Feedback-based digital qec correction method for digital array

Abstract

The invention relates to the technical field of qec correction of digital arrays, in particular to a feedback-based digital qec correction method for a digital array, and the method comprises the following steps: S1, constructing a transceiving channel distortion model, and calculating distortion model parameters; s2, constructing a transmitting terminal pre-distortion model according to the distortion model parameters, and performing transmitting terminal qec correction; and S3, constructing a post-distortion model of the receiving end according to the distortion model parameters, and performing qec correction of the receiving end. According to the scheme, the problem of mirror image and direct current correction of the receiving and transmitting end of the digital array antenna is solved digitally, the method does not depend on hardware design and does not need support of an external reference source, mirror image qec correction is carried out by using a digital method based on feedback, error correction of the mirror image and the local oscillator is also realized by the method, and the method is high in precision and good in portability.

Description

Technical Field

[0001] The present invention relates to the technical field of QEC correction of digital arrays, and more particularly to a feedback-based digital QEC correction method for digital arrays. Background Art

[0002] Digital array antennas are commonly used in satellite communications. Serving as satellite antennas for communication with ground stations or mobile phones, they are a crucial component of satellite payloads and have a significant impact on the entire satellite communications system. Digital multi-beamforming is a key technology in satellite communications systems. Accurate beamforming requires high RF channel quality. However, errors introduced by hardware non-idealities, time-varying environments, and structural complexity within the array's RF channels degrade channel quality. The resulting IQ imbalance, which can cause image errors and local oscillator leakage in the transmit and receive channels, is a key issue that needs to be addressed.

[0003] Traditional methods rely on hardware circuit design to address IQ imbalance. This approach places high demands on the hardware circuitry, resulting in higher costs and poor product updateability. Another approach, active correction, relies on a known reference source (such as a calibration signal or spectrum analyzer). However, this requires additional hardware and cannot be updated in real time. It is only suitable for static error environments and is clearly unsuitable for satellites in orbit.

[0004] The present invention proposes a solution for multi-channel QEC correction of digital array antennas that is independent of hardware design and does not require the support of an external reference source. It uses a feedback-based digital method for mirror QEC correction. This method also achieves error correction of the mirror and local oscillator with high accuracy and good portability. Summary of the Invention

[0005] The present invention aims to overcome at least one defect (shortcoming) of the above-mentioned prior art and provide a feedback-based digital QEC correction method for digital arrays, which is used to digitally solve the problems of image and DC correction at the transmitting and receiving ends of digital array antennas.

[0006] The technical solution adopted by the present invention is a method for digital QEC correction based on feedback for a digital array, the method comprising the following steps: S1: Build a distortion model for the transmit and receive channels and calculate the distortion model parameters; S2: Construct a transmitter pre-distortion model based on the distortion model parameters and perform transmitter QEC correction; S3: Construct a post-distortion model at the receiving end based on the distortion model parameters and perform QEC correction at the receiving end.

[0007] This proposed feedback-based digital QEC correction method accurately describes the sources of error in the system by constructing a distortion model of the transmit and receive channels and calculating the distortion model parameters, providing a theoretical basis for subsequent correction. This method first performs QEC correction on the transmitter side by constructing a pre-distortion model to eliminate image errors and local oscillator leakage caused by IQ imbalance, ensuring signal quality. It then performs correction on the receiver side by constructing a post-distortion model to restore the authenticity of the received signal and minimize the impact of errors. This method is independent of hardware design and external reference sources, and utilizes a feedback mechanism to achieve real-time correction, adapting to dynamic environmental changes. This high-precision digital correction not only improves system performance but also offers good portability, adaptability to different platforms and environments, and low system complexity and cost, making it widely applicable in fields such as satellite communication systems.

[0008] Preferably, in step S1, the construction of the transceiver channel distortion model includes: at the transmitting end or the receiving end, the time domain signal Input into the distortion model to get , wherein the function formula of the distortion model is:

[0009] in, is the channel transfer function; is the mirror transfer function; is the channel delay; when is the mirror delay, For direct current; is the time domain signal sequence representation of the transmitter; is the independent variable of the time domain series x.

[0010] This application captures signal distortion caused by factors such as channel attenuation, image effects, and DC offset during transmission, providing precise error modeling. This provides a theoretical basis for subsequent QEC correction, achieving high-precision distortion modeling that can adapt to signal changes in different environments in real time, enhancing the stability and reliability of correction. Furthermore, mathematical modeling reduces reliance on external hardware, lowers system complexity and cost, and improves adaptability and scalability.

[0011] Preferably, in step S1, calculating the distortion model parameters includes: S11: Calculate DC by averaging ,in ; S12: Perform a circular shift Then, take multiple shifted versions and Perform correlation calculations and find the delay at the maximum correlation as the channel delay , where the relevant calculation formula is: ; S13: Delay Then get the delayed time domain signal , and then use the LS algorithm to calculate the channel transfer function , Contains the amplitude and phase information of the channel; S14: After calculating the channel delay and channel transfer function, according to the mutual non-correlation characteristics of the image signal, first subtract the system function of the signal in the calculated image to obtain the image after the distortion model ,in, ; S15: Circular shift of the mirror item Get multiple delayed versions and perform correlation calculations with the mirror images after the distortion model to get the mirror delay , and then use the LS algorithm to get the mirror transfer function .

[0012] By gradually calculating the DC component, channel delay, channel transfer function, image signal, and image transfer function, accurate modeling of signal distortion is effectively achieved. Each calculation step improves the accuracy of signal processing, enabling comprehensive and accurate correction of various distortion factors during signal transmission, thereby providing high-precision support for subsequent error correction and signal recovery.

[0013] Preferably, in step S13, the LS algorithm formula is: ; The calculation formula is: .

[0014] In this step, the channel transfer function is calculated using a least-squares algorithm, enabling precise estimation of the channel's amplitude and phase information. This algorithm effectively extracts channel characteristics by minimizing the sum of squared signal errors. It exhibits strong noise immunity and can accurately estimate the transfer function even when the signal is subject to noise. The matrix operation form of the LS algorithm offers high computational efficiency, making it suitable for real-time signal processing. It avoids complex nonlinear optimization calculations, thereby improving processing speed and simplicity. By accurately calculating the channel transfer function, distorted signals can be effectively restored, enhancing overall system performance and stability.

[0015] Preferably, the step S2 includes: S21: The original signal in the transmitted time domain is obtained through the predistortion model ; S22: What you will get Obtained through the distortion model ,in ; S23: According to and Solve the image coefficient of the predistortion model and the predistortion model DC correction term ; S24: According to the solution and The input signal is subjected to transmit pre-distortion processing, and then processed by the distortion model of the transmit channel to obtain a signal output with the image and local oscillation removed.

[0016] By gradually implementing signal pre-distortion and distortion correction, we ensure that after the signal passes through the distortion model, image and local oscillator interference can be effectively removed, resulting in a clearer and more realistic signal output. The optimization and correction of each step enables pre-distortion processing to more accurately adapt to different signal characteristics, thereby improving the signal transmission quality and stability of the entire system.

[0017] Preferably, in step S21, the predistortion model formula is:

[0018] in, Indicates mirror correction; is the convolution symbol; Represents a mirror item.

[0019] The predistortion model eliminates image interference through convolution operation and performs fine adjustment in combination with DC correction terms, thereby effectively optimizing signal quality, reducing errors, and improving the accuracy and robustness of signal processing.

[0020] Preferably, the step S23 includes: bringing the predistortion model formula into Then, we can extract the mirror image term and solve it to get , then extract the DC term and take its conjugate to solve for .

[0021] By accurately extracting and solving the image term and DC term, the interference components in the signal can be effectively eliminated, and by optimizing the parameters and , improving the signal quality and processing accuracy. This process ensures the accuracy of subsequent signal processing and enhances the robustness and reliability of the system.

[0022] Preferably, the step S3 includes: S31: The original signal in the transmission time domain is obtained through the distortion model ,in, ; S32: What you will get After the distortion model, we get ,in, ; S33: According to and Solve to get the mirror coefficient of the post-distortion model , then according to Solve the DC correction term of the post-distortion model ; S34: Using the solution and ,according to Formula, the received signal is received and then distorted to obtain a signal with the image and local oscillation removed.

[0023] Through precise distortion modeling, post-distortion processing, and correction, image and local oscillator interference in the time domain signal is eliminated, optimizing signal quality and accuracy. This not only improves the accuracy of signal recovery but also ensures that the signal processing system can operate stably under complex interference conditions.

[0024] Preferably, step S33 includes: Bring in Then extract its mirror image and set it to 0, so as to obtain , then according to Solve .

[0025] By accurately removing the image term and solving the image correction coefficient and DC correction term in this step, the signal quality is significantly improved, the interference component is eliminated, and the signal recovery process is made more accurate and reliable.

[0026] Preferably, the function formula for extracting the mirror item and setting it to 0 is:

[0027] Thus, according to the above formula, we can obtain ; Then, we solve for the DC term , ,in represents the DC mirror image.

[0028] By precisely extracting the image terms and setting them to zero, and then solving for the image correction coefficients and DC terms, the entire signal recovery process is significantly optimized. This method effectively removes interference from the signal, ensuring accurate recovery of both the spectrum and the DC portion of the signal, ultimately improving the robustness, stability, and accuracy of the signal processing system.

[0029] Compared with the prior art, the present invention has the following beneficial effects: This paper proposes a QEC correction scheme for digital array antennas based on digital feedback, digitally resolving the issues of image and DC correction at the transmit and receive ends of digital array antennas. This solution is independent of hardware design and does not require an external reference source. It offers high portability and precision, effectively eliminating interference and distortion in signals, improving signal quality and recovery accuracy, and ensuring efficient and stable system operation in changing environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The present invention provides a flow chart of the method.

[0031] Figure 2 This is a schematic diagram of the distortion model provided by the present invention.

[0032] Figure 3 This is a schematic diagram of channel parameter calculation provided by the present invention.

[0033] Figure 4 This is a schematic diagram of the transmitter predistortion model provided by the present invention.

[0034] Figure 5 This is a schematic diagram of the post-distortion model at the receiving end provided by the present invention.

[0035] Figure 6 This is a schematic diagram of the simulation results provided by the present invention.

[0036] Figure 7 This is a schematic diagram of the system structure provided by the present invention. DETAILED DESCRIPTION

[0037] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting the present invention. To better illustrate the following embodiments, some components in the accompanying drawings may be omitted, enlarged, or reduced in size, and do not represent actual product dimensions. Those skilled in the art will appreciate that some well-known structures and their descriptions may be omitted from the accompanying drawings.

[0038] Example 1 like Figure 1 As shown, this embodiment provides a method for feedback-based digital QEC correction for a digital array, the method comprising the following steps: Step S1: Construct a distortion model of the transmitting and receiving channels and calculate the distortion model parameters; Preferably, in step S1, Figure 2 As shown, the construction of the transceiver channel distortion model includes: at the transmitting end or the receiving end, the time domain signal Input into the distortion model to get , wherein the function formula of the distortion model is:

[0039] in, is the channel transfer function; is the mirror transfer function; is the channel delay; when is the mirror delay, For direct current; is the time domain signal sequence representation of the transmitter; is the independent variable of the time domain series x.

[0040] More preferably, Figure 3 As shown, in step S1, the calculation of the distortion model parameters includes: Step S11: Calculate DC by averaging ,in ; Step S12: Perform a circular shift Then, take multiple shifted versions and Perform correlation calculations and find the delay at the maximum correlation as the channel delay , where the relevant calculation formula is: ; Step S13: Delay Then get the delayed time domain signal , and then use the LS algorithm to calculate the channel transfer function , Contains the amplitude and phase information of the channel; Further preferably, in step S13, the LS algorithm formula is: ; The calculation formula is: ,in, Contains the amplitude and phase information of the channel, represents the conjugate transpose.

[0041] Step S14: After calculating the channel delay and channel transfer function, according to the mutual non-correlation characteristics of the mirror signal, first subtract the system function of the signal in the calculated mirror image to obtain the mirror image after the distortion model. ,in, ; Step S15: cyclically shift the mirror item Get multiple delayed versions and perform correlation calculations with the mirror images after the distortion model to get the mirror delay , and then use the LS algorithm to get the mirror transfer function .

[0042] By gradually calculating the DC component, channel delay, channel transfer function, image signal, and image transfer function, accurate modeling of signal distortion is effectively achieved. Each calculation step improves the accuracy of signal processing, enabling comprehensive and accurate correction of various distortion factors during signal transmission, thereby providing high-precision support for subsequent error correction and signal recovery.

[0043] Step S2: Construct the transmitter pre-distortion model according to the distortion model parameters and perform transmitter QEC correction, such as Figure 4 As shown, is the original signal in the transmitting time domain, is a predistortion signal at the transmitting end, wherein the predistortion model is a qec compensation model; Preferably, the step S2 includes: Step S21: The original signal in the transmission time domain is obtained through the predistortion model ; Preferably, in step S21, the predistortion model formula is:

[0044] in, Indicates mirror correction; is the convolution symbol; Represents a mirror item.

[0045] Step S22: The obtained Obtained through the distortion model ,in ; Step S23: According to and Solve the image coefficient of the predistortion model and the predistortion model DC correction term ; Further preferably, the step S23 includes: bringing the predistortion model formula into Then, we can extract the mirror image term and solve it to get , then extract the DC term and take its conjugate to solve for .

[0046] Specifically include: Substitute the predistortion model formula into From the formula, we can get:

[0047]

[0048] Then we extract the mirror term and solve it. :

[0049] Then extract the DC term to obtain the following formula:

[0050] Taking the conjugate of the above formula gives:

[0051] Then write the formula obtained by extracting the DC term and taking the conjugate into matrix form to obtain the DC correction term ,

[0052] Step S24: According to the solution and The input signal is subjected to transmit pre-distortion processing, and then processed by the distortion model of the transmit channel to obtain a signal output with the image and local oscillation removed.

[0053] By gradually implementing signal pre-distortion and distortion correction, we ensure that after the signal passes through the distortion model, image and local oscillator interference are effectively removed, resulting in a clearer and more realistic signal output. The optimization and correction of each step enables pre-distortion processing to more accurately adapt to different signal characteristics, thereby improving the signal transmission quality and stability of the entire system.

[0054] Step S3: Figure 5 As shown, the post-distortion model of the receiving end is constructed according to the distortion model parameters, and the QEC correction of the receiving end is performed. x(n) is the original signal in the transmission time domain. is the receiving end signal, is a post-distortion signal at the receiving end, wherein the post-distortion model is a qec compensation model.

[0055] Preferably, the step S3 includes: Step S31: The original signal in the transmission time domain is obtained through the distortion model ,in, ; Step S32: The obtained After the distortion model, we get ,in, ; Step S33: According to and Solve to get the mirror coefficient of the post-distortion model , then according to Solve the DC correction term of the post-distortion model ; More preferably, step S33 includes: Bring in Then extract its mirror image and set it to 0, so as to obtain , then according to Solve .

[0056] Specifically, Bring in You can get:

[0057] Then extract the mirror item and set it to 0:

[0058] Thus, according to the above formula, we can obtain ; Then, we can solve the DC term to get , ,in represents the DC mirror image.

[0059] Step S34: Using the obtained and ,according to Formula, the received signal is received and then distorted to obtain a signal with the image and local oscillation removed.

[0060] By precisely extracting the image term and setting it to zero, and then solving for the image correction coefficient and DC term, the entire signal recovery process is greatly optimized. This method effectively removes interference from the signal, ensuring accurate recovery of both the spectrum and the DC portion of the signal, ultimately improving the robustness, stability, and accuracy of the signal processing system.

[0061] Specifically, first, in this embodiment, a pair of standard transceiver ADDAs after external calibration is required; For the transmit calibration solution, a test signal (a ZC sequence with good autocorrelation can be used as the loading sequence) is serially transmitted from each transmitter to be calibrated. A standard receiver connected to the RF line receives the digital signal. The transmit channel parameters are calculated according to the solution and then applied to the transmit predistortion model to construct transmit QEC and DC calibration. Subsequent transmission of an in-band single-tone signal verifies that QEC and DC correction are effective under the predistortion model. For the receive calibration solution, a standard transmitter transmits a test signal (a ZC signal can also be used). The receive channels to be calibrated are then connected to the RF line to receive the sampled digital signal. The parameters of each receive channel are calculated using the aforementioned scheme and then incorporated into the post-receive distortion model to construct the receive QEC and DC calibration. After the post-receive distortion model is constructed, the effectiveness of the QEC and DC calibration can be verified.

[0062] The results obtained by simulating using simulation software according to the method described in this embodiment are as follows: Figure 6 As shown, the transmitted signal uses a multi-carrier signal, where the signal appears every other tick, making it possible to intuitively decompose the signal and image classification, set the distortion channel, add delay, image, DC and other models, and obtain the spectrum of the received signal y. Figure 6 From the transmit signal spectrum x in the upper left figure and the receive signal spectrum y in the upper right figure, the image suppression becomes 17dB, while the DC suppression is 27dB. The simulation results of pre-distortion and post-distortion are obtained using the above scheme, as shown in the figure below. Figure 6 The results on the lower left and lower right show that both schemes can significantly improve the channel's image and DC suppression, with suppression ratios exceeding 50dB.

[0063] The feedback-based digital QEC correction method proposed in this embodiment accurately describes the sources of error in the system by constructing a distortion model of the transmit and receive channels and calculating the distortion model parameters, providing a theoretical basis for subsequent correction. This method first performs QEC correction at the transmitter by constructing a pre-distortion model to eliminate image errors and local oscillator leakage caused by IQ imbalance, ensuring signal quality. It then performs correction at the receiver by constructing a post-distortion model to restore the authenticity of the received signal and reduce the impact of errors. This method is independent of hardware design and external reference sources, and utilizes a feedback mechanism to achieve real-time correction, adapting to dynamic environmental changes. This high-precision digital correction not only improves system performance but also offers good portability, adaptability to different platforms and environments, and low system complexity and cost, making it widely applicable in fields such as satellite communication systems.

[0064] Example 2 like Figure 7 As shown, according to the method described in embodiment 1, this embodiment provides a system for feedback-based digital QEC correction of a digital array, the system comprising: Parameter calculation module, used to build a distortion model of the transmitting and receiving channels and calculate the distortion model parameters; The transmitter QEC correction module is used to build a transmitter pre-distortion model based on the distortion model parameters and perform transmitter QEC correction; The receiving end QEC correction module is used to construct the receiving end post-distortion model according to the distortion model parameters and perform receiving end QEC correction.

[0065] Therefore, in this system, by constructing a distortion model of the transmit and receive channels and calculating the distortion model parameters, the error sources in the system are accurately described, providing a theoretical basis for subsequent corrections. First, the QEC correction module at the transmitter side performs QEC correction by constructing a pre-distortion model to eliminate the image error and local oscillator leakage caused by IQ imbalance and ensure signal quality. Then, the QEC correction module at the receiver side performs correction by constructing a post-distortion model to restore the authenticity of the received signal and reduce the impact of errors. The system described in this embodiment does not rely on hardware design or external reference sources, but uses a feedback mechanism to achieve real-time correction and adapt to dynamic environmental changes. Through high-precision digital correction, not only is the system performance improved, but it also has good portability, adapts to different platforms and environments, has low system complexity and cost, and is widely applicable to fields such as satellite communication systems.

[0066] Preferably, the parameter calculation module includes: The distortion function calculation unit is used to convert the time domain signal into Input into the distortion model to calculate ; Among them, the function formula of the distortion model is:

[0067] in, is the channel transfer function; is the mirror transfer function; is the channel delay; when is the mirror delay, For direct current; is the time domain signal sequence representation of the transmitter; is the independent variable of the time domain series x.

[0068] This unit captures signal distortion during transmission due to factors such as channel attenuation, image effects, and DC offset, providing precise error modeling. This provides a theoretical basis for subsequent QEC correction, achieving high-precision distortion modeling that adapts to signal changes in different environments in real time, enhancing the stability and reliability of correction. Furthermore, mathematical modeling reduces reliance on external hardware, lowers system complexity and cost, and improves adaptability and scalability.

[0069] Further preferably, the parameter calculation module further includes: A distortion model parameter calculation unit, used to calculate relevant parameters of the distortion model; Specifically include: Calculate DC by averaging ,in ; Will Perform a circular shift Then, take multiple shifted versions and Perform correlation calculations and find the delay at the maximum correlation as the channel delay , where the relevant calculation formula is: ; Will Delay Then get the delayed time domain signal , and then use the LS algorithm to calculate the channel transfer function , Contains the amplitude and phase information of the channel; wherein the LS algorithm formula is: ; The calculation formula is: .

[0070] By using the least squares algorithm to calculate the channel transfer function, the channel's amplitude and phase information can be accurately estimated. This algorithm effectively extracts channel characteristics by minimizing the sum of squared signal errors. It exhibits strong noise immunity and can accurately estimate the transfer function even when the signal is subject to noise. The matrix operation form of the LS algorithm is highly computationally efficient and suitable for real-time signal processing. It avoids complex nonlinear optimization calculations, thereby improving processing speed and simplicity. By accurately calculating the channel transfer function, distorted signals can be effectively restored, improving overall system performance and stability.

[0071] After calculating the channel delay and channel transfer function, according to the mutual non-correlation characteristics of the image signal, the system function of the signal in the calculated image is first subtracted to obtain the image after the distortion model. ,in, ; Circular shift of the mirror item Get multiple delayed versions and perform correlation calculations with the mirror images after the distortion model to get the mirror delay , and then use the LS algorithm to get the mirror transfer function .

[0072] This unit effectively and accurately models signal distortion by gradually calculating the DC component, channel delay, channel transfer function, image signal, and image transfer function. Each calculation step improves signal processing accuracy, enabling comprehensive and accurate correction of various distortion factors during signal transmission, thus providing high-precision support for subsequent error correction and signal recovery.

[0073] Preferably, the transmitting end qec correction module includes: A predistortion model parameter processing unit, used to generate a predistortion model mirror coefficient and a predistortion model DC correction term; Specifically include: the original signal in the transmission time domain is obtained through the predistortion model , the predistortion model formula is:

[0074] in, Indicates mirror correction; is the convolution symbol; Represents a mirror item; Will get Obtained through the distortion model ,in ; according to and Solve the image coefficient of the predistortion model and the predistortion model DC correction term , specifically: Substitute the predistortion model formula into Then, we can extract the mirror image term and solve it to get , then extract the DC term and take its conjugate to solve for .

[0075] The transmitter correction unit is used to perform transmit predistortion processing on the input signal according to the predistortion model image coefficient and the predistortion model DC correction term, and then process the input signal through the distortion model of the transmit channel to obtain a signal output with the image and local oscillation removed.

[0076] By gradually implementing signal pre-distortion and distortion correction, we ensure that after the signal passes through the distortion model, image and local oscillator interference are effectively removed, resulting in a clearer and more realistic signal output. The optimization and correction of each step enables pre-distortion processing to more accurately adapt to different signal characteristics, thereby improving the signal transmission quality and stability of the entire system.

[0077] Preferably, the receiving end qec correction module includes: A post-distortion model parameter calculation unit, used for calculating the post-distortion model mirror coefficient and the post-distortion model DC correction term; Specifically include: The original signal in the time domain is obtained by the distortion model ,in, ; Will get After the distortion model, we get ,in, ; according to and Solve to get the mirror coefficient of the post-distortion model , then according to Solve the DC correction term of the post-distortion model Specifically, by Bring in Then extract its mirror image and set it to 0, so as to obtain , then according to Solve The function formula for extracting the mirror image item and setting it to 0 is:

[0078] Thus, according to the above formula, we can obtain ; Then, we solve for the DC term , ,in represents the DC mirror image.

[0079] By precisely extracting the image term and setting it to zero, and then solving for the image correction coefficient and DC term, the entire signal recovery process is greatly optimized. This method effectively removes interference from the signal, ensuring accurate recovery of both the spectrum and the DC portion of the signal, ultimately improving the robustness, stability, and accuracy of the signal processing system.

[0080] The receiving end correction unit is used to obtain the and , and according to Formula, the received signal is received and then distorted to obtain a signal with the image and local oscillation removed.

[0081] Through precise distortion modeling, post-distortion processing, and correction, image and local oscillator interference in the time domain signal is eliminated, optimizing signal quality and accuracy. This not only improves the accuracy of signal recovery but also ensures that the signal processing system can operate stably under complex interference conditions.

[0082] The system for feedback-based digital QEC correction for a digital array provided in an embodiment of the present solution is used to execute the above-mentioned method for feedback-based digital QEC correction for a digital array in the present solution. Its implementation method is consistent with the implementation method of the method for feedback-based digital QEC correction for a digital array provided in the present solution, and can achieve the same beneficial effects, which will not be repeated here.

[0083] This system for feedback-based digital QEC correction for a digital array is used in the feedback-based digital QEC correction method for a digital array in the aforementioned embodiments. Therefore, the descriptions and definitions of the feedback-based digital QEC correction method for a digital array in the aforementioned embodiments can be used to understand the various execution modules in the embodiments of this solution.

[0084] Obviously, the above embodiments of the present invention are merely examples for the purpose of clearly illustrating the technical solutions of the present invention, and are not intended to limit the specific implementation methods of the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the claims of the present invention shall be included within the scope of protection of the claims of the present invention.

Claims

1. A method for feedback-based digital QEC correction of a digital array, characterized in that: The method comprises the following steps: S1: Build a distortion model for the transmit and receive channels and calculate the distortion model parameters; S2: Construct a transmitter pre-distortion model based on the distortion model parameters and perform transmitter QEC correction; S3: Construct a post-distortion model at the receiving end based on the distortion model parameters and perform QEC correction at the receiving end.

2. The method for feedback-based digital QEC correction for a digital array according to claim 1, characterized in that: In step S1, the construction of the transceiver channel distortion model includes: at the transmitting end or the receiving end, the time domain signal Input into the distortion model to get , wherein the function formula of the distortion model is: in, is the channel transfer function; is the mirror transfer function; is the channel delay; when is the mirror delay, For direct current; is the time domain signal sequence representation of the transmitter; is the independent variable of the time domain series x.

3. The method for feedback-based digital QEC correction for a digital array according to claim 2, characterized in that: In step S1, the calculation of distortion model parameters includes: S11: Calculate DC by averaging ,in ; S12: Perform a circular shift Then, take multiple shifted versions and Perform correlation calculations and find the delay at the maximum correlation as the channel delay , where the relevant calculation formula is: ; S13: Delay Then get the delayed time domain signal , and then use the LS algorithm to calculate the channel transfer function , Contains the amplitude and phase information of the channel; S14: After calculating the channel delay and channel transfer function, according to the mutual non-correlation characteristics of the image signal, first subtract the system function of the signal in the calculated image to obtain the image after the distortion model ,in, ; S15: Circular shift of the mirror item Get multiple delayed versions and perform correlation calculations with the mirror images after the distortion model to get the mirror delay , and then use the LS algorithm to get the mirror transfer function .

4. The method for feedback-based digital QEC correction for a digital array according to claim 3, characterized in that: In step S13, the LS algorithm formula is: ; The calculation formula is: .

5. The method for feedback-based digital QEC correction for a digital array according to claim 4, characterized in that: In the step S2, it includes: S21: The original signal in the transmitted time domain is obtained through the predistortion model ; S22: What you will get Obtained through the distortion model ,in ; S23: According to and Solve the image coefficient of the predistortion model and the predistortion model DC correction term ; S24: According to the solution and The input signal is subjected to transmit pre-distortion processing, and then processed by the distortion model of the transmit channel to obtain a signal output with the image and local oscillation removed.

6. The method for feedback-based digital QEC correction for a digital array according to claim 5, characterized in that: In step S21, the predistortion model formula is: in, Indicates mirror correction; is the convolution symbol; Represents a mirror item.

7. The method for feedback-based digital QEC correction for a digital array according to claim 6, characterized in that: The step S23 includes: bringing the predistortion model formula into Then, we can extract the mirror image term and solve it to get , then extract the DC term and take its conjugate to solve for .

8. The method for feedback-based digital QEC correction for a digital array according to claim 4, characterized in that: The step S3 includes: S31: The original signal in the transmission time domain is obtained through the distortion model ,in, ； S32: What you will get After the distortion model, we get ,in, ； S33: According to and Solve to get the mirror coefficient of the post-distortion model , then according to Solve the DC correction term of the post-distortion model ; S34: Using the solution and ,according to Formula, the received signal is received and then distorted to obtain a signal with the image and local oscillation removed.

9. The method for feedback-based digital QEC correction for a digital array according to claim 8, characterized in that: In step S33, the following steps are included: Bring in Then extract its mirror image and set it to 0, so as to obtain , then according to Solve .

10. The method for feedback-based digital QEC correction for a digital array according to claim 9, characterized in that: The function formula for extracting the mirror item and setting it to 0 is: Thus, according to the above formula, we can obtain ; Then, we solve for the DC term , ,in represents the DC mirror image.

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