WO2018192252A1 - 一种数字预失真处理方法和装置 - Google Patents

一种数字预失真处理方法和装置 Download PDF

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Publication number
WO2018192252A1
WO2018192252A1 PCT/CN2017/117525 CN2017117525W WO2018192252A1 WO 2018192252 A1 WO2018192252 A1 WO 2018192252A1 CN 2017117525 W CN2017117525 W CN 2017117525W WO 2018192252 A1 WO2018192252 A1 WO 2018192252A1
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Prior art keywords
input signal
signal
threshold
power amplifier
output signal
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PCT/CN2017/117525
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English (en)
French (fr)
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WO2018192252A8 (zh
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吴卓智
刁穗东
姜成玉
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京信通信***（中国）有限公司
京信通信***（广州）有限公司
京信通信技术(广州)有限公司
天津京信通信***有限公司
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Publication of WO2018192252A1 publication Critical patent/WO2018192252A1/zh
Publication of WO2018192252A8 publication Critical patent/WO2018192252A8/zh

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    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03F—AMPLIFIERS
    • H03F1/00—Details of amplifiers with only discharge tubes, only semiconductor devices or only unspecified devices as amplifying elements
    • H03F1/32—Modifications of amplifiers to reduce non-linear distortion
    • H03F1/3241—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits
    • H03F1/3247—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits using feedback acting on predistortion circuits
    • H—ELECTRICITY
    • H03—ELECTRONIC CIRCUITRY
    • H03F—AMPLIFIERS
    • H03F1/00—Details of amplifiers with only discharge tubes, only semiconductor devices or only unspecified devices as amplifying elements
    • H03F1/32—Modifications of amplifiers to reduce non-linear distortion
    • H03F1/3241—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits
    • H03F1/3258—Modifications of amplifiers to reduce non-linear distortion using predistortion circuits based on polynomial terms

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  • Embodiments of the present invention relate to the field of intelligent transportation, and in particular, to a digital predistortion processing method and apparatus.
  • DPD Digital Pre-Distortio
  • the predistortion data acquisition method used in the prior art is to set a fixed threshold value, and the data is collected according to a fixed threshold value for calculating the predistortion coefficient, but in order to ensure the success rate of data acquisition, the conditions for data acquisition are relaxed. The resulting data does not fully reflect the characteristics of nonlinear distortion, which affects the predistortion performance.
  • Embodiments of the present invention provide a digital predistortion processing method and apparatus for solving the problem that the digital predistortion data acquisition cannot fully reflect the nonlinear distortion characteristic by using a fixed threshold value in the prior art.
  • an embodiment of the present invention provides a digital predistortion processing method, including:
  • the set threshold is adjusted according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the method further includes: continuing to acquire an input signal of the power amplifier and an output signal of the power amplifier when determining that the collected input signal does not satisfy the set threshold.
  • the determining a fitting error of the carrier according to the updated pre-distortion coefficient, the collected input signal, and the collected output signal includes:
  • the fitting error is determined based on the fitted power amplifier input signal and the acquired input signal.
  • the formula (1) is:
  • Input the signal for the fitted amplifier For the updated pre-distortion coefficient, y(nl) is the acquired output signal, k is the polynomial order, K is the polynomial maximum order, l is the memory depth, and L is the maximum memory depth;
  • z(n) is the input signal of the acquisition
  • N is the number of sampling points of the signal
  • n is greater than or equal to zero.
  • the setting threshold includes an amplitude threshold and a quantity threshold
  • Adjusting the set threshold according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the pre-distortion coefficient including:
  • the amplitude threshold and the quantity threshold are adjusted according to the cancellation index.
  • K_dpd [ ⁇ (CC 0 )+ ⁇ (30+10 ⁇ lg( ⁇ )-Ps)]..................(3)
  • K_dpd is the cancellation index
  • C is the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient
  • C 0 is the adjacent frequency leakage ratio of the signal before predistortion
  • ⁇ is the fitting error
  • Ps is the power of the signal
  • ⁇ And ⁇ are weighting coefficients
  • a p is the adjusted amplitude threshold
  • K_dpd is the cancellation index
  • a 1 is the initial amplitude threshold
  • Equation (5) is:
  • B q is the adjusted number threshold
  • K_dpd is the cancellation index
  • B 1 is the initial number threshold
  • an embodiment of the present invention provides a digital predistortion processing apparatus, including:
  • An acquisition module configured to acquire an input signal of the power amplifier and an output signal of the power amplifier, where the input signal of the power amplifier is a pre-distorted processed signal
  • an updating module configured to: when determining that the collected input signal meets the set threshold, updating the pre-distortion coefficient according to the collected input signal and the collected output signal;
  • a processing module configured to determine a fitting error according to the updated pre-distortion coefficient, the collected input signal, and the collected output signal;
  • an adjustment module configured to adjust the set threshold according to the fitting error and an adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the update module is further configured to:
  • the input signal of the power amplifier and the output signal of the power amplifier are continuously acquired.
  • processing module is specifically configured to:
  • the fitting error is determined based on the fitted power amplifier input signal and the acquired input signal.
  • processing module is specifically configured to:
  • the formula (1) is:
  • Input the signal for the fitted amplifier For the updated pre-distortion coefficient, y(nl) is the acquired output signal, k is the polynomial order, K is the polynomial maximum order, l is the memory depth, and L is the maximum memory depth;
  • the fitting error of the carrier is determined according to the following formula (2);
  • z(n) is the input signal of the acquisition
  • N is the number of sampling points of the signal
  • n is greater than or equal to zero.
  • the adjusting module is specifically configured to:
  • the set threshold includes an amplitude threshold and a quantity threshold
  • the amplitude threshold and the quantity threshold are adjusted according to the cancellation index.
  • the adjusting module is specifically configured to:
  • K_dpd [ ⁇ (CC 0 )+ ⁇ (30+10 ⁇ lg( ⁇ )-Ps)]..................(3)
  • K_dpd is the cancellation index
  • C is the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient
  • C 0 is the adjacent frequency leakage ratio of the signal before predistortion
  • ⁇ is the fitting error
  • Ps is the power of the signal
  • ⁇ And ⁇ are weighting coefficients
  • a p is the adjusted amplitude threshold
  • K_dpd is the cancellation index
  • a 1 is the initial amplitude threshold
  • B q is the adjusted number threshold
  • K_dpd is the cancellation index
  • B 1 is the initial number threshold
  • an embodiment of the present invention provides a digital pre-distortion processing device, including:
  • At least one processor and,
  • the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the digital predistortion processing method of the first aspect above .
  • an embodiment of the present invention provides a non-transitory computer readable storage medium, where the non-transitory computer readable storage medium stores computer instructions for causing the computer to perform the first aspect described above Digital predistortion processing method.
  • an embodiment of the present invention provides a computer program product, the computer program product comprising a computing program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, when the program instruction When executed by a computer, the computer is caused to perform the digital predistortion processing method of the above first aspect.
  • the embodiment of the invention shows that the input signal of the power amplifier and the output signal of the power amplifier are collected, and the input signal of the power amplifier is a signal after pre-distortion processing.
  • the pre-distortion coefficient is updated according to the acquired input signal and the acquired output signal.
  • a fitting error is then determined based on the updated pre-distortion coefficient, the acquired input signal, and the acquired output signal.
  • the set threshold is adjusted according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the pre-distortion processed signal is collected for threshold determination, and when it is determined that the collected signal meets the set threshold, the pre-distortion coefficient is updated and the set threshold is adjusted using the collected signal. Therefore, the use of real-time updated pre-distortion coefficients and set thresholds for data acquisition can better reflect the characteristics of nonlinear distortion, thereby improving the performance of digital pre-distortion processing.
  • FIG. 1 is a system architecture diagram of a digital pre-distortion processing system according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a digital pre-distortion processing method according to an embodiment of the present invention
  • FIG. 3 is a schematic flowchart of a method for adjusting a threshold according to an embodiment of the present disclosure
  • FIG. 4 is a schematic flowchart diagram of another digital pre-distortion processing method according to an embodiment of the present disclosure.
  • FIG. 5 is a schematic structural diagram of a digital pre-distortion processing apparatus according to an embodiment of the present disclosure
  • FIG. 6 is a schematic structural diagram of a digital pre-distortion processing device according to an embodiment of the present invention.
  • FIG. 1 exemplarily shows a system architecture diagram of a digital predistortion processing system, as shown in FIG. 1:
  • the digital predistortion processing system 100 includes a peak reduction unit 101, a DPD processing unit 102, a power amplifier 103, a data acquisition unit 104, a DPD coefficient calculation unit 105, a fitting error calculation unit 106, an adjacent frequency leakage ratio calculation unit 107, and a threshold adjustment unit. 108.
  • the data acquisition unit 104 can be implemented by using an analog-to-digital converter (ADC), a DPD coefficient calculation unit 105, a fitting error calculation unit 106, an adjacent frequency leakage ratio calculation unit 107, and a threshold.
  • the adjustment unit 108 can be integrated on a dedicated chip or implemented using a serial processor such as Digital Signal Processing (DSP) or a soft core.
  • the DPD processing unit 102 can be implemented using a parallel processor such as a Field Programmable Gate Array (FPGA) or a dedicated chip.
  • FPGA Field Programmable Gate Array
  • the peak reduction unit 101, the DPD processing unit 102, and the power amplifier 103 are sequentially connected, and the input signal is input to the DPD processing unit 102 by the peak reduction unit 101 to lower the mean peak ratio.
  • the DPD processing unit 102 is connected to the DPD coefficient calculation unit 105 for performing DPD processing on the signal according to the DPD coefficient calculated by the DPD coefficient calculation unit 105, and then inputting the signal to the power amplifier 103 and outputting the signal.
  • Both ends of the data acquisition unit 104 are respectively connected to the input terminal and the output terminal of the power amplifier 103 for collecting the input signal of the power amplifier 103 and the output signal of the power amplifier 103.
  • the data collection module 104 is connected to the threshold adjustment unit 108 for threshold determination of the collected signals according to the adjusted thresholds in the threshold adjustment unit 108.
  • the data acquisition unit 104, the DPD coefficient calculation unit 105 and the fitting error calculation unit 106 are sequentially connected for inputting the acquired signal to the DPD coefficient calculation unit 105 to update the DPD coefficient when determining that the acquired signal satisfies the set threshold, and then collecting the collected DPD coefficient.
  • the signal and the updated DPD coefficient input fitting error calculation unit 106 calculates the fitting error of the carrier.
  • the data collecting unit 104 is further connected to the adjacent frequency leakage ratio calculating unit 107, and is configured to update the pre-distortion coefficient and then collect the power amplifier output signal once, and input the collected signal into the adjacent frequency leakage ratio calculating unit 107 to calculate the adjacent frequency leakage ratio of the signal. It should be noted that the power amplifier output signal collected this time does not need to be judged by the threshold.
  • the fitting error calculation unit 106 and the adjacent frequency leakage ratio calculating unit 107 are both connected to the threshold adjusting unit 108 for adjusting the set threshold according to the calculated fitting error and the adjacent frequency leakage ratio, and inputting the adjusted setting threshold. Data acquisition unit 104.
  • FIG. 2 exemplarily shows a flow of a digital pre-distortion processing method provided by an embodiment of the present invention, which may be performed by a digital pre-distortion processing system. As shown in Figure 2, the specific steps of the process include:
  • Step S201 collecting an input signal of the power amplifier and an output signal of the power amplifier.
  • Step S202 when it is determined that the collected input signal meets the set threshold, the pre-distortion coefficient is updated according to the collected input signal and the collected output signal.
  • Step S203 determining a fitting error according to the updated pre-distortion coefficient, the collected input signal, and the collected output signal;
  • Step S204 adjusting the set threshold according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the digital predistortion system before acquiring the input signal of the power amplifier and the output signal of the power amplifier, the digital predistortion system first receives the signal, and then performs predistortion processing on the received signal according to the predistortion coefficient, and finally inputs the signal after the predistortion processing.
  • Power amplifier The predistortion process conforms to the following formula (6):
  • Z(n) is the signal after pre-distortion processing
  • a kl is the pre-distortion coefficient
  • X(nl) is the signal before pre-loss processing
  • k is the polynomial order
  • K is the polynomial maximum order
  • l is the memory depth
  • L is the maximum memory depth.
  • the set threshold includes an amplitude threshold and a quantity threshold.
  • Set the length of the input signal to be one frame length, specifically 4096 points, the initial amplitude threshold is 5000, and the initial number threshold is 20.
  • the pre-distortion coefficient is updated according to the collected input signal and the acquired output signal, and the set threshold is adjusted.
  • the digital predistortion system receives the next set of signals, the signal is predistorted and input to the power amplifier using the updated predistortion coefficient.
  • the digital predistortion system uses the adjusted set threshold to threshold the collected input signal and the collected output signal, and iterates sequentially.
  • the digital predistortion system reacquires the input signal of the power amplifier and the output signal of the power amplifier, and uses the unadjusted setting.
  • the threshold value is used to determine the threshold value of the input signal.
  • the input signal of the power amplifier is a pre-distortion processed signal according to the unupdated pre-distortion coefficient. It should be noted that, when the counting failure counter is greater than the preset value, it indicates that the mining number is abnormal, and further measures need to be taken at this time, specifically: determining whether the quantity threshold B is the initial quantity threshold B1.
  • B ⁇ B1 use the lower-level quantity threshold as the new quantity threshold for threshold judgment.
  • the current quantity threshold is Bq
  • (Bq-Bs) is used as the new quantity threshold
  • Bs is the quantity threshold change.
  • Step size the lower threshold value is used as the new amplitude threshold for threshold determination.
  • the current amplitude threshold is set to Ap
  • (Ap-As) is used as a new amplitude threshold
  • As is a change step of the amplitude threshold.
  • the pre-distortion processed signal is collected for threshold determination, and the pre-distortion coefficient is updated by the collected signal when the collected signal meets the set threshold, and the threshold is also adjusted according to the pre-distortion processed signal in real time. Therefore, using the adjusted threshold value to perform threshold determination on the currently acquired pre-distortion processed signal can better reflect the characteristics of nonlinear distortion, thereby improving the performance of the digital pre-distortion processing.
  • adjusting the set threshold according to the updated pre-distortion coefficient and the collected input signal and the collected output signal specifically includes the following steps, as shown in FIG. 3:
  • Step 301 Determine a fitted power amplifier input signal according to the updated pre-distortion coefficient and the collected output signal.
  • Step 302 Determine a fitting error according to the fitted power amplifier input signal and the collected input signal.
  • Step 303 adjusting the amplitude threshold and the quantity threshold according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • step S301 determining the fitted power amplifier input signal according to the updated pre-distortion coefficient and the collected output signal conforms to the following formula (1);
  • Input the signal for the fitted amplifier For the updated pre-distortion coefficient, y(nl) is the acquired output signal, k is the polynomial order, K is the polynomial maximum order, l is the memory depth, and L is the maximum memory depth;
  • step S302 the fitting error of the carrier is determined according to the fitted power amplifier input signal and the collected input signal according to the following formula (2):
  • z(n) is the input signal of the acquisition
  • N is the number of sampling points of the signal
  • n is greater than or equal to zero.
  • step S303 adjusting the amplitude threshold and the quantity threshold according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient specifically includes two methods:
  • Method 1 Determine the cancellation index according to the fitting error and the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient, which specifically meets the following formula (3):
  • K_dpd [ ⁇ (CC 0 )+ ⁇ (30+10 ⁇ lg( ⁇ )-Ps)]..................(3)
  • K_dpd is the cancellation index
  • C is the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient
  • C 0 is the adjacent frequency leakage ratio of the signal before predistortion
  • ⁇ is the fitting error
  • Ps is the power of the signal
  • ⁇ And ⁇ is a weighting factor.
  • the amplitude threshold is adjusted, which is in accordance with the following formula (4):
  • a p is the adjusted amplitude threshold
  • K_dpd is the cancellation index
  • a 1 is the initial amplitude threshold
  • B q is the adjusted number threshold
  • K_dpd is the cancellation index
  • B 1 is the initial number threshold.
  • the present invention provides the following specific embodiments, setting the initial amplitude threshold to 5000, the initial number threshold to 20, the pre-distortion fitting error to 14 dBm, and the signal power to 34 dBm.
  • the pre-distortion adjacent-frequency leakage ratio is -46dBc
  • the initial adjacent-frequency leakage ratio of the signal is -30dBc.
  • the adjusted amplitude threshold calculated by equations (4) and (5) is 5150, and the adjusted number threshold is 25. Then, when the threshold value is judged for the next acquired input signal and the collected output signal, the amplitude threshold is 5150 and the number threshold is 25.
  • Method 2 Adjust the amplitude threshold according to the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient, specifically: the adjacent frequency leakage ratio of the signal before the predistortion processing is used as the initial adjacent frequency leakage ratio, and the initial adjacent frequency leakage ratio is used as the starting point. Every 3dBc is divided into one interval, and the interval is left closed and right open. At the same time, the 0 to initial adjacent frequency leakage is merged into the first interval. The value of the adjacent frequency leakage ratio is divided into n intervals C1, C2, C3, ..., Cn, and each interval corresponds to an amplitude threshold A1, A2, A3, ... An. Judging the interval of the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient, the amplitude threshold corresponding to the interval is the adjusted amplitude threshold A p , which specifically conforms to the following formula (7)
  • a p is the adjusted amplitude threshold
  • a 1 is the initial amplitude threshold
  • p is the number of intervals corresponding to the interval in which the adjacent frequency leakage ratio of the output signal is updated after updating the predistortion coefficient
  • p is an integer greater than 0.
  • the adjusted amplitude threshold is used when the threshold is judged after the next data acquisition.
  • the number threshold is adjusted according to the fitting error, specifically: the fitting error is divided into an interval from 0dBc to -30dBc every 3dBc, the interval is left closed and right open, and the fitting error is divided into m intervals D1, D2, D3, ..., Dm Each interval corresponds to a quantity threshold B1, B2, B3, ..., Bm.
  • the interval in which the current fitting error is located is determined, and the adjusted number threshold B q is determined according to the interval number corresponding to the interval in which the current fitting error is located and the initial number threshold, which specifically conforms to the following formula (8):
  • B q is the adjusted number threshold and B 1 is the initial number threshold.
  • q is the number of intervals corresponding to the interval in which the current fitting error is located, and q is an integer greater than 0.
  • the adjusted number threshold is used when the threshold is judged after the next data acquisition.
  • the present invention provides the following specific embodiments: setting the initial amplitude threshold to 5000, the initial number threshold to 20, the fitting error to -20 dBc, and the output signal after updating the pre-distortion coefficient.
  • the adjacent frequency leakage ratio is -46dBc
  • the adjusted amplitude threshold and quantity threshold are used when the threshold is judged after the next data acquisition.
  • the set threshold is adjusted according to the updated pre-distortion coefficient, so the updated pre-distortion coefficient and the adjusted set threshold are used in the next pre-distortion processing and threshold determination.
  • Mutual cooperation can better solve the problem of changing data characteristics in digital predistortion processing.
  • step S401 an input signal N is received.
  • step S402 the signal X is obtained by lowering the peak-to-average ratio of the input signal N.
  • Step S403 acquiring the pre-distortion coefficient a1 and performing predistortion processing on the signal X according to the predistortion coefficient a1 to obtain the signal Z.
  • step S404 the signal Z is input to the power amplifier to obtain a power output signal Y.
  • step S405 the acquisition signal Z and the signal Y respectively obtain the signal z0 and the signal y0.
  • step S406 it is determined whether the signal z0 satisfies the set threshold. If yes, step S407 is performed, otherwise step S412 is performed.
  • step S407 the predistortion coefficient a1 is updated to the predistortion coefficient a2 based on the signal z0 and the signal y0.
  • Step S408 pre-distortion processing the signal X according to the pre-distortion coefficient a2 and amplifying the processing result by the power amplifier to obtain the signal Y1.
  • step S409 the signal Y1 is acquired to obtain a power amplifier output signal y1 after updating the predistortion coefficient.
  • Step S410 calculating a fitting error according to the predistortion coefficient a2, the signal z0, and the signal y0.
  • Step S411 adjusting the set threshold according to the fitting error and the adjacent frequency leakage ratio of the power amplifier output signal y1 after updating the predistortion coefficient.
  • step S412 the number of failed attempts is increased by one.
  • step S413 it is determined whether the number of failed attempts is greater than a preset value, and if yes, step S414 is performed, otherwise step S416 is performed.
  • step S414 the set threshold is updated using a lower level quantity threshold or an amplitude threshold.
  • step S415 the input signal of the power amplifier and the output signal of the power amplifier are continuously collected, and the threshold determination is continued using the updated set threshold.
  • step S416 the input signal of the power amplifier and the output signal of the power amplifier are continuously collected, and the threshold determination is continued using the set threshold.
  • the input signal of the power amplifier and the output signal of the power amplifier are collected, and when the collected input signal meets the set threshold, the pre-distortion coefficient and the set threshold are updated by using the collected input signal and the collected output signal, and after updating,
  • the pre-distortion coefficient is used for the next pre-distortion process to obtain the input signal of the power amplifier
  • the updated set threshold is used for threshold determination of the next acquired input signal and the collected output signal, and iteratively, so the pre-distortion coefficient and setting The threshold is always associated with real-time pre-distortion processing data for better pre-distortion processing.
  • FIG. 5 exemplarily shows the structure of a digital pre-distortion processing apparatus provided by an embodiment of the present invention, which can perform a flow of digital pre-distortion processing.
  • the device includes:
  • the acquisition module 501 is configured to collect an input signal of the power amplifier and an output signal of the power amplifier, where the input signal of the power amplifier is a pre-distort processed signal;
  • the updating module 502 is configured to: when determining that the collected input signal meets the set threshold, update the pre-distortion coefficient according to the collected input signal and the collected output signal;
  • the processing module 503 is configured to determine a fitting error according to the updated pre-distortion coefficient, the collected input signal, and the collected output signal;
  • the adjusting module 504 is configured to adjust the set threshold according to the fitting error and an adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the update module 502 is further configured to:
  • the input signal of the power amplifier and the output signal of the power amplifier are continuously acquired.
  • processing module 503 is specifically configured to:
  • the fitting error is determined based on the fitted power amplifier input signal and the acquired input signal.
  • processing module 503 is specifically configured to:
  • the formula (1) is:
  • Input the signal for the fitted amplifier For the updated pre-distortion coefficient, y(nl) is the acquired output signal, k is the polynomial order, K is the polynomial maximum order, l is the memory depth, and L is the maximum memory depth;
  • the fitting error of the carrier is determined according to the following formula (2);
  • z(n) is the input signal of the acquisition
  • N is the number of sampling points of the signal
  • n is greater than or equal to zero.
  • the adjusting module 504 is specifically configured to:
  • the set threshold includes an amplitude threshold and a quantity threshold
  • the amplitude threshold and the quantity threshold are adjusted according to the cancellation index.
  • the adjusting module 504 is specifically configured to:
  • K_dpd [ ⁇ (CC 0 )+ ⁇ (30+10 ⁇ lg( ⁇ )-Ps)]..................(3)
  • K_dpd is the cancellation index
  • C is the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient
  • C 0 is the adjacent frequency leakage ratio of the signal before predistortion
  • ⁇ is the fitting error
  • Ps is the power of the signal
  • ⁇ And ⁇ are weighting coefficients
  • a p is the adjusted amplitude threshold
  • K_dpd is the cancellation index
  • a 1 is the initial amplitude threshold
  • the number threshold is adjusted according to the following formula (5); the formula (5) is:
  • B q is the adjusted number threshold
  • K_dpd is the cancellation index
  • a 1 is the initial number threshold
  • an embodiment of the present invention provides a digital predistortion processing apparatus. At least one processor; and a memory communicatively coupled to the at least one processor; the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor such that The at least one processor is capable of executing the digital pre-distortion processing method in the above embodiment.
  • FIG. 6 is a configuration of a digital pre-distortion processing device according to an embodiment of the present invention.
  • the digital pre-distortion processing device 600 includes a transceiver 601, a processor 602, a memory 603, and a bus system 604.
  • the memory 603 is used to store a program.
  • the program can include program code, the program code including computer operating instructions.
  • the memory 603 may be a random access memory (RAM) or a non-volatile memory, such as at least one disk storage. Only one memory is shown in the figure, of course, the memory can also be set to a plurality as needed. Memory 603 can also be a memory in processor 602.
  • the memory 603 stores the following elements, executable modules or data structures, or a subset thereof, or an extended set thereof:
  • Operation instructions include various operation instructions for implementing various operations.
  • Operating system Includes a variety of system programs for implementing various basic services and handling hardware-based tasks.
  • the digital predistortion processing method of the above embodiment of the present invention may be applied to the processor 602 or implemented by the processor 602.
  • Processor 602 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above digital pre-distortion processing method may be completed by an integrated logic circuit of hardware in the processor 602 or an instruction in a form of software.
  • the processor 602 described above may be a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, or discrete hardware. Component.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA field programmable gate array
  • the methods, steps, and logical block diagrams disclosed in the embodiments of the present application can be implemented or executed.
  • the general purpose processor may be a microprocessor or the processor or any conventional processor or the like.
  • the steps of the method disclosed in the embodiments of the present invention may be directly implemented by the hardware decoding processor, or may be performed by a combination of hardware and software modules in the decoding processor.
  • the software module can be located in a conventional storage medium such as random access memory, flash memory, read only memory, programmable read only memory or electrically erasable programmable memory, registers, and the like.
  • the storage medium is located in the memory 603, and the processor 602 reads the information in the memory 603 and performs the following steps in conjunction with its hardware:
  • the transceiver 601 is configured to collect an input signal of the power amplifier and an output signal of the power amplifier, where the input signal of the power amplifier is a predistort processed signal;
  • the processor 602 is configured to: when determining that the collected input signal meets the set threshold, update the pre-distortion coefficient according to the collected input signal and the collected output signal; according to the updated pre-distortion coefficient, the acquiring The input signal and the acquired output signal determine a fitting error; the set threshold is adjusted according to the fitting error and an adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient.
  • the processor 602 is further configured to continue to collect an input signal of the power amplifier and an output signal of the power amplifier when determining that the collected input signal does not satisfy the set threshold.
  • the processor 602 is configured to determine a fitted power amplifier input signal according to the updated pre-distortion coefficient and the collected output signal, and determine, according to the matched power amplifier input signal and the collected input signal, The fitting error is described.
  • the processor 602 is configured to determine a fitted power amplifier input signal according to the following formula (1);
  • the formula (1) is:
  • Input the signal for the fitted amplifier For the updated pre-distortion coefficient, y(nl) is the acquired output signal, k is the polynomial order, K is the polynomial maximum order, l is the memory depth, and L is the maximum memory depth;
  • the fitting error of the carrier is determined according to the following formula (2);
  • z(n) is the input signal of the acquisition
  • N is the number of sampling points of the signal
  • n is greater than or equal to zero.
  • the processor 602 is configured to determine a cancellation index according to the fitting error and an adjacent frequency leakage ratio of the output signal after updating the pre-distortion coefficient; and the amplitude threshold and the quantity threshold according to the cancellation index The adjustment is made, and the set threshold includes an amplitude threshold and a quantity threshold.
  • the processor 602 is configured to determine a cancellation index according to the following formula (3);
  • K_dpd [ ⁇ (CC 0 )+ ⁇ (30+10 ⁇ lg( ⁇ )-Ps)]..................(3)
  • K_dpd is the cancellation index
  • C is the adjacent frequency leakage ratio of the output signal after updating the predistortion coefficient
  • C 0 is the adjacent frequency leakage ratio of the signal before predistortion
  • ⁇ is the fitting error
  • Ps is the power of the signal
  • ⁇ And ⁇ are weighting coefficients
  • a p is the adjusted amplitude threshold
  • K_dpd is the cancellation index
  • a 1 is the initial amplitude threshold
  • B q is the adjusted number threshold
  • K_dpd is the cancellation index
  • B 1 is the initial number threshold
  • an embodiment of the present invention provides a non-transitory computer readable storage medium, where the non-transitory computer readable storage medium stores computer instructions for causing the computer to perform any of the above The digital predistortion processing method described in the item.
  • an embodiment of the present invention provides a computer program product, the computer program product comprising a computing program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions, when the program When the instruction is executed by the computer, the computer is caused to perform the digital predistortion processing method described in any of the above.
  • embodiments of the present invention can be provided as a method, or a computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely 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, CD-ROM, optical storage, etc.) including computer usable program code.
  • a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, 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.

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Abstract

一种数字预失真处理方法和装置，采集功率放大器的输入信号和功率放大器的输出信号（S201）。在确定采集的输入信号满足设定阈值时，根据采集的输入信号和采集的输出信号更新预失真系数（S202）。然后根据更新后的预失真系数、采集的输入信号和采集的输出信号确定拟合误差（S203）。最后根据拟合误差和更新预失真系数后输出信号的邻频泄露比调整设定阈值（S204）。在上述技术方案中，采集预失真处理后的信号进行阈值判断，在确定采集的信号满足设定阈值时，使用采集的信号更新预失真系数和调整设定阈值，故使用调整后的设定阈值对下一次采集的预失真处理后的信号进行阈值判断更能反映非线性失真的特性，从而提升预失真处理性能。

Description

一种数字预失真处理方法和装置
本申请要求在2017年4月20日提交中华人民共和国知识产权局、申请号为201710260788.3，发明名称为“一种数字预失真处理方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明实施例涉及智能交通领域，尤其涉及一种数字预失真处理方法和装置。
背景技术
随着无线通信的发展，信号的峰均比越来越大，功放不可避免的会工作在非线性区，从而带来大量的非线性失真，降低通信质量。现行业界解决方案是使用数字预失真(Digital Pre-Distortio，简称DPD)技术，信号首先通过一个预失真器进行校正，然后在再送到功放进行放大输出，预失真器产生的信号失真特性与发信通道的失真特性相反，从而可以抵消失真分量，得到无失真的信号输出。
在预失真过程中，需要采集数据计算预失真系数，采集数据的特性将直接影响预失真的效果。现有技术中使用的预失真数据采集方法是设置一个固定的门限值，根据固定的门限值采集数据用于计算预失真系数，但为了保证数据采集的成功率，会放宽数据采集的条件，导致采集的数据不能全面反映非线性失真的特性，从而影响预失真性能。
发明内容
本发明实施例提供一种数字预失真处理方法和装置，用于解决现有技术中采用固定的门限值进行数字预失真数据采集不能全面反映非线性失真特性的问题。
第一方面，本发明实施例提供了一种数字预失真处理方法，包括：
采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；
根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；
根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
可选地，还包括：在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
可选地，所述根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定载波的拟合误差，包括：
根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；
根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
可选地，根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号符合下述公式(1)；
所述公式(1)为：
Figure PCTCN2017117525-appb-000001
其中，
Figure PCTCN2017117525-appb-000002
为拟合的功放输入信号，
Figure PCTCN2017117525-appb-000003
为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度；
根据所述拟合的功放输入信号和所述采集的输入信号确定载波的拟合误差符合下述公式(2)；
所述公式(2)为：
Figure PCTCN2017117525-appb-000004
其中，
Figure PCTCN2017117525-appb-000005
为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
可选地，所述设定阈值包括幅度阈值和数量阈值；
所述根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值，包括：
根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；
根据所述对消指数对所述幅度阈值和所述数量阈值进行调整。
可选地，根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数符合下述公式(3)；
所述公式(3)为：
K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
根据所述对消指数对所述幅度阈值进行调整符合下述公式(4)；
所述公式(4)为：
A p＝A 1+30*K_dpd……………………………(4)
其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
根据所述对消指数对所述数量阈值进行调整符合下述公式(5)；所述公
式(5)为：
B q＝B 1+K_dpd……………………………(5)
其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。
第二方面，本发明实施例提供了一种数字预失真处理装置，包括：
采集模块，用于采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
更新模块，用于在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；
处理模块，用于根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；
调整模块，用于根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
可选地，所述更新模块还用于：
在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
可选地，所述处理模块具体用于：
根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；
根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
可选地，所述处理模块具体用于：
根据下述公式(1)确定拟合的功放输入信号；
所述公式(1)为：
Figure PCTCN2017117525-appb-000006
其中，
Figure PCTCN2017117525-appb-000007
为拟合的功放输入信号，
Figure PCTCN2017117525-appb-000008
为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度；
根据下述公式(2)确定载波的拟合误差；
所述公式(2)为：
Figure PCTCN2017117525-appb-000009
其中，
Figure PCTCN2017117525-appb-000010
为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
可选地，所述调整模块具体用于：
所述设定阈值包括幅度阈值和数量阈值；
根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；
根据所述对消指数对所述幅度阈值和所述数量阈值进行调整。
可选地，所述调整模块具体用于：
根据下述公式(3)确定对消指数；
所述公式(3)为：
K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
根据下述公式(4)调整所述幅度阈值；
所述公式(4)为：
A p＝A 1+30*K_dpd……………………………(4)
其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
根据下述公式(5)调整所述数量阈值；
所述公式(5)为：
B q＝B 1+K_dpd……………………………(5)
其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。
第三方面，本发明实施例提供了一种数字预失真处理设备，包括：
至少一个处理器；以及，
与所述至少一个处理器通信连接的存储器；其中，
所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所 述至少一个处理器执行，以使所述至少一个处理器能够执行上述第一方面中的数字预失真处理方法。
第四方面，本发明实施例提供了一种非暂态计算机可读存储介质，所述非暂态计算机可读存储介质存储计算机指令，所述计算机指令用于使所述计算机执行上述第一方面中的数字预失真处理方法。
第五方面，本发明实施例提供了一种计算机程序产品，所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述第一方面中的数字预失真处理方法。
本发明实施例表明，采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号。在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数。然后根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差。最后根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。本发明实施例中，采集预失真处理后的信号进行阈值判断，在确定采集的信号满足设定阈值时，使用采集的信号更新预失真系数和调整设定阈值。故使用实时更新的预失真系数和设定阈值进行数据采集更能反映非线性失真的特性，从而提升数字预失真处理的性能。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简要介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域的普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本发明实施例提供的一种数字预失真处理***的***架构图；
图2为本发明实施例提供的一种数字预失真处理方法的流程示意图；
图3为本发明实施例提供的设定阈值调整方法的流程示意图；
图4为本发明实施例提供的另一种数字预失真处理方法的流程示意图；
图5为本发明实施例提供的一种数字预失真处理装置的结构示意图；
图6为本发明实施例提供的一种数字预失真处理设备的结构示意图。
具体实施方式
为了使本发明的目的、技术方案及有益效果更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。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。
本发明实施例中的技术方案应用于数字预失真处理***，图1示例性示出了一种数字预失真处理***的***架构图，如图1所示：
数字预失真处理***100包括波峰降低单元101、DPD处理单元102、功率放大器103、数据采集单元104、DPD系数计算单元105、拟合误差计算单元106、邻频泄露比计算单元107、阈值调整单元108。在硬件实现上：数据采集单元104可以使用模数转换器(Analog-to-Digital Converter，简称ADC)实现，DPD系数计算单元105、拟合误差计算单元106、邻频泄露比计算单元107、阈值调整单元108可集成在专用芯片上或使用数字信号处理(Digital Signal Processing，简称DSP)或软核等串行处理器实现。DPD处理单元102可使用现场可编程门阵列(Field Programmable Gate Array，简称FPGA)或专用芯片等并行处理器实现。
波峰降低单元101、DPD处理单元102和功率放大器103依次连接，输入信号经波峰降低单元101降低均峰比后输入DPD处理单元102。DPD处理单元102与DPD系数计算单元105连接，用于根据DPD系数计算单元105计算得到的DPD系数对信号进行DPD处理，然后将信号输入功率放大器103后输出。数据采集单元104的两端分别与功率放大器103的输入端和输出端连接，用于采集功率放大器103的输入信号和功率放大器103的输出信号。数据采集模块104与阈值调整单元108连接，用于根据阈值调整单元108中 调整后的设定阈值对采集的信号进行阈值判断。数据采集单元104、DPD系数计算单元105和拟合误差计算单元106依次连接，用于在判断采集的信号满足设定阈值时将采集的信号输入DPD系数计算单元105更新DPD系数，然后将采集的信号以及更新的DPD系数输入拟合误差计算单元106计算载波的拟合误差。数据采集单元104还与邻频泄露比计算单元107连接，用于更新预失真系数后再采集一次功放输出信号，并将采集的信号输入邻频泄露比计算单元107计算信号的邻频泄露比，需要说明的是此次采集的功放输出信号不需要进行阈值判断。拟合误差计算单元106和邻频泄露比计算单元107均与阈值调整单元108连接，用于根据计算得到的拟合误差和邻频泄露比调整设定阈值，并将调整后的设定阈值输入数据采集单元104。
图2示例性示出了本发明实施例提供的一种数字预失真处理方法的流程，该流程可以由数字预失真处理***执行。如图2所示，该流程的具体步骤包括：
步骤S201，采集功率放大器的输入信号和功率放大器的输出信号。
步骤S202，在确定采集的输入信号满足设定阈值时，根据采集的输入信号和采集的输出信号更新预失真系数。
步骤S203，根据更新后的预失真系数、采集的输入信号和采集的输出信号确定拟合误差；
步骤S204，根据拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
具体实施中，在采集功率放大器的输入信号和功率放大器的输出信号之前，数字预失真***首先接收信号，然后根据预失真系数对接收的信号进行预失真处理，最后将预失真处理后的信号输入功率放大器。预失真处理过程符合下述公式(6)：
Figure PCTCN2017117525-appb-000011
其中Z(n)为预失真处理处理后的信号，a kl为预失真系数，X(n-l)为预失处 理前的信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度。
采集功率放大器的输入信号和功率放大器的输出信号之后，判断采集的输入信号是否满足设定阈值，设定阈值包括幅度阈值和数量阈值。设定采集的输入信号的长度为一个帧长度，具体为4096个点，初始幅度阈值为5000，初始数量阈值为20，首先判断采集的输入信号的幅度大于5000的数据个数，如果大于幅度阈值的数据个数大于20，则说明采集的输入信号满足设定阈值，否则说明采集的输入信号不满足设定阈值。
若采集的输入信号满足设定阈值，则根据采集的输入信号和采集的输出信号更新预失真系数以及调整设定阈值。数字预失真***在接收到下一组信号时，采用更新后的预失真系数对信号进行预失真处理并输入功率放大器。同样的，数字预失真***采用调整后的设定阈值对采集的输入信号和采集的输出信号进行阈值判断，依次迭代。
若采集的输入信号不满足设定阈值，则说明当前采集数据失败，采数失败计数器加一，数字预失真***重新采集功率放大器的输入信号和功率放大器的输出信号，并使用未调整的设定阈值对采集的输入信号进行阈值判断，此时功率放大器的输入信号为根据未更新的预失真系数进行预失真处理后的信号。需要说明的是，当采数失败计数器大于预设值时，则说明采数异常，此时需要进一步采取措施，具体为：判断数量阈值B是否为初始数量阈值B1。当B≠B1时，使用低一级的数量阈值作为新的数量阈值进行阈值判断，比如设定当前数量阈值是Bq时，将(Bq-Bs)作为新的数量阈值，Bs是数量阈值的变化步长。当B＝B1时，使用低一级的幅度阈值作为新的幅度阈值进行阈值判断。比如设定当前幅度阈值是Ap时，将(Ap-As)作为新的幅度阈值，As是幅度阈值的变化步长。本发明实施例中，采集预失真处理后的信号进行阈值判断，在采集的信号满足设定阈值时用采集的信号更新预失真系数，由于设定阈值也会根据预失真处理后的信号实时调整，故使用调整后的设定阈值对当前采集的预失真处理后的信号进行阈值判断更能反映非线性失真的特性，从而提 升数字预失真处理的性能。
具体实施中，在更新预失真系数之后，根据更新后的预失真系数以及采集的输入信号和采集的输出信号调整设定阈值具体包括以下步骤，如图3所示：
步骤301，根据更新后的预失真系数和采集的输出信号确定拟合的功放输入信号。
步骤302，根据拟合的功放输入信号和采集的输入信号确定拟合误差。
步骤303，根据拟合误差和更新预失真系数后输出信号的邻频泄露比对幅度阈值和数量阈值进行调整。
具体地，在步骤S301中，根据更新后的预失真系数和采集的输出信号确定拟合的功放输入信号符合下述公式(1)；
Figure PCTCN2017117525-appb-000012
其中，
Figure PCTCN2017117525-appb-000013
为拟合的功放输入信号，
Figure PCTCN2017117525-appb-000014
为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度；
在步骤S302中，根据拟合的功放输入信号和采集的输入信号确定载波的拟合误差符合下述公式(2)：
Figure PCTCN2017117525-appb-000015
其中，
Figure PCTCN2017117525-appb-000016
为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
在步骤S303中，根据拟合误差和更新预失真系数后输出信号的邻频泄露比对幅度阈值和数量阈值进行调整具体包括两种方法：
方法一：根据拟合误差和更新预失真系数后输出信号的邻频泄露比确定对消指数，具体符合下述公式(3)：
K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数。
根据对消指数对幅度阈值进行调整，具体符合下述公式(4)：
A p＝A 1+30*K_dpd……………………………(4)
其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
根据对消指数对数量阈值进行调整，具体符合下述公式(5)：
B q＝B 1+K_dpd……………………………(5)
其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。为了更好地介绍方法一中设定阈值调整过程，本发明提供以下具体实施例，设定初始幅度阈值为5000，初始数量阈值为20，预失真时拟合误差是14dBm，信号的功率是34dBm，预失真后邻频泄露比为-46dBc，信号的初始邻频泄露比为-30dBc。加权系数α＝-0.2，加权系数β＝-0.133。根据公式(3)计算得到对消指数K_dpd＝5。然后再通过对消指数K_dpd计算调整后的幅度阈值A p和数量阈值B q。通过公式(4)、(5)计算得到调整后的幅度阈值是5150，调整后的数量阈值是25。那么对下一次采集的输入信号和采集的输出信号进行阈值判断时，幅度阈值是5150，数量阈值是25。
方法二：根据更新预失真系数后输出信号的邻频泄露比调整幅度阈值，具体为：将预失真处理前的信号的邻频泄露比作为初始邻频泄露比，以初始邻频泄露比为起点，每3dBc划分为一个区间，区间左闭右开。同时将0到初始邻频泄露比这段区间并入第一区间。将邻频泄露比的值划分成n个区间C1、C2、C3、…、Cn，每个区间对应一个幅度阈值A1、A2、A3、…An。判断更新预失真系数后输出信号的邻频泄露比所处区间，该区间对应的幅度阈值即为调整后的幅度阈值A p，具体符合下述公式(7)
A p＝A 1+100*(p-1)…………(7)
其中A p为调整后的幅度阈值，A 1为初始幅度阈值，p为更新预失真系数后输出信号的邻频泄露比所处区间所对应的区间数，p是大于0的整数。下一次数据采集后进行阈值判断时，将使用调整后的幅度阈值。
根据拟合误差调整数量阈值，具体为：将拟合误差从0dBc到-30dBc每3dBc划分为一个区间，区间左闭右开，将拟合误差分成m个区间D1、D2、D3、…、Dm，每个区间对应一个数量阈值B1、B2、B3、…、Bm。判断当前拟合误差所处区间，根据当前拟合误差所处区间对应的区间数和初始数量阈值确定调整后的数量阈值B q，具体符合下述公式(8)：
B q＝B 1+q-1……………(8)
其中B q为调整后的数量阈值，B 1为初始数量阈值。q为当前拟合误差所处区间对应的区间数，q是大于0的整数。下一次数据采集后进行阈值判断时，将使用调整后的数量阈值。
为了更好地介绍方法二中设定阈值调整过程，本发明提供以下具体实施例：设定初始幅度阈值为5000，初始数量阈值为20，拟合误差为-20dBc；更新预失真系数后输出信号的邻频泄露比为-46dBc，初始邻频泄露比为-30dBc。以-30dBc为起点，每3dBc划分为一个区间，则-46dBc位于第6个区间，对应得出p＝6，通过公式(7)可以计算出下一次采数的幅度阈值是5500。从0dBc到-30dBc每3dBc划分为一个区间，则拟合误差为-20dBc位于第7个区间，对应得出q＝7，通过公式(8)可以计算出下一次采数的数量阈值为26。下一次数据采集后进行阈值判断时，将使用调整后的幅度阈值和数量阈值。本发明实施例中，在更新预失真系数之后，根据更新后的预失真系数对应调整设定阈值，故在下一次预失真处理以及阈值判断时，更新后的预失真系数和调整后的设定阈值相互配合能更好地解决数字预失真处理中数据特性发生改变的问题。
为了更好的解释本发明实施例，下面通过具体的实施场景描述本发明实施例提供的一种数字预失真处理方法的流程，该流程由数字预失真***执行。如图4所述，包括以下步骤：
步骤S401，接收输入信号N。
步骤S402，将输入信号N降低峰均比后得到信号X。
步骤S403，获取预失真系数a1并根据预失真系数a1对信号X进行预失真处理得到信号Z。
步骤S404，将信号Z输入功率放大器后得到功率输出信号Y。
步骤S405，采集信号Z和信号Y分别得到信号z0和信号y0。
步骤S406，判断信号z0是否满足设定阈值，若是，则执行步骤S407，否则执行步骤S412。
步骤S407，根据信号z0和信号y0将预失真系数a1更新为预失真系数a2。
步骤S408，根据预失真系数a2对信号X进行预失真处理并将处理结果经功率放大器放大后得到信号Y1。
步骤S409，采集信号Y1得到更新预失真系数后功放输出信号y1。
步骤S410，根据预失真系数a2、信号z0和信号y0计算拟合误差。
步骤S411，根据拟合误差和更新预失真系数后功放输出信号y1的邻频泄露比调整设定阈值。
步骤S412，采数失败次数加一。
步骤S413，判断采数失败次数是否大于预设值，若是则执行步骤S414，否则执行步骤S416。
步骤S414，使用低一级的数量阈值或幅度阈值更新设定阈值。
步骤S415，继续采集功率放大器的输入信号和功率放大器的输出信号，使用更新的设定阈值继续进行阈值判断。
步骤S416，继续采集功率放大器的输入信号和功率放大器的输出信号，使用设定阈值继续进行阈值判断。
本发明实施例中采集功率放大器的输入信号和功率放大器的输出信号，确定采集的输入信号满足设定阈值时，使用采集的输入信号和采集的输出信号更新预失真系数和设定阈值，更新后的预失真系数用于下一次预失真处理得到功率放大器的输入信号，更新后的设定阈值用于对下一次采集的输入信 号和采集输出信号进行阈值判断，依次迭代，故预失真系数和设定阈值始终与实时的预失真处理数据相关联，从而能达到更好的预失真处理效果。
基于相同构思，图5示例性的示出了本发明实施例提供的一种数字预失真处理装置的结构，该装置可以执行数字预失真处理的流程。
如图5所示，该装置包括：
采集模块501，用于采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
更新模块502，用于在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；
处理模块503，用于根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；
调整模块504，用于根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
可选地，所述更新模块502还用于：
在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
可选地，所述处理模块503具体用于：
根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；
根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
可选地，所述处理模块503具体用于：
根据下述公式(1)确定拟合的功放输入信号；
所述公式(1)为：
Figure PCTCN2017117525-appb-000017
其中，
Figure PCTCN2017117525-appb-000018
为拟合的功放输入信号，
Figure PCTCN2017117525-appb-000019
为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为 最大记忆深度；
根据下述公式(2)确定载波的拟合误差；
所述公式(2)为：
Figure PCTCN2017117525-appb-000020
其中，
Figure PCTCN2017117525-appb-000021
为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
可选地，所述调整模块504具体用于：
所述设定阈值包括幅度阈值和数量阈值；
根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；
根据所述对消指数对所述幅度阈值和所述数量阈值进行调整。
可选地，所述调整模块504具体用于：
根据下述公式(3)确定对消指数；
所述公式(3)为：
K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
根据下述公式(4)调整所述幅度阈值；
所述公式(4)为：
A p＝A 1+30*K_dpd……………………………(4)
其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
根据下述公式(5)调整所述数量阈值；所述公式(5)为：
B q＝B 1+K_dpd……………………………(5)
其中，B q为调整后的数量阈值，K_dpd为对消指数，A 1为初始数量阈值。
基于相同的技术构思，本发明实施例提供一种数字预失真处理设备。至少一个处理器；以及，与所述至少一个处理器通信连接的存储器；所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行上述实施例中的数字预失真处理方法。
以一个处理器为例，图6为本发明实施例提供的数字预失真处理设备的结构，该数字预失真处理设备600包括：收发器601、处理器602、存储器603和总线***604；
其中，存储器603，用于存放程序。具体地，程序可以包括程序代码，程序代码包括计算机操作指令。存储器603可能为随机存取存储器(random access memory，简称RAM)，也可能为非易失性存储器(non-volatile memory)，例如至少一个磁盘存储器。图中仅示出了一个存储器，当然，存储器也可以根据需要，设置为多个。存储器603也可以是处理器602中的存储器。
存储器603存储了如下的元素，可执行模块或者数据结构，或者它们的子集，或者它们的扩展集：
操作指令：包括各种操作指令，用于实现各种操作。
操作***：包括各种***程序，用于实现各种基础业务以及处理基于硬件的任务。
上述本发明实施例数字预失真处理方法可以应用于处理器602中，或者说由处理器602实现。处理器602可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述数字预失真处理方法的各步骤可以通过处理器602中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器602可以是通用处理器、数字信号处理器(DSP)、专用集成电路(ASIC)、现场可编程门阵列(FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本发明实施例所公开的方法的步骤可以直接体现为硬件译码处 理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器603，处理器602读取存储器603中的信息，结合其硬件执行以下步骤：
所述收发器601，用于采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
所述处理器602，用于在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
所述处理器602还用于在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
所述处理器602，用于根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
所述处理器602，用于根据下述公式(1)确定拟合的功放输入信号；
所述公式(1)为：
Figure PCTCN2017117525-appb-000022
其中，
Figure PCTCN2017117525-appb-000023
为拟合的功放输入信号，
Figure PCTCN2017117525-appb-000024
为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度；
根据下述公式(2)确定载波的拟合误差；
所述公式(2)为：
Figure PCTCN2017117525-appb-000025
其中，
Figure PCTCN2017117525-appb-000026
为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的 采样点数，n大于等于0。
所述处理器602，用于根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；根据所述对消指数对所述幅度阈值和所述数量阈值进行调整，所述设定阈值包括幅度阈值和数量阈值。
所述处理器602，用于根据下述公式(3)确定对消指数；
所述公式(3)为：
K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
根据下述公式(4)调整所述幅度阈值；
所述公式(4)为：
A p＝A 1+30*K_dpd……………………………(4)
其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
根据下述公式(5)调整所述数量阈值；
所述公式(5)为：
B q＝B 1+K_dpd……………………………(5)
其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。
基于相同技术构思，本发明实施例提供了一种非暂态计算机可读存储介质，所述非暂态计算机可读存储介质存储计算机指令，所述计算机指令用于使所述计算机执行上述任一项所述的数字预失真处理方法。
基于相同技术构思，本发明实施例提供了一种计算机程序产品，所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行上述任一项所述的数字预失真处理方法。
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、或计算机 程序产品。因此，本发明可采用完全硬件实施例、完全软件实施例、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、CD-ROM、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(***)、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。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。
显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (15)

  1. 一种数字预失真处理方法，其特征在于，包括：
    采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
    在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；
    根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；
    根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
  2. 如权利要求1所述的方法，其特征在于，还包括：
    在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
  3. 如权利要求1或2所述的方法，其特征在于，所述根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定载波的拟合误差，包括：
    根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；
    根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
  4. 如权利要求3所述的方法，其特征在于，根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号符合下述公式(1)；
    所述公式(1)为：
    Figure PCTCN2017117525-appb-100001
    其中，
    Figure PCTCN2017117525-appb-100002
    为拟合的功放输入信号，
    Figure PCTCN2017117525-appb-100003
    为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为 最大记忆深度；
    根据所述拟合的功放输入信号和所述采集的输入信号确定载波的拟合误差符合下述公式(2)；
    所述公式(2)为：
    Figure PCTCN2017117525-appb-100004
    其中，
    Figure PCTCN2017117525-appb-100005
    为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
  5. 如权利要求3所述的方法，其特征在于，所述设定阈值包括幅度阈值和数量阈值；
    所述根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值，包括：
    根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；
    根据所述对消指数对所述幅度阈值和所述数量阈值进行调整。
  6. 如权利要求5所述的方法，其特征在于，根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数符合下述公式(3)；
    所述公式(3)为：
    K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
    其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
    根据所述对消指数对所述幅度阈值进行调整符合下述公式(4)；
    所述公式(4)为：
    A p＝A 1+30*K_dpd……………………………(4)
    其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
    根据所述对消指数对所述数量阈值进行调整符合下述公式(5)；所述公 式(5)为：
    B q＝B 1+K_dpd……………………………(5)
    其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。
  7. 一种数字预失真处理装置，其特征在于，包括：
    采集模块，用于采集功率放大器的输入信号和功率放大器的输出信号，所述功率放大器的输入信号为预失真处理后的信号；
    更新模块，用于在确定采集的输入信号满足设定阈值时，根据所述采集的输入信号和所述采集的输出信号更新预失真系数；
    处理模块，用于根据更新后的预失真系数、所述采集的输入信号和所述采集的输出信号确定拟合误差；
    调整模块，用于根据所述拟合误差和更新预失真系数后输出信号的邻频泄露比调整所述设定阈值。
  8. 如权利要求7所述的装置，其特征在于，所述更新模块还用于：
    在确定所述采集的输入信号不满足所述设定阈值时，继续采集所述功率放大器的输入信号和所述功率放大器的输出信号。
  9. 如权利要求7或8所述的装置，其特征在于，所述处理模块具体用于：
    根据所述更新后的预失真系数和所述采集的输出信号确定拟合的功放输入信号；
    根据所述拟合的功放输入信号和所述采集的输入信号确定所述拟合误差。
  10. 如权利要求9所述的装置，其特征在于，所述处理模块具体用于：
    根据下述公式(1)确定拟合的功放输入信号；
    所述公式(1)为：
    Figure PCTCN2017117525-appb-100006
    其中，
    Figure PCTCN2017117525-appb-100007
    为拟合的功放输入信号，
    Figure PCTCN2017117525-appb-100008
    为更新后的预失真系数，y(n-l)为采集的输出信号，k为多项式阶数，K为多项式最大阶数，l为记忆深度，L为最大记忆深度；
    根据下述公式(2)确定载波的拟合误差；
    所述公式(2)为：
    Figure PCTCN2017117525-appb-100009
    其中，
    Figure PCTCN2017117525-appb-100010
    为拟合的功放输入信号，z(n)为采集的输入信号，N为信号的采样点数，n大于等于0。
  11. 如权利要求9所述的装置，其特征在于，所述调整模块具体用于：
    所述设定阈值包括幅度阈值和数量阈值；
    根据所述拟合误差和所述更新预失真系数后输出信号的邻频泄露比确定对消指数；
    根据所述对消指数对所述幅度阈值和所述数量阈值进行调整。
  12. 如权利要求11所述的装置，其特征在于，所述调整模块具体用于：
    根据下述公式(3)确定对消指数；
    所述公式(3)为：
    K_dpd＝[α·(C-C 0)+β·(30+10·lg(ε)-Ps)]………………(3)
    其中，K_dpd为对消指数，C为更新预失真系数后输出信号的邻频泄露比，C 0为预失真前的信号的邻频泄露比，ε为拟合误差，Ps为信号的功率，α和β为加权系数；
    根据下述公式(4)调整所述幅度阈值；
    所述公式(4)为：
    A p＝A 1+30*K_dpd……………………………(4)
    其中，A p为调整后的幅度阈值，K_dpd为对消指数，A 1为初始幅度阈值；
    根据下述公式(5)调整所述数量阈值；
    所述公式(5)为：
    B q＝B 1+K_dpd……………………………(5)
    其中，B q为调整后的数量阈值，K_dpd为对消指数，B 1为初始数量阈值。
  13. 一种数字预失真处理设备，其特征在于，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行权利要求1-6任一所述的方法。
  14. 一种非暂态计算机可读存储介质，其特征在于，所述非暂态计算机可读存储介质存储计算机指令，所述计算机指令用于使所述计算机执行权利要求1-6任一所述的方法。
  15. 一种计算机程序产品，所述计算机程序产品包括存储在非暂态计算机可读存储介质上的计算程序，所述计算机程序包括程序指令，当所述程序指令被计算机执行时，使所述计算机执行权利要求1-6任一所述的方法。
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