter identification algorithm is used to identify the correction parameters and download to the pre-corrector to implement the correction.
  • Adaptive processing of parameters The pre-corrector module performs digital pre-correction processing on the main link signal to obtain a pre-corrected signal.
  • the pre-corrector module pre-corrects the main link signal according to the amplitude and phase information of the signal, and the correction information has the same amplitude and opposite phase as the distortion signal generated by the nonlinear system, thereby canceling the nonlinear system to the main link signal The distortion caused.
  • the pre-corrected signal is converted from the digital domain to the analog domain by the DAC module, and the nonlinear processing of the signal is realized by the nonlinear system module.
  • the output signal of the nonlinear system passes through the ADC module, and finally the feedback digital signal is obtained.
  • the adaptive module periodically completes the acquisition of the main link signal, the pre-corrected signal, and the feedback digital signal.
  • the parameter identification algorithm is used to identify the corrected parameter and download it to the pre-corrector.
  • a control signal module may be further provided to control the adaptive device module relatively independently, including controlling data acquisition, signal preprocessing flow, correction parameter identification and correction parameters in the adaptive device module.
  • FIG. 6 is a basic structural diagram of a pre-corrector module according to an example of the present invention, including an address index unit, a correction signal generating unit, and a pre-correction processing unit.
  • the address indexing unit and the correction information generating unit are mainly responsible for linearly or non-linearly mapping the amplitude or power of the input signal, generating index address information, and obtaining a correction signal corresponding to the input data based on the address information.
  • the mapping relationship that the address index unit can adopt is as follows: Where a is the address information of the correction signal, and
  • the mapping function of the present invention is not limited to the above-described logarithmic mapping.
  • the pre-correction processing unit is mainly responsible for pre-correcting the main link signal.
  • Step 1 the address is generated. Calculate the amplitude or power of the main link signal, and calculate the index address of the corrected signal according to equation (1).
  • Step 2 calculating a distortion correction signal. Use the generated index address to find the corresponding content in the correction parameters.
  • Step 3 Pre-correction processing.
  • the main link signal is pre-corrected according to equations (2), (3), and (4) to obtain a pre-corrected signal.
  • 7 is a basic structural diagram of an adaptor according to an example of the present invention, including a data acquisition unit, a signal processing unit, and a correction parameter identification unit.
  • the data acquisition unit is mainly responsible for collecting the processing data required for the calibration parameter identification, including the main link signal and the feedback digital signal, and can also be used for directly collecting the pre-corrected signal. It should be noted that the acquisition of the pre-corrected signal is not necessary, and the pre-corrected signal may be indirectly obtained by performing pre-correction processing on the collected main link signal.
  • the signal processing unit is mainly responsible for performing necessary data preprocessing on the acquired digital signals.
  • the correction parameter identification unit is mainly responsible for constructing the parameter identification matrix R and the target matrix/) according to a predetermined distortion model, using the parameter identification algorithm to identify the correction parameters, and downloading the correction parameters to the correction information generation unit. .
  • a parameter download unit may be separately set, which is responsible for saving and updating the correction parameters, and then downloading the correction parameters into the correction information generating unit.
  • the distortion model can use a general memory polynomial model, as follows: Among them, the input signal for the model is the signal delay, P is the model order, J, K is the maximum delay, and P is the highest order of the model, which is the model coefficient.
  • the output signal of the signal generator module is the target matrix /); the available distortion model is not limited to the general memory polynomial model, but also the Wiener model, the Hammerstein model, the Volterra model, the neural network, the wavelet network, etc. .
  • the calibration parameter identification can use a least squares identification algorithm.
  • FIG. 8 is a schematic diagram showing the specific structure of a power amplifier pre-correcting apparatus according to an example 1 of the present invention.
  • the nonlinear system is a power amplifier, and each module is not explicitly shown in the figure, but is represented by a function realized.
  • the entire system includes a baseband signal module, a channel filter module, a pre-corrector module, a DAC module, an ADC module, an up-conversion module, a down-conversion module, an LO module, a power amplifier module, and an attenuator module.
  • the pre-corrected signal is obtained according to the pre-correction function shown in equation (8).
  • the parameter identification matrix R is constructed according to equation (7), and the target matrix /) is constructed by the difference between the feedback signal and the pre-corrected signal, as shown in equation (9).
  • FIG. 9 is a schematic diagram showing the specific structure of a power amplifier pre-correcting apparatus according to Example 2 of the present invention.
  • the nonlinear system is a power amplifier, and each module is not explicitly shown in the figure, but is represented by a function realized.
  • the entire system includes a baseband signal module, a channel filter module, a pre-corrector module, a DAC module, an ADC module, an up-conversion module, a down-conversion module, an LO module, a power amplifier module, and an attenuator module as application basis.
  • the multiple item constructor constructs a plurality of item sequences M according to equations (10) and (11), and the compensator constructs a correction signal according to equation (12), and the pre-corrected signal is according to equation (13).
  • the pre-correction function is obtained.
  • the parameter identification matrix R is constructed according to equation (7), and the target matrix /) is constructed by the difference between the pre-corrected signal and the feedback signal, as shown in equation (13).
  • Other modules are handled in the same manner as described above and in the prior art.
  • P is the highest order of the polynomial
  • is the modulo operation
  • X is the multi-carrier combined signal
  • ⁇ is the signal delay.
  • FIG. 10 is a flowchart of a nonlinear system distortion correction method according to an embodiment of the present invention.
  • the nonlinear system distortion correction method according to the embodiment of the present invention includes: Step S1002: collecting primary link data and feedback link data; Step S1004, collecting collected primary link data and feedback link data Performing preprocessing; Step S1006: performing parameter identification according to the preprocessed main link data and the feedback link data to obtain a correction parameter of the nonlinear system; and in step S1008, performing pre-correction processing on the main link data according to the correction parameter.
  • step S1006 may further include the following processes: (1) constructing a parameter identification matrix and a target matrix according to the distortion correction model, the pre-corrected signal, and the preprocessed main link data and the feedback link data;
  • the calibration parameter identification is divided into three steps. First, construct the parameter identification matrix, which is the parameter identification matrix and the target matrix.
  • the parameter identification matrix and the target matrix are the pre-processed main link signals, the pre-processed feedback signals and the pre-processing.
  • the corrected signal ie, the input signal of the nonlinear system
  • the pseudo inverse matrix of the parameter identification matrix is calculated; finally, the predetermined parameter identification algorithm is used for the target matrix and the parameter identification matrix.
  • the pseudo inverse matrix is used for parameter identification, and the correction parameters of the nonlinear system are obtained.
  • the distortion correction model may include one of the following: a general memory polynomial model, a Wiener model, a Hammerstein model, a Volterra model, a neural network, a wavelet network; a P/or, a parameter identification matrix and a pseudo-inverse matrix of the target matrix.
  • the algorithm may include one of the following: singular value decomposition, QR decomposition, Cholesky decomposition; and/or, the predetermined parameter identification algorithm may include one of the following: a least squares algorithm, a recursive least squares algorithm, a least mean square algorithm.
  • the models and algorithms that can be used include, but are not limited to, the above-mentioned models and algorithms, and may be expanded and differently matched according to specific needs.
  • step S1008 may further include the following processing:
  • Pre-correction can also be divided into three steps. First, linear or non-linear mapping of the amplitude or power of the main link signal is generated to generate index address information. Secondly, the content corresponding to the index address information is searched for in the correction parameter. A distortion correction signal is generated. Finally, the main link signal is pre-corrected according to the distortion correction signal to obtain a pre-corrected signal to cancel the nonlinear distortion generated by the subsequent nonlinear system.
  • the mapping algorithm for generating the index address information may include: Where a is the address information of the correction signal, and
  • X [x(n), ⁇ ( ⁇ _ 1), ... , x(n _ J)], where is the distortion correction signal vector found based on the index address information, the main link signal vector, f
  • J is the maximum delay of the main link signal, "for the signal sampling time serial number, _y is the pre-corrected signal;
  • ⁇ ( ⁇ ) is the pre-correction function.
  • the nonlinear system distortion correction method may include the following steps in the specific implementation process: Step S1102, receiving a baseband signal; Step S1104, baseband signal passing through the channel a filter module, implementing pulse shaping and sampling rate conversion to obtain a main link signal; and step S 1106, coupling a feedback signal from the power amplifier output port; Step S1108, the carrier frequency point conversion is completed by down-conversion of the coupled feedback signal; step S1110, obtaining a feedback link signal through the ADC; step S1112, performing correction parameter identification according to the main link signal, the feedback link signal, and the pre-corrected signal , Determine the calibration parameters.
  • Step S1114 the main link signal is subjected to pre-correction processing to obtain a pre-corrected signal; in step S1116, the pre-corrected signal is converted by the DAC to the analog signal.
  • the technical solution provided by the present invention is not limited to pre-correction only for GSM multi-carrier signals, and the pre-correction effect is superior to the conventional ones for GSM, CDMA, UMTS, TD-SCDMA, LTE, WiMAX, and various mixed-mode signals.
  • Pre-correction technology for GSM, CDMA, UMTS, TD-SCDMA, LTE and WiMAX single-mode or multi-mode systems.
  • the above modules or steps of the present invention can be implemented by a general-purpose computing device, which can be concentrated on a single computing device or distributed over a network composed of multiple computing devices.
  • the computing device may be implemented by program code executable by the computing device, such that they may be stored in the storage device by the computing device and, in some cases, may be different from the order herein.
  • the steps shown or described are performed, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps are fabricated as a single integrated circuit module.
  • the invention is not limited to any specific combination of hardware and software.
  • the above is only the preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes can be made to the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and scope of the present invention are intended to be included within the scope of the present invention.

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Abstract

L'invention porte sur un appareil et un procédé de correction de distorsion pour un système non linéaire. L'appareil comprend : un module d'adaptation et un module de précorrection. Le module d'adaptation comprend : une unité de collecte de données pour collecter des données de liaison hôtes et des données de liaison de rétroaction ; une unité de traitement de signal pour prétraiter les données de liaison hôtes et les données de liaison de rétroaction collectées ; une unité d'identification de paramètres de correction pour identifier des paramètres en fonction des données de liaison hôtes et des données de liaison de rétroaction prétraitées afin d'obtenir les paramètres de correction d'un système non linéaire ; et un module de précorrection pour précorriger les données de liaison hôtes en fonction des paramètres de correction. Tandis que le procédé de prétraitement numérique existant ne réussit pas à atteindre l'exigence de grande linéarité, la solution technique de la présente invention résout le problème, améliorant ainsi la précision d'identification des paramètres de correction.
PCT/CN2011/084583 2011-06-23 2011-12-23 Appareil et procédé de correction de distorsion pour système non linéaire WO2012174842A1 (fr)

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