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

Abstract

The invention relates to the field of optical fiber communication, in particular to a vector signal recovery method, device and equipment, a medium and a product, and the method comprises the steps: carrying out the serial-parallel conversion and data partitioning of an input signal; for each data block, Fourier transform and equalization processing are carried out on the data block transformed to the frequency domain in combination with the corresponding tap vector so as to compensate for damage in a link, the equalized data block is transformed to the time domain through inverse Fourier transform, and principal component analysis is carried out on the transformed first signal so as to obtain a second signal; in order to avoid the influence of the balanced enhanced phase noise, phase compensation is carried out on the first signal of the data block according to the phase noise corresponding to the data block to obtain a recovered signal, so that inter-symbol interference is eliminated, and carrier phase recovery is carried out at the same time. And the phase error of the signal is compensated while the signal is balanced, so that the influence of phase noise of balance enhancement is reduced.

Description

Technical Field

[0001] The present application relates to the field of optical fiber communications, and in particular to a vector signal recovery method, device, equipment, 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 need to go through various complex transmission environments and processing processes. In this process, 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 increase in the number of taps, but this is essential for high baud rate transmission systems. The frequency domain equalization algorithm performs signal recovery. In the frequency domain equalizer, the high-complexity convolution in the time domain is replaced by the 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.

[0004] However, in actual scenarios, signals are often subject to various interferences, which causes noise to exist in the input signal of the frequency domain equalization algorithm. When performing frequency domain equalization operations, the noise may be enhanced, further affecting the performance of the signal.

[0005] Therefore, how to improve the accuracy of signal processing and make the signal performance more excellent is a technical problem that technical personnel 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, which can improve the accuracy of signal processing and make the signal performance more excellent.

[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] 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, a principal component analysis of the target data block is performed to obtain the second principal component information corresponding to the target data block;

[0011] estimating a phase noise corresponding to the target data block according to 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 the 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 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;

[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 decision output of a recovery signal according to a recovery signal corresponding to a previous data block of the target data block;

[0019] Determine a time domain error signal corresponding to the previous data block according to a recovered signal and a decision output corresponding to the previous data block;

[0020] Performing Fourier transformation 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 inverse Fourier transform according to 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 of 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 the second principal component information corresponding to the target data block includes:

[0024] 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;

[0025] 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.

[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, according to 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, the second principal component information corresponding to the target data block comprises:

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

[0029] 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;

[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 can be further configured as follows:

[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 sequentially perform Fourier transform, equalization processing, and inverse Fourier transform 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 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, so as to obtain second principal component information corresponding to the target data block;

[0038] A phase noise estimation module, used for estimating the phase noise corresponding to the target data block according to 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 the recovery signal corresponding to the target data block, so as to obtain the recovery signals 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, a code set or an instruction set, and the at least one instruction, at least one program, a code set or an instruction set is loaded by a processor and executes the steps of the vector signal recovery method shown in any possible implementation method of the first aspect.

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

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

[0047] The input signal is converted from serial to parallel and the data is divided into blocks to obtain multiple data blocks; Fourier transform, equalization processing, and inverse Fourier transform are performed 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; principal component analysis of the target data block is performed 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; according to the second principal component information corresponding to the target data block, the phase noise corresponding to the target data block is estimated; according to the phase noise corresponding to the target data block, the first signal corresponding to the target data block is compensated 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 transformed into the time domain through inverse Fourier transform, and the transformed first signal is subjected to principal component analysis 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 based on the phase noise corresponding to the data block to obtain a recovered signal to eliminate inter-code crosstalk, and carrier phase recovery is performed at the same time. 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 drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying 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 A main flow chart of frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application;

[0053] Figure 3 An algorithm step diagram of frequency domain equalization based on principal component phase estimation provided in an embodiment of the present application;

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

[0055] Figure 5 It is a structural schematic diagram 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, a person skilled in the art may make non-creative modifications to the present embodiment as needed, but such modifications are protected by the patent law as long as they are within the scope of the present application.

[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 with 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 needs to obtain 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] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0059] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0060] Adaptive equalizers are often used to compensate for inter-symbol interference (ISI). The computational complexity of the time domain equalizer increases rapidly with the increase in the number of taps, but this is essential for high baud rate transmission systems. In the embodiment of the present application, a frequency domain equalization algorithm is applied for signal recovery. In the frequency domain equalizer, the high complexity convolution in the time domain is replaced by the 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 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-code interference and performs carrier phase recovery at the same time. While equalizing the signal, the phase error of the signal is also compensated, thereby reducing the impact of equalization-enhanced phase noise.

[0062] Specifically, the present application embodiment 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 block division 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 to obtain multiple data blocks. , the length of each data block is , where L is greater than 1 and can be divided into N, Block, block-based signal It is expressed as: ;in, is a data block of length L, Indicates the nth data block.

[0067] S102, according to the target data block and the tap vector corresponding to the target data block, sequentially perform Fourier transform, equalization processing, and inverse Fourier transform 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 transform the signal from the time domain to the frequency domain; inverse Fourier transform can transform 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 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;

[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 according to 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 one by one, 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 the embodiment of the present application, the input signal is converted from serial to parallel and the data is divided into blocks; for each data block, the data block transformed to 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 transformed to the time domain through inverse Fourier transform, and the transformed first signal is subjected to principal component analysis 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 crosstalk, 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] A possible implementation of the embodiment of the present application is, 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, including:

[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 it to a zero vector with a length of L. 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, 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;

[0083] Among them, the equalizer is padded with 0, the padded length is equal to the block length, and then Fourier transform is performed to obtain the frequency domain tap vector ;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 transformed to the time domain through inverse Fourier transform. ; Only keep Elements, remember The data block consisting of elements is 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 the 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 transformed to obtain the first signal corresponding to the target data block.

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

[0088] SA1, determining the judgment output of the recovery signal according to 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 may be expressed in complex form, and after the restored signal is obtained, the corresponding decision output may 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, determining a time domain error signal corresponding to the previous data block according to the recovery signal and the judgment output corresponding to the previous data block;

[0092] The recovery signal corresponding to the previous data block And the judgment output are all time domain signals. At this time, according to , and get the time domain error signal .

[0093] SA3, 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;

[0094] Error signal Transformed to the frequency domain, the first L data of the error signal need to be padded with zeros before it can be transformed to the frequency domain. The frequency domain expression is: .

[0095] SA4, performing an inverse Fourier transform according to 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 is calculated, 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] A possible implementation of the embodiment of the present application, S103, performing principal component analysis of 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:

[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 of the equalizer output 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 part and imaginary part 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 is expressed as as well as The update expressions include: ;in, It means that 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 case, 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; according to 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: according to the covariance matrix corresponding to the first data block and the preset principal component information, the initial second principal component information is determined; the initial second principal component information is used as the 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 repeated until the preset condition is met, and the second principal component information corresponding to the target data block is obtained; wherein the preset condition includes: the number of repetitions reaches the 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 second principal component information finally obtained 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 restored 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 it.

[0111] Based on any of the above embodiments, the present application provides a novel vector signal recovery method for realizing dynamic signal equalization and phase estimation, thereby improving the communication quality of the communication system. Figure 2 and Figure 3 , Figure 2 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 that 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-to-parallel conversion Divide into blocks, and the signal after block division 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 as a zero vector with a length of L. The expression after adding the data block is as shown in Formula 3: is a zero vector data block with a length of L added, 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, Fourier transform is performed 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, fill the equalizer with 0, the padding length is equal to the block length, and perform Fourier transform on the padded equalizer tap vector. 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 according to the recovery signal, the decision output and the 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, according to the recovery signal corresponding to the previous data block of the target data block, the decision output of the recovery signal is determined; according to the recovery signal and the decision 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; according to 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; according to 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 transform it to the time domain through inverse Fourier transform. Apply the overlapping storage 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 part and imaginary part 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 of is formula 10: .

[0123] Step 7: Estimate the phase noise for the nth data block, see formula 11: ; Respectively 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;

[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 Perform phase compensation and obtain the recovered signal after phase compensation , restore the signal Output after parallel-to-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 be used 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 is transformed into the frequency domain by padding 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: Judgement 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 in the embodiment of the present application includes the following contents: 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, when the data block length is set to be equal to the equalizer length, the calculation efficiency can be maximized. After the equalizer, the equalized data block is transformed from the frequency domain to the time domain through the inverse Fourier transform, and the covariance matrix of the data block is calculated and the principal component is updated. Then the phase of the data block is estimated and the phase noise of the data block is extracted. The phase error of all symbols in the block is compensated by the extracted phase noise, thereby reducing the impact of the phase noise enhanced by the equalization. The data block is phase compensated to obtain the recovered signal, which is output after parallel-to-serial conversion. At the same time, the error signal is calculated, and the tap coefficient of the equalizer is adjusted by comparing the output with the expected error to achieve 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 be referred to each other. The device of this embodiment is set in a vector signal recovery device. Figure 4 , Figure 4 It is a structural block diagram of a device of one embodiment of the present application, comprising:

[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] The transformation module 220 is used to perform Fourier transformation, equalization processing, and inverse Fourier transformation 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;

[0137] A principal component analysis module 230 is used to 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, so as to obtain second principal component information corresponding to the target data block;

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

[0139] The compensation module 250 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 restored signals corresponding to each of the multiple data blocks.

[0140] In an implementable manner, the transform module 220 is used to perform Fourier transform according to the target data block and the overlapping 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, thereby obtaining 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 achievable manner, the present invention 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 a time domain error signal corresponding to the previous data block according to a recovered signal and a decision output corresponding to the previous data block;

[0146] Performing Fourier transformation 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 inverse Fourier transform according to 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 used to:

[0150] 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;

[0151] According to 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.

[0152] In one achievable 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, and the second principal component information corresponding to the target data block is obtained;

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

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

[0158] The signal combination module is used to: perform parallel-to-serial conversion on the restored 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 an 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, such as through a bus 302. Optionally, the vector signal recovery device 300 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 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] The processor 301 may 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 devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may 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] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0163] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices 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 compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the 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 the 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 contents shown in the above method embodiment.

[0165] Figure 5 The vector signal recovery device shown is only an example and should not bring any limitation to 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, on which a computer program is stored. When the computer-readable storage medium is run on a computer, the computer can execute the corresponding content in 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 flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence 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 a part of the steps in the flowchart 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 part of the sub-steps or stages of other steps.

[0169] The above are only some 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; 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, a principal component analysis of the target data block is performed to obtain the second principal component information corresponding to the target data block; estimating a phase noise corresponding to the target data block according to 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 processing, 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 the 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 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; 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 decision output of a recovery signal according to a recovery signal corresponding to a previous data block of the target data block; Determine a time domain error signal corresponding to the previous data block according to a recovered signal and a decision output corresponding to the previous data block; Performing Fourier transformation 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 inverse Fourier transform according to 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, characterized in that: 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 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; 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.

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, according to 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, the second principal component information corresponding to the target data block comprises: Determining initial second principal component information according to the covariance matrix corresponding to the first data block and preset principal component information; 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; 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 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, so as to obtain second principal component information corresponding to the target data block; A phase noise estimation module, used for estimating the phase noise corresponding to the target data block according to 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 the recovery signal corresponding to the target data block, so as to obtain the recovery signals 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, and the one or more applications are 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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