Vector signal recovery method, device, equipment, medium and product

Abstract

The present application relates to the field of optical fiber communications, and in particular to a vector signal recovery method, apparatus, device, medium, and product. The method comprises: performing serial-to-parallel conversion and data segmentation on an input signal; for each data block, performing Fourier transform and equalization processing on the data block transformed into the frequency domain in combination with its corresponding tap vector to compensate for damage in the link, and inverse Fourier transforming the equalized data block into the time domain, and performing principal component analysis on the transformed first signal to extract phase noise based on principal component information corresponding to the data block. To avoid the influence of equalization-enhanced phase noise, phase compensation is performed on the first signal of the data block based on the phase noise corresponding to the data block to obtain a recovered signal to eliminate inter-symbol crosstalk, and carrier phase recovery is performed simultaneously. While equalizing the signal, the phase error of the signal is also compensated, thereby reducing the influence of equalization-enhanced phase noise.

Description

Technical Field

[0001] The present application relates to the field of optical fiber communications, and in particular to a vector signal recovery method, apparatus, device, medium, and product. Background Art

[0002] With the continuous advancement of mobile communication technology, signal processing technology has become the key to ensuring communication quality.

[0003] Signals must pass through a variety of complex transmission environments and processing processes. Frequency-domain equalization algorithms play an increasingly important role in signal processing. Adaptive equalizers are often used to compensate for inter-symbol interference (ISI). The computational complexity of time-domain equalizers increases rapidly with the number of taps, yet this is essential for high-baud-rate transmission systems. Frequency-domain equalization algorithms perform signal recovery. In frequency-domain equalizers, the highly complex convolution in the time domain is replaced by a direct Hadamard product in the frequency domain. Frequency-domain equalization algorithms have lower computational complexity and better convergence, and they require fewer hardware resources.

[0004] However, in real-world scenarios, signals are often subject to various interferences, which can cause noise to be present in the input signal of the frequency domain equalization algorithm. During the frequency domain equalization operation, this noise may be enhanced, further affecting the signal performance.

[0005] Therefore, how to improve the accuracy of signal processing and make the signal performance more excellent is a technical problem that technicians in this field urgently need to solve. Summary of the Invention

[0006] The purpose of this application is to provide a vector signal recovery method, device, equipment, medium and product that can improve the accuracy of signal processing and make the signal performance better.

[0007] In a first aspect, a vector signal recovery method is provided, comprising:

[0008] Perform serial-to-parallel conversion and data block division on the input signal to obtain multiple data blocks;

[0009] According to a target data block and a tap vector corresponding to the target data block, Fourier transform, equalization processing, and inverse Fourier transform are sequentially performed to obtain a first signal corresponding to the target data block; the target data block is any one of the multiple data blocks;

[0010] performing principal component analysis on the target data block according to the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block;

[0011] estimating the phase noise corresponding to the target data block according to the second principal component information corresponding to the target data block;

[0012] The first signal corresponding to the target data block is compensated according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain restored signals corresponding to each of the multiple data blocks.

[0013] In a preferred example, the present application may be further configured as follows: performing Fourier transform, equalization processing, and inverse Fourier transform in sequence according to the target data block and the tap vector corresponding to the target data block to obtain the first signal corresponding to the target data block, including:

[0014] Performing Fourier transform according to the target data block and an overlapping storage method to obtain a second signal corresponding to the target data block;

[0015] performing a Hadamard product operation on the second signal corresponding to the target data block and a frequency domain tap vector corresponding to the target data block to facilitate equalization processing, to obtain a third signal, wherein the frequency domain tap vector is obtained by performing Fourier transform on the tap vector;

[0016] Perform an inverse Fourier transform on the third signal to obtain a first signal corresponding to the target data block.

[0017] In a preferred example, the present application may be further configured as follows: before sequentially performing Fourier transform, equalization processing, and inverse Fourier transform according to the target data block and the tap vector corresponding to the target data block to obtain the first signal corresponding to the target data block, the present application may further include:

[0018] Determining a judgment output of a recovery signal according to a recovery signal corresponding to a previous data block of the target data block;

[0019] Determine the time domain error signal corresponding to the previous data block based on the recovered signal and the judgment output corresponding to the previous data block;

[0020] Performing Fourier transform on the time domain error signal corresponding to the previous data block to obtain the frequency domain error signal corresponding to the previous data block;

[0021] Performing an inverse Fourier transform on the frequency domain error signal corresponding to the previous data block and the second signal corresponding to the previous data block to determine the gradient information corresponding to the previous data block;

[0022] The tap vector corresponding to the previous data block is updated according to the gradient information corresponding to the previous data block to obtain the tap vector corresponding to the target data block.

[0023] In a preferred example, the present application may be further configured as follows: performing principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block includes:

[0024] Performing covariance calculation based on the real part and the imaginary part of the first signal corresponding to the target data block to obtain a covariance matrix corresponding to the target data block;

[0025] Second principal component information corresponding to the target data block is determined according to a covariance matrix corresponding to the target data block and first principal component information of a previous data block corresponding to the target data block.

[0026] In a preferred example, the present application may be further configured as follows: if the target data block is the first data block, the first principal component information of the previous data block is the preset principal component information;

[0027] The determining, based on the covariance matrix corresponding to the target data block and the first principal component information of a previous data block corresponding to the target data block, second principal component information corresponding to the target data block includes:

[0028] Determining initial second principal component information according to the covariance matrix corresponding to the first data block and preset principal component information;

[0029] Using the initial second principal component information as new preset principal component information, repeatedly performing the step of determining the initial second principal component information based on the covariance matrix corresponding to the first data block and the preset principal component information until a preset condition is met, thereby obtaining the second principal component information corresponding to the target data block;

[0030] The preset conditions include: the number of repetitions reaches a preset threshold or a stop instruction is received.

[0031] In a preferred example, the present application may be further configured to include:

[0032] Performing parallel-to-serial conversion on the recovered signals corresponding to the multiple data blocks to obtain sub-signals corresponding to the multiple data blocks;

[0033] The sub-signals corresponding to the multiple data blocks are combined to obtain a processed signal.

[0034] In a second aspect, a signal recovery device is provided, comprising:

[0035] A block module is used to perform serial-to-parallel conversion and data block division on the input signal to obtain multiple data blocks;

[0036] a transform module, configured to perform Fourier transform, equalization processing, and inverse Fourier transform in sequence according to a target data block and a tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block; the target data block is any one of the multiple data blocks;

[0037] a principal component analysis module, configured to perform principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block, to obtain second principal component information corresponding to the target data block;

[0038] a phase noise estimation module, configured to estimate the phase noise corresponding to the target data block based on the second principal component information corresponding to the target data block;

[0039] The compensation module is used to compensate the first signal corresponding to the target data block according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain a restored signal corresponding to each of the multiple data blocks.

[0040] In a third aspect, a vector signal recovery device is provided, comprising:

[0041] one or more processors;

[0042] Memory;

[0043] One or more applications, wherein the one or more applications are stored in a memory and configured to be executed by one or more processors, and the one or more programs are configured to: perform operations corresponding to the vector signal recovery method shown in any possible implementation manner of the first aspect.

[0044] In a fourth aspect, a computer-readable storage medium is provided, wherein the storage medium stores at least one instruction, at least one program, code set, or instruction set, and the at least one instruction, at least one program, code set, or instruction set is loaded by a processor and executes the steps of the vector signal recovery method shown in any possible implementation of the first aspect.

[0045] In a fifth aspect, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements operations corresponding to the vector signal recovery method shown in any possible implementation manner in the first aspect.

[0046] In summary, the vector signal recovery method provided by this application has the following beneficial technical effects:

[0047] Perform serial-to-parallel conversion and data segmentation on the input signal to obtain multiple data blocks; perform Fourier transform, equalization processing, and inverse Fourier transform in sequence according to the target data block and the tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block; the target data block is any data block among the multiple data blocks; perform principal component analysis on the target data block according to the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block; estimate the phase noise corresponding to the target data block according to the second principal component information corresponding to the target data block; compensate the first signal corresponding to the target data block according to the phase noise corresponding to the target data block to obtain a recovery signal corresponding to the target data block, so as to obtain recovery signals corresponding to each of the multiple data blocks.

[0048] In this scheme, the input signal is converted from serial to parallel and the data is divided into blocks; for each data block, the data block transformed into the frequency domain is Fourier transformed and equalized in combination with its corresponding tap vector to compensate for damage in the link, and the equalized data block is inversely Fourier transformed into the time domain, and the principal component analysis is performed on the transformed first signal to facilitate phase noise extraction based on the principal component information corresponding to the data block. To avoid the influence of the phase noise enhanced by equalization, the first signal of the data block is phase compensated according to the phase noise corresponding to the data block to obtain a recovered signal, so as to eliminate inter-symbol interference, and at the same time, carrier phase recovery is performed. While the signal is equalized, the phase error of the signal is also compensated, thereby reducing the influence of the phase noise enhanced by equalization.

[0049] In addition, the present application also provides a vector signal recovery device, equipment, medium and product, all of which have the above-mentioned beneficial technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions of the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0051] Figure 1 is a flow chart of a vector signal recovery method provided by an embodiment of the present application;

[0052] Figure 2 The main flow chart of frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application;

[0053] Figure 3 This is a diagram of the algorithm steps for frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application;

[0054] Figure 4 1 is a schematic structural diagram of a vector signal recovery device provided in an embodiment of the present application;

[0055] Figure 5 Schematic diagram of the structure of a vector signal recovery device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] This specific embodiment is merely an explanation of the present application and is not a limitation of the present application. After reading this specification, those skilled in the art may make non-creative modifications to the present embodiment as needed, but as long as they are within the scope of the present application, they are protected by patent law.

[0057] It should be noted that in the optional embodiments of the present application, the object information and other related data involved, when the embodiments in the present application are applied to specific products or technologies, need to obtain the permission or consent of the object, and the collection, use and processing of the relevant data need to comply with the relevant laws, regulations and standards of the relevant countries and regions. In other words, if the embodiments of the present application involve data related to the object, it needs to be obtained through the authorization and consent of the object, the authorization and consent of the relevant departments, and in compliance with the relevant laws, regulations and standards of the country and region. If personal information is involved in the embodiments, the acquisition of all personal information requires the consent of the individual. If sensitive information is involved, the separate consent of the information subject needs to be obtained. The embodiments also need to be implemented with the authorization and consent of the object.

[0058] To make the purpose, technical solutions, and advantages of the embodiments of this application more clear, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0059] In this document, the term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document, unless otherwise specified, generally indicates an "or" relationship between the related objects.

[0060] Adaptive equalizers are often used to compensate for inter-symbol interference (ISI). The computational complexity of a time-domain equalizer increases rapidly with the number of taps, which is essential for high-baud-rate transmission systems. In the embodiment of the present application, a frequency-domain equalization algorithm is used for signal recovery. In the frequency-domain equalizer, the high-complexity convolution in the time domain is replaced by a direct Hadamard product in the frequency domain. The frequency-domain equalization algorithm has lower computational complexity and better convergence, and the frequency-domain equalizer requires fewer hardware resources.

[0061] For the traditional frequency domain equalization algorithm, the algorithm has equalization-enhanced phase noise, which affects the performance of the signal. This is because the input signal is not subjected to carrier phase recovery. When the signal without carrier phase recovery is equalized, the phase noise will be enhanced, affecting the performance of the signal. In order to avoid the impact of equalization-enhanced phase noise, it is necessary to perform phase estimation while equalizing to eliminate the phase noise. Therefore, the embodiment of the present application proposes this frequency domain equalization algorithm based on principal component phase estimation, which relates to the field of optical fiber communication, has low computational complexity, and is easy to implement in hardware. The algorithm uses an adaptive equalizer to eliminate inter-symbol interference and performs carrier phase recovery at the same time. While equalizing the signal, it also compensates for the phase error of the signal, thereby reducing the impact of equalization-enhanced phase noise.

[0062] Specifically, the embodiment of the present application provides a vector signal recovery method, such as Figure 1 As shown, the method provided in the embodiment of the present application can be performed by a vector signal recovery device, and the method includes:

[0063] S101, performing serial-to-parallel conversion and data segmentation on an input signal to obtain multiple data blocks;

[0064] Among them, the input signal is converted from serial to parallel. Assume that the input vector at the time of equalization m is , then the signal after serial-to-parallel conversion is ,for ;

[0065] in, is the signal after serial-to-parallel conversion, Represents matrix transpose.

[0066] At the same time, the serial-to-parallel converted signal Divide the signal into blocks and obtain multiple data blocks. , each data block length is , where L is greater than 1 and can be divided into N, which can be divided into Block, block signal Expressed as: ;in, is a data block of length L, Indicates the nth data block.

[0067] S102, performing Fourier transform, equalization processing, and inverse Fourier transform in sequence according to the target data block and the tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block; the target data block is any data block among the multiple data blocks;

[0068] The tap vector is the tap coefficient of the equalizer corresponding to the target data block. Fourier transform can convert the signal from the time domain to the frequency domain; inverse Fourier transform can convert the signal from the frequency domain back to the time domain.

[0069] In the embodiment of the present application, the target data block may be selected in the order of the multiple data blocks, so that S102 - S105 are sequentially executed on the data blocks until the processing of the multiple data blocks is completed.

[0070] S103, performing principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block, to obtain second principal component information corresponding to the target data block;

[0071] S104, estimating the phase noise corresponding to the target data block according to the second principal component information corresponding to the target data block;

[0072] In the embodiment of the present application, the noise is estimated based on the second principal component information Vn corresponding to the target data block, wherein the second principal component information Vn is a 2-dimensional column vector with two elements. ,in, and They represent the second and third elements of the principal component of the nth input group (i.e., the target data block). The first element of the principal component of the target data block of the input group.

[0073] S105 . Compensate the first signal corresponding to the target data block according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain restored signals corresponding to each of the multiple data blocks.

[0074] The first signal corresponding to the target data block Perform phase compensation to obtain the recovered signal , .

[0075] In the process of processing data blocks in sequence, it is determined whether n is equal to , if they are equal, then end; if , then S102-S105 are repeatedly executed until the processing of multiple data blocks is completed and the recovery signals corresponding to the multiple data blocks are obtained.

[0076] It can be seen that in an embodiment of the present application, the input signal is serial-to-parallel converted and data is divided into blocks; for each data block, the data block transformed into the frequency domain is Fourier transformed and equalized in combination with its corresponding tap vector to compensate for damage in the link, and the equalized data block is inverse Fourier transformed into the time domain, and the principal component analysis is performed on the transformed first signal to facilitate phase noise extraction based on the principal component information corresponding to the data block. In order to avoid the influence of the phase noise enhanced by equalization, the first signal of the data block is phase compensated according to the phase noise corresponding to the data block to obtain a recovered signal, so as to eliminate inter-code interference, and at the same time, carrier phase recovery is performed. While the signal is equalized, the phase error of the signal is also compensated, thereby reducing the influence of the phase noise enhanced by equalization.

[0077] In one possible implementation of the embodiment of the present application, S102, performing Fourier transform, equalization processing, and inverse Fourier transform in sequence according to the target data block and the tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block includes:

[0078] S1021, performing Fourier transform according to the target data block and the overlapping storage method to obtain a second signal corresponding to the target data block;

[0079] According to the overlapping storage method, add a data block before the first data block of the input , the data block Set the length to L as the zero vector. The expression after adding the data block is: ; Recorded as the 0th data block.

[0080] At the same time, according to the overlapping storage method, fast Fourier transform is performed on each two data blocks as a group to obtain the second signal in the frequency domain ; Where n represents the nth data block , is a time domain data block with a length of L.

[0081] For example, , that is, Fourier transform is performed on the 0th data block and the 1st data block.

[0082] S1022. Perform a Hadamard product operation on the second signal corresponding to the target data block and the frequency domain tap vector corresponding to the target data block to facilitate equalization processing, to obtain a third signal, where the frequency domain tap vector is obtained by performing Fourier transform on the tap vector;

[0083] Among them, the equalizer is padded with 0, the padded length is equal to the block length, and then the frequency domain tap vector is obtained by Fourier transform ;according to The third signal is calculated, ; w(n) is the tap vector corresponding to the nth data block.

[0084] S1023. Perform an inverse Fourier transform on the third signal to obtain a first signal corresponding to the target data block.

[0085] In this step, the first signal output by the equalizer is converted to the time domain through inverse Fourier transform. ; Only keep Elements, remember The data block consists of elements That is, the first signal, where n means the nth data block output, and IFFT means inverse Fourier transform.

[0086] It can be seen that in an embodiment of the present application, Fourier transform is performed according to the target data block and the overlapping storage method to obtain the second signal corresponding to the target data block; Hadamard product operation is performed according to the second signal corresponding to the target data block and the frequency domain tap vector corresponding to the target data block to obtain the third signal, and the high-complexity convolution in the time domain is replaced by the direct Hadamard product in the frequency domain; it has lower computational complexity and better convergence, and the frequency domain equalizer requires fewer hardware resources, and the third signal is inverse Fourier transform to obtain the first signal corresponding to the target data block.

[0087] A possible implementation of the embodiment of the present application further includes, before sequentially performing Fourier transform, equalization, and inverse Fourier transform according to the target data block and the tap vector corresponding to the target data block to obtain the first signal corresponding to the target data block:

[0088] SA1. Determine the judgment output of the recovery signal based on the recovery signal corresponding to the previous data block of the target data block;

[0089] In the embodiment of the present application, the restored signal can be represented in a complex form. After the restored signal is obtained, the corresponding decision output can be determined according to the restored signal.

[0090] For example, taking the QPSK signal as an example, the representation of the four standard constellation points of QPSK includes: 1+i, -1+i, -1-i, 1-i; if the recovered signal corresponding to the previous data block is 1.1+1.1i, then after the judgment, the judgment output obtained is 1+i.

[0091] SA2. Determine the time domain error signal corresponding to the previous data block based on the recovered signal and the judgment output corresponding to the previous data block;

[0092] Recovery signal corresponding to the previous data block and judgment output Are all time domain signals, at this time, according to , and get the time domain error signal .

[0093] SA3. Perform Fourier transform on the time domain error signal corresponding to the previous data block to obtain a frequency domain error signal corresponding to the previous data block;

[0094] Error signal Transformed to the frequency domain, it is necessary to fill the first L data of the error signal with zeros before transforming to the frequency domain. The frequency domain expression is: .

[0095] SA4. Perform an inverse Fourier transform on the frequency domain error signal corresponding to the previous data block and the second signal corresponding to the previous data block to determine the gradient information corresponding to the previous data block;

[0096] SA5. Update the tap vector corresponding to the previous data block according to the gradient information corresponding to the previous data block to obtain the tap vector corresponding to the target data block.

[0097] In the embodiment of the present application, the gradient information is calculated and the tap vector is updated. After the gradient calculation, only the first L elements are retained.

[0098] Gradient information corresponding to the previous data block The tap vector corresponding to the target data block The update expressions are 、 ;

[0099] in, is the gradient information, Indicates the second signal corresponding to the previous data block The conjugate of for The first L elements of is the updated tap weight vector, is the step size factor, Is a positive number.

[0100] It can be seen that in the embodiment of the present application, by comparing the output of the previous data block with the expected error, the tap coefficient of the equalizer is adjusted as the tap vector of the next data block to achieve dynamic equalization.

[0101] In one possible implementation of the embodiment of the present application, S103, performing principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block includes:

[0102] S1031, performing covariance calculation according to the real part and the imaginary part of the first signal corresponding to the target data block to obtain a covariance matrix corresponding to the target data block;

[0103] The first signal output by the equalizer The real and imaginary parts of the first signal form a real matrix , the covariance matrix for , The expressions include: ;in, and represent the real and imaginary parts respectively.

[0104] S1032. Determine second principal component information corresponding to the target data block according to the covariance matrix corresponding to the target data block and first principal component information of a previous data block corresponding to the target data block.

[0105] The principal component of the target data block Update and normalize. Initialize the principal components , is a 2-dimensional column vector with two elements. The initialization expression is as well as The update expressions include: ;in, It means All symbols in the vector are squared and summed, and then the square root is taken.

[0106] Represents the updated and normalized formula, for example, the principal component of the second input group The update and normalization are expressed as: .

[0107] In one possible scenario, if the target data block is the first data block, the first principal component information of the previous data block is the preset principal component information; based on the covariance matrix corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block, the second principal component information corresponding to the target data block is determined, including: determining the initial second principal component information based on the covariance matrix corresponding to the first data block and the preset principal component information; using the initial second principal component information as the new preset principal component information, repeatedly performing the step of determining the initial second principal component information based on the covariance matrix corresponding to the first data block and the preset principal component information until a preset condition is met, thereby obtaining the second principal component information corresponding to the target data block; wherein the preset condition includes: the number of repetitions reaches a preset number threshold or a stop instruction is received. Through iterative processing, a reasonable calculation starting point for subsequent data blocks can be determined, and the final second principal component information can be made more accurate and reliable.

[0108] in, , the calculation can be iterated multiple times, wherein the preset number threshold can be set by technicians based on experience, such as 2, 3, 4, etc.; the stop instruction is issued by the user to stop the process of iteratively calculating the principal component information corresponding to the first data block.

[0109] It can be seen that in the embodiment of the present application, the principal component analysis method is used to perform phase estimation on the data block, wherein the covariance matrix corresponding to the target data block is obtained by covariance calculation of the real part and the imaginary part of the first signal of the target data block; the principal component information of the previous data block is introduced to jointly determine the second principal component information corresponding to the target data block, which can make the second principal component information more accurate.

[0110] A possible implementation of the embodiment of the present application further includes: performing parallel-to-serial conversion on the recovered signals corresponding to the multiple data blocks to obtain sub-signals corresponding to the multiple data blocks; and combining the sub-signals corresponding to the multiple data blocks to obtain a processed signal. After obtaining multiple sub-signals, they are combined to obtain the processed signal and output.

[0111] Based on any of the above embodiments, the present application provides a novel vector signal recovery method for achieving dynamic signal equalization and phase estimation, thereby improving the communication quality of the communication system. Figure 2 and Figure 3 , Figure 2 This is the main flow chart of frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application. Figure 3 This is a diagram of the algorithm steps for frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application.

[0112] Step 1: Convert the input signal from serial to parallel. Assume the equalizer The input vector at this moment is

[0113] , then the signal after serial-to-parallel conversion is , which is Formula 1: ;

[0114] The signal after serial-parallel conversion Blocking, the signal after block It is expressed as formula 2: , is a data block of length L.

[0115] Step 2: Calculate the FFT of the data block. According to the overlapping storage method, add a data block before the input data block. The data block is set to a zero vector with a length of L. The expression after adding the data block is as shown in Formula 3: The added zero vector data block with a length of L is recorded as the 0th data block.

[0116] According to the overlapping storage method, fast Fourier transform is performed on each two data blocks as a group to obtain the frequency domain signal , The expression is as shown in Formula 4: ; n represents the nth data block , is a time domain data block with a length of L.

[0117] For example, , that is, perform Fourier transform on the 0th data block and the 1st data block.

[0118] Step 3: Initialize the tap coefficients of the equalizer. According to the overlapping storage method, the equalizer is padded with 0s, and the padded length is equal to the block length. The padded equalizer tap vector is Fourier transformed. The frequency domain tap vector expression is formula 5: ; is the time domain equalizer tap vector, is the frequency domain tap coefficient, is an L-dimensional zero vector.

[0119] in, It is determined based on the recovery signal, judgment output and second signal of the previous data block, wherein the second signal of the previous data block is obtained by Fourier transforming the previous data block and the overlapping storage method; specifically, based on the recovery signal corresponding to the previous data block of the target data block, the judgment output of the recovery signal is determined; based on the recovery signal and judgment output corresponding to the previous data block, the time domain error signal corresponding to the previous data block is determined; the time domain error signal corresponding to the previous data block is Fourier transformed to obtain the frequency domain error signal corresponding to the previous data block; based on the frequency domain error signal corresponding to the previous data block and the second signal corresponding to the previous data block, an inverse Fourier transform is performed to determine the gradient information corresponding to the previous data block; based on the gradient information corresponding to the previous data block, the tap vector corresponding to the previous data block is updated to obtain the tap vector corresponding to the target data block.

[0120] Step 4: Calculate the output signal and convert it to the time domain through inverse Fourier transform. Apply the overlapping memory method, and the equalizer output signal is shown in Formula 6: ; The first L elements of are the result of circular convolution, so only the last L elements are retained. The data block composed of the last L elements is recorded as That is the first signal, where n means the nth data block output. Represents the inverse Fourier transform.

[0121] Step 5: Calculate the covariance matrix . The first signal output by the equalizer The symbols in are squared, and the real and imaginary parts form a real matrix , the covariance matrix for , As shown in formula 7: ; Cn is as shown in formula 8: ; and represent the real and imaginary parts respectively.

[0122] Step 6: Principal component of the nth data block of the input Update and normalize. First, initialize the principal component , is a 2-dimensional column vector with two elements. Formula 9: ; The update expression is Formula 10: .

[0123] Step 7: Estimate the phase noise for the nth data block, see formula 11: ; They represent the second element of the principal component of the nth data block and the first element of the principal component of the nth data block respectively;

[0124] Step 8: Perform phase compensation on the input data block. Based on the obtained phase noise, the first signal of the nth data block is compensated. Perform phase compensation and obtain the recovered signal after phase compensation , restore the signal Output after parallel-serial conversion , The expression is formula 12: ;

[0125] The expression is formula 13: .

[0126] The tap vector is updated through steps nine to eleven to serve as the tap vector of the next data block.

[0127] Step 9: Calculate the error. The formula for calculating the error information in the frequency domain is formula 14: ; is the error of the nth data block, is the decision output of the nth data block.

[0128] Step 10: Error Signal Transform to frequency domain.

[0129] The error signal can be transformed into the frequency domain by filling the first L data with zeros. The frequency domain expression is as shown in Formula 15: .

[0130] Step 11: Calculate the gradient information and update the tap weight vector (tap vector).

[0131] After the gradient information is calculated, only the previous elements, gradient information The expression is as shown in Formula 16: ; The tap weight vector update expression is as shown in Formula 17: ; is the gradient information, express The conjugate of for Before elements, is the updated tap weight vector, is the step size factor, a positive number.

[0132] Step 12: Judgment Is it equal to , if they are equal, then end; if , then repeat steps 2 to 11 until the sub-signals corresponding to all data blocks are obtained.

[0133] It can be seen that the frequency domain equalization algorithm based on principal component phase estimation provided by the embodiment of the present application includes the following: the input sequence is converted into a column vector through serial-parallel conversion, and the column vector is divided into multiple data blocks, each data block is also a column vector, and each data block is processed one by one; the data block is converted into a column vector through Fourier transform. , after being transformed from the time domain to the frequency domain, it is sent to The equalizer performs equalization processing to compensate for link damage. According to the overlap storage method and overlap addition method, setting the data block length to be equal to the equalizer length can maximize the calculation efficiency. After equalization, the equalized data block is transformed from the frequency domain to the time domain through an inverse Fourier transform. The covariance matrix of the data block is calculated and the principal components are updated. Phase estimation is then performed on the data block to extract its phase noise. This extracted phase noise is used to compensate for the phase errors of all symbols within the block, thereby mitigating the effects of phase noise enhanced by equalization. After phase compensation, the recovered signal is generated from the data block and output through parallel-to-serial conversion. Simultaneously, an error signal is calculated and compared with the expected error to adjust the tap coefficients of the equalizer, achieving dynamic equalization.

[0134] The following is an introduction to a device provided in an embodiment of the present application. The device described below and the method described above can refer to each other. The device of this embodiment is set in a vector signal recovery device. Figure 4 , Figure 4 This is a structural block diagram of a device according to one embodiment of the present application, including:

[0135] The block module 210 is used to perform serial-to-parallel conversion and data block division on the input signal to obtain multiple data blocks;

[0136] a transform module 220 configured to sequentially perform Fourier transform, equalization, and inverse Fourier transform on the target data block and the tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block; the target data block is any one of the multiple data blocks;

[0137] A principal component analysis module 230 is configured to perform principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block, to obtain second principal component information corresponding to the target data block;

[0138] A phase noise estimation module 240 is configured to estimate the phase noise corresponding to the target data block based on the second principal component information corresponding to the target data block;

[0139] The compensation module 250 is configured to compensate the first signal corresponding to the target data block according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain restored signals corresponding to each of the multiple data blocks.

[0140] In one implementable manner, the transform module 220 is configured to perform Fourier transform according to the target data block and the overlap storage method to obtain a second signal corresponding to the target data block;

[0141] performing a Hadamard product operation on the second signal corresponding to the target data block and the frequency domain tap vector corresponding to the target data block to facilitate equalization processing to obtain a third signal, wherein the frequency domain tap vector is obtained by performing Fourier transform on the tap vector;

[0142] Perform an inverse Fourier transform on the third signal to obtain a first signal corresponding to the target data block.

[0143] In one possible implementation, the device further includes a tap vector module configured to:

[0144] Determine the judgment output of the recovery signal according to the recovery signal corresponding to the previous data block of the target data block;

[0145] Determine the time domain error signal corresponding to the previous data block based on the recovered signal and the judgment output corresponding to the previous data block;

[0146] Performing Fourier transform on the time domain error signal corresponding to the previous data block to obtain the frequency domain error signal corresponding to the previous data block;

[0147] Performing an inverse Fourier transform on the frequency domain error signal corresponding to the previous data block and the second signal corresponding to the previous data block to determine the gradient information corresponding to the previous data block;

[0148] The tap vector corresponding to the previous data block is updated according to the gradient information corresponding to the previous data block to obtain the tap vector corresponding to the target data block.

[0149] In one achievable manner, the principal component analysis module 230 is configured to:

[0150] Performing covariance calculation based on the real part and the imaginary part of the first signal corresponding to the target data block to obtain a covariance matrix corresponding to the target data block;

[0151] Second principal component information corresponding to the target data block is determined according to the covariance matrix corresponding to the target data block and first principal component information of a previous data block corresponding to the target data block.

[0152] In one implementable manner, if the target data block is the first data block, the first principal component information of the previous data block is the preset principal component information;

[0153] The principal component analysis module 230 is used to:

[0154] Determine initial second principal component information according to the covariance matrix corresponding to the first data block and preset principal component information;

[0155] The initial second principal component information is used as new preset principal component information, and the step of determining the initial second principal component information according to the covariance matrix corresponding to the first data block and the preset principal component information is repeatedly performed until the preset condition is met, thereby obtaining the second principal component information corresponding to the target data block;

[0156] The preset conditions include: the number of repetitions reaches a preset threshold or a stop instruction is received.

[0157] In one achievable method, the present invention further includes:

[0158] The signal combination module is used to perform parallel-to-serial conversion on the recovered signals corresponding to the multiple data blocks to obtain sub-signals corresponding to the multiple data blocks;

[0159] The sub-signals corresponding to the multiple data blocks are combined to obtain a processed signal.

[0160] In the embodiment of the present application, a vector signal recovery device is provided, such as Figure 5 As shown, Figure 5 The vector signal recovery device 300 shown includes a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, for example, via a bus 302. Optionally, the vector signal recovery device 300 may further include a transceiver 304. It should be noted that in practical applications, the number of transceivers 304 is not limited to one, and the structure of the vector signal recovery device 300 does not constitute a limitation on the embodiments of the present application.

[0161] Processor 301 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 301 can also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0162] Bus 302 may include a path for transmitting information between the above components. Bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. Bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0163] The memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0164] The memory 303 is used to store application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the content shown in the above method embodiment.

[0165] Figure 5 The vector signal recovery device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application.

[0166] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding contents of the aforementioned method embodiment.

[0167] An embodiment of the present application provides a computer program product, including a computer program, which implements the corresponding contents of the aforementioned method embodiment when the computer program is executed by a processor.

[0168] It should be understood that although the steps in the flowcharts of the accompanying drawings are shown in sequence as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the flowcharts of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0169] The above are only some of the implementation methods of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A vector signal recovery method, characterized in that: include: Perform serial-to-parallel conversion and data block division on the input signal to obtain multiple data blocks; According to a target data block and a tap vector corresponding to the target data block, Fourier transform, equalization processing, and inverse Fourier transform are sequentially performed to obtain a first signal corresponding to the target data block; the target data block is any one of the multiple data blocks; performing principal component analysis on the target data block according to the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block; estimating the phase noise corresponding to the target data block according to the second principal component information corresponding to the target data block; The first signal corresponding to the target data block is compensated according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain restored signals corresponding to each of the multiple data blocks.

2. The method according to claim 1, characterized in that The method of sequentially performing Fourier transform, equalization, and inverse Fourier transform according to the target data block and the tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block includes: Performing Fourier transform according to the target data block and an overlapping storage method to obtain a second signal corresponding to the target data block; performing a Hadamard product operation on the second signal corresponding to the target data block and a frequency domain tap vector corresponding to the target data block to facilitate equalization processing, to obtain a third signal, wherein the frequency domain tap vector is obtained by performing Fourier transform on the tap vector; Perform an inverse Fourier transform on the third signal to obtain a first signal corresponding to the target data block.

3. The method according to claim 1, characterized in that Before sequentially performing Fourier transform, equalization processing, and inverse Fourier transform according to the target data block and the tap vector corresponding to the target data block to obtain the first signal corresponding to the target data block, the method further includes: Determining a judgment output of a recovery signal according to a recovery signal corresponding to a previous data block of the target data block; Determine the time domain error signal corresponding to the previous data block based on the recovered signal and the judgment output corresponding to the previous data block; Performing Fourier transform on the time domain error signal corresponding to the previous data block to obtain the frequency domain error signal corresponding to the previous data block; Performing an inverse Fourier transform on the frequency domain error signal corresponding to the previous data block and the second signal corresponding to the previous data block to determine the gradient information corresponding to the previous data block; The tap vector corresponding to the previous data block is updated according to the gradient information corresponding to the previous data block to obtain the tap vector corresponding to the target data block.

4. The method according to claim 1, wherein The step of performing principal component analysis on the target data block according to the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block to obtain second principal component information corresponding to the target data block includes: Performing covariance calculation based on the real part and the imaginary part of the first signal corresponding to the target data block to obtain a covariance matrix corresponding to the target data block; Second principal component information corresponding to the target data block is determined according to a covariance matrix corresponding to the target data block and first principal component information of a previous data block corresponding to the target data block.

5. The method according to claim 4, characterized in that If the target data block is the first data block, the first principal component information of the previous data block is the preset principal component information; The determining, based on the covariance matrix corresponding to the target data block and the first principal component information of a previous data block corresponding to the target data block, second principal component information corresponding to the target data block includes: Determining initial second principal component information according to the covariance matrix corresponding to the first data block and preset principal component information; Using the initial second principal component information as new preset principal component information, repeatedly performing the step of determining the initial second principal component information based on the covariance matrix corresponding to the first data block and the preset principal component information until a preset condition is met, thereby obtaining the second principal component information corresponding to the target data block; The preset conditions include: the number of repetitions reaches a preset threshold or a stop instruction is received.

6. The method according to claim 1, characterized in that Also includes: Performing parallel-to-serial conversion on the recovered signals corresponding to the multiple data blocks to obtain sub-signals corresponding to the multiple data blocks; The sub-signals corresponding to the multiple data blocks are combined to obtain a processed signal.

7. A vector signal recovery device, characterized in that: include: A block module is used to perform serial-to-parallel conversion and data block division on the input signal to obtain multiple data blocks; a transform module, configured to perform Fourier transform, equalization processing, and inverse Fourier transform in sequence according to a target data block and a tap vector corresponding to the target data block to obtain a first signal corresponding to the target data block; the target data block is any one of the multiple data blocks; a principal component analysis module, configured to perform principal component analysis on the target data block based on the first signal corresponding to the target data block and the first principal component information of the previous data block corresponding to the target data block, to obtain second principal component information corresponding to the target data block; a phase noise estimation module, configured to estimate the phase noise corresponding to the target data block based on the second principal component information corresponding to the target data block; The compensation module is used to compensate the first signal corresponding to the target data block according to the phase noise corresponding to the target data block to obtain a restored signal corresponding to the target data block, so as to obtain a restored signal corresponding to each of the multiple data blocks.

8. A vector signal recovery device, characterized in that: include: one or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications being configured to: perform the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The storage medium stores at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded by the processor and executes the steps of the method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises a computer program, which, when executed by a processor, implements the steps of the method according to any one of claims 1 to 6.

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