Data processing method, device, equipment and computer readable storage medium

Abstract

The present invention discloses a data processing method, device, equipment and computer-readable storage medium. The data processing method includes: obtaining communication transmission data, performing data analysis on the communication transmission data to obtain communication evaluation data, performing data analysis on the communication transmission data to obtain communication evaluation data, including: obtaining sequence data of the communication transmission data, performing linear operation conversion processing on the sequence data to obtain initial solution space data, summarizing the initial solution space data to obtain target solution space data, obtaining data of intersection in the target solution space data to obtain intersection solution space data, and performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data. The present invention can reduce the amount of calculation for solving sequence data.

Description

Technical Field

[0001] The present invention relates to the field of computer communication technology, and in particular to a data processing method, device, equipment and computer-readable storage medium. Background Art

[0002] At present, in the era of the Internet of Everything, new technologies such as 5G, big data, and artificial intelligence have brought innovative vitality to the Internet of Things (IoT). The Internet of Things has the characteristics of large-scale connections and diverse access methods, and the boundaries between the digital world and the physical world are gradually disappearing. 5G communication is also an important area of ​​national development. Technologies such as communication coding, communication channel estimation, and synchronization are developing day by day. One of the difficulties is that in the field of communication, various applications more or less involve the construction of sequences, and many sequence constructions involve solving multivariate nonlinear equations.

[0003] In the related art, the direct numerical trial method is used to solve the multivariate nonlinear equation by computer, which uses an exhaustive method to try all the solution data based on a single decimal number until the final solution data is obtained. This algorithm has a huge amount of calculation for multivariate nonlinear equations, and the amount of calculation increases sharply with the increase of sequence length. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention proposes a data processing method that can reduce the amount of calculation for solving sequence data.

[0005] The present invention also provides a data processing device.

[0006] The present invention also provides a data processing device.

[0007] The present invention also provides a computer-readable storage medium.

[0008] In a first aspect, an embodiment of the present invention provides a data processing method, comprising:

[0009] Acquire communication transmission data;

[0010] Performing data analysis on the communication transmission data to obtain communication evaluation data;

[0011] The performing data analysis on the communication transmission data to obtain communication evaluation data includes:

[0012] Acquiring sequence data of the communication transmission data;

[0013] Performing linear operation conversion processing on the sequence data to obtain initial solution space data;

[0014] Summarizing the initial solution space data to obtain target solution space data;

[0015] Acquire the data of the intersection in the target solution space data to obtain the intersection solution space data;

[0016] The intersection solution space data is processed according to a preset solution algorithm to obtain the communication evaluation data.

[0017] The data processing method of the embodiment of the present invention has at least the following beneficial effects: performing data analysis on the acquired communication transmission data, including: acquiring multiple sequence data of the communication transmission data, and performing linear operation conversion processing on the sequence data to obtain initial solution space data of each sequence data, so as to convert the sequence data into linear, and then, aggregating the initial solution space data to obtain a set of multiple initial solution space data, that is, the target solution space data of each sequence data, and then, obtaining the data of the intersection of each target solution space data to obtain the intersection solution space data, and finally, solving the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data, which can reduce the amount of calculation for solving the sequence data.

[0018] According to some other embodiments of the data processing method of the present invention, the linear operation conversion processing is performed on the sequence data to obtain initial solution space data, including:

[0019] Obtaining coefficient matrix data corresponding to the sequence data;

[0020] Performing a solution process with the sum of the coefficient matrix data being zero to obtain first solution space data, wherein the first solution space data includes a plurality of solution basis data;

[0021] Adding any two of the solution basis data among a plurality of the first solution space data, and / or multiplying the solution basis data by a preset scalar to obtain second solution space data;

[0022] The initial solution space data is determined according to the first solution space data and the second solution space data.

[0023] According to some other embodiments of the data processing method of the present invention, the step of obtaining coefficient matrix data corresponding to the sequence data includes:

[0024] The sequence data is expressed by a preset linear equation expression to obtain a target linear equation, wherein the preset linear equation expression is formed by combining preset parameters, a coefficient matrix and transposed data of the preset parameters;

[0025] The coefficient matrix in the target linear equation is obtained to obtain the coefficient matrix data.

[0026] According to some other embodiments of the data processing method of the present invention, the aggregating and processing the initial solution space data to obtain the target solution space data includes:

[0027] Obtaining coefficient matrix data corresponding to the sequence data;

[0028] Transposing the coefficient matrix data to obtain transposed matrix data;

[0029] Performing a solution process with the sum of the transposed matrix data being zero to obtain third solution space data;

[0030] The third solution space data and the initial solution space data are aggregated to obtain the target solution space data.

[0031] According to some other embodiments of the data processing method of the present invention, the aggregating and processing the initial solution space data to obtain the target solution space data further includes:

[0032] Processing the coefficient matrix data accordingly according to a preset processing rule to obtain conversion matrix data;

[0033] Performing a solution process with the sum of the transformation matrix data being zero to obtain fourth solution space data;

[0034] The third solution space data, the fourth solution space data and the initial solution space data are aggregated to obtain the target solution space data.

[0035] According to some other embodiments of the data processing method of the present invention, the obtaining of the intersection data in the target solution space data to obtain the intersection solution space data includes:

[0036] Acquire two linearly related target solution space data;

[0037] The two target solution space data are spliced ​​in column direction to obtain corresponding spliced ​​solution space data;

[0038] Transposing the spliced ​​solution space data to obtain transposed solution space data;

[0039] Cutting and transposing the preset columns of the transposed solution space data to obtain cut solution space data;

[0040] The target solution space data is multiplied by the intercepted solution space data and the result is solved with the sum being zero to obtain the intersection solution space data.

[0041] According to some other embodiments of the data processing method of the present invention, the step of performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data includes:

[0042] Acquire combined solution space data according to the intersection solution space data;

[0043] The combined solution space data is solved according to the preset solution algorithm to obtain the communication evaluation data.

[0044] In a second aspect, an embodiment of the present invention provides a data processing device, comprising:

[0045] An acquisition module, used for acquiring communication transmission data;

[0046] An analysis module, used for performing data analysis on the communication transmission data to obtain communication evaluation data;

[0047] The analysis module comprises:

[0048] An acquisition unit, used for acquiring sequence data of the communication transmission data;

[0049] A conversion unit, used for performing linear operation conversion processing on the sequence data to obtain initial solution space data;

[0050] A summarizing unit, used for summarizing the initial solution space data to obtain target solution space data;

[0051] An intersection unit, used to obtain the data of the intersection in the target solution space data to obtain the intersection solution space data;

[0052] A solution unit is used to process the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data.

[0053] The data processing device of the embodiment of the present invention has at least the following beneficial effects: the analysis module performs data analysis on the communication transmission data acquired by the acquisition module, and the acquisition module includes: the acquisition unit acquires multiple sequence data of the communication transmission data, and the conversion unit performs linear operation conversion processing on the sequence data to obtain initial solution space data of each sequence data, and can convert the sequence data into linear; then, the summary unit summarizes the initial solution space data to obtain a set of multiple initial solution space data, that is, the target solution space data of each sequence data; secondly, the intersection unit obtains the data of the intersection of each target solution space data to obtain the intersection solution space data; finally, the solution unit solves the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data, which can reduce the amount of calculation for solving the sequence data.

[0054] In a third aspect, an embodiment of the present invention provides a data processing device, comprising:

[0055] at least one processor, and

[0056] a memory communicatively connected to the at least one processor; wherein,

[0057] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the data processing method as described in the first aspect.

[0058] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the data processing method as described in the first aspect.

[0059] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained through the structures particularly pointed out in the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flowchart of a specific embodiment of the data processing method in an embodiment of the present invention;

[0061] Figure 2 yes Figure 1 A schematic flow chart of a specific embodiment of step S200;

[0062] Figure 3 yes Figure 2 A flowchart of a specific embodiment of step S220;

[0063] Figure 4 yes Figure 3 A schematic flow chart of a specific embodiment of step S221;

[0064] Figure 5 yes Figure 2 A schematic flow chart of a specific embodiment of step S230;

[0065] Figure 6 yes Figure 2 Another specific embodiment of step S230 is shown in the flowchart;

[0066] Figure 7 yes Figure 2 A schematic flow chart of a specific embodiment of step S240;

[0067] Figure 8 yes Figure 2 A schematic flow chart of a specific embodiment of step S250;

[0068] Fig. 9 is a block diagram of a specific embodiment of a data processing device in an embodiment of the present invention; Description of the drawings:

[0070] Acquisition module 100, analysis module 200;

[0071] An acquisition unit 210 , a conversion unit 220 , a summary unit 230 , an intersection unit 240 , and a solution unit 250 . DETAILED DESCRIPTION

[0072] The following will be combined with the embodiments to clearly and completely describe the concept of the present invention and the technical effects produced, so as to fully understand the purpose, characteristics and effects of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative work are all within the scope of protection of the present invention.

[0073] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0074] It should be noted that although the system diagram is divided into functional modules and the flow chart shows a logical order, in some cases, the steps shown or described may be performed in a manner different from the module division in the system or the order in the flow chart.

[0075] In the description of the present invention, unless otherwise clearly defined, terms such as setting, installing, connecting, etc. should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in the present invention based on the specific content of the technical solution.

[0076] In the description of the embodiments of the present invention, if "several" is involved, it means more than one, if "multiple" is involved, it means more than two, if "greater than", "less than" or "exceed" is involved, it should be understood as not including the number itself, if "above", "below" or "within" is involved, it should be understood as including the number itself. If "first" or "second" is involved, it should be understood as being used to distinguish technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0077] Reference Figure 1 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S100 to S200.

[0078] Step S100, acquiring communication transmission data;

[0079] In step S100, transmission data after space matrix communication coding is acquired to obtain communication transmission data.

[0080] Step S200: analyzing the communication transmission data to obtain communication evaluation data.

[0081] In step S200, the correlation coefficient of the communication transmission data is obtained, and the correlation coefficient is solved and analyzed to obtain communication evaluation data.

[0082] By executing step S100 to step S200, transmission data after space matrix communication coding is acquired to obtain communication transmission data. Correlation coefficient data of the communication transmission data is solved and analyzed to obtain communication evaluation data.

[0083] Reference Figure 2 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S210 to S250.

[0084] Step S210, acquiring sequence data of communication transmission data;

[0085] In step S210, an autocorrelation equation of the communication transmission data is obtained to obtain sequence data.

[0086] It should be noted that the present invention needs to construct the communication transmission data into perfect Gaussian integer sequence data, and extract the autocorrelation equation of the communication transmission data. For example, the sequence data is determined as follows:

[0087]

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095]

[0096] Analyzing one of the sequence data R00, it can be seen that the characteristics of all items are quadratic. All items in the sequence data R11 are also quadratic. All items in the sequence data R21 are also quadratic. To construct a perfect Gaussian integer sequence data, it is required that R00 = 0, R01 = 0, R02 = 0, R10 = 0, R11 = 0, R12 = 0, R20 = 0, and R21 = 0. However, R22, which represents its own energy, is not zero. To achieve this condition, it is necessary to solve the 8 equations composed of all sequence data. Moreover, the sequence data R22 represents energy, which is naturally not equal to zero.

[0097] Step S220, performing linear operation conversion processing on the sequence data to obtain initial solution space data;

[0098] In step S220, the quadratic coefficients of each sequence data are extracted, and the quadratic coefficients are linearized to reduce the dimension of the sequence data to a linear equation system to obtain initial solution space data.

[0099] Step S230, summarizing the initial solution space data to obtain target solution space data;

[0100] In step S230, more solution space data of each sequence data is obtained, and the solution space data and the initial solution space data are aggregated and processed to obtain the target solution space data.

[0101] Step S240, obtaining the data of the intersection in the target solution space data to obtain the intersection solution space data;

[0102] In step S240, data of intersections of all target solution space data are obtained to obtain intersection solution space data.

[0103] Step S250: Process the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data.

[0104] In step S250, the intersection solution space data is processed according to a preset solution algorithm to obtain a numerical solution of the intersection solution space to obtain communication evaluation data.

[0105] By executing steps S210 to S250, first, the autocorrelation equation of the communication transmission data is obtained to obtain sequence data. Then, the sequence data is linearized according to the quadratic coefficients of each sequence data, and the sequence data is reduced to a linear equation system to obtain initial solution space data. Secondly, more solution space data of each sequence data is obtained, and the solution space data and the initial solution space data are summarized and processed to obtain target solution space data. Then, data with intersections of all target solution space data is obtained to obtain intersection solution space data. Finally, the intersection solution space data is solved according to a preset solution algorithm to obtain a numerical solution of the intersection solution space to obtain communication evaluation data.

[0106] Reference Figure 3 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S221 to S224.

[0107] Step S221, obtaining coefficient matrix data corresponding to the sequence data;

[0108] In step S221, coefficient matrix data of each sequence data is obtained, wherein each sequence data corresponds to one coefficient matrix data.

[0109] For example, the coefficient matrix data A00 of the sequence data R00 is:

[0110]

[0111] Step S222, performing a solution process with the sum of the coefficient matrix data being zero to obtain first solution space data, and obtaining a plurality of solution basis data based on the first solution space data;

[0112] In step S222, the value of each coefficient matrix data is equal to zero, and all solutions of each coefficient matrix data are obtained according to the null space solution method to obtain the corresponding first solution space data, and the first solution space data includes multiple solution basis data.

[0113] It should be noted that each row of data in the first solution space data corresponds to a solution basis data.

[0114] For example: the coefficient matrix data A 00 = 0, that is, calculate NullSpace(A 00 ):

[0115]

[0116] Among them, the solution basis data corresponding to the first row is: {0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,2}.

[0117] Step S223, adding any two solution basis data among the plurality of first solution space data, and / or multiplying the solution basis data by a preset scalar to obtain second solution space data;

[0118] In step S223, any two solution basis data of each first solution space data are added to obtain a new solution basis data. A solution basis data can also be multiplied by a preset scalar to obtain new solution basis data. The solution basis data and the new solution basis data are combined to obtain the second solution space data.

[0119] It should be noted that each first solution space data generates new solution basis data through the solution basis data included in itself, and the new solution basis data can be used to generate other new solution basis data.

[0120] For example: NullSpace(A 00 )’s two solution basis data: {0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,2} and {0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,1,0}. Adding these two solution basis data we can get a new solution basis data: {0,0,0,0,0,0,0,0,0,0,0,0,0,-2,0,0,1,2}.

[0121] Step SS224, determining the initial solution space data according to the first solution space data and the second solution space data

[0122] In step S224, all the first solution space data and all the second solution space data are combined into an initial solution space data.

[0123] By executing steps S221 to S224, first, the coefficient matrix data of each sequence data is obtained, and all solutions of each coefficient matrix data are obtained according to the null space solution method to obtain the corresponding first solution space data, wherein the first solution space data includes a plurality of solution basis data. Then, any two solution basis data of each first solution space data are added together to obtain a new solution basis data, or a solution basis data is multiplied by a preset scalar to obtain a new solution basis data, and the solution basis data and the new solution basis data are combined to obtain the second solution space data. Finally, all the first solution space data and all the second solution space data are combined into an initial solution space data.

[0124] Reference Figure 4 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S2211 to S2212.

[0125] Step S2211, expressing the sequence data with a preset linear equation expression to obtain a target linear equation, wherein the preset linear equation is formed by combining preset parameters, a coefficient matrix, and transposed data of the preset parameters;

[0126] In step S2211, the coefficient matrix of each sequence data is obtained, a preset parameter is preset, and the preset parameter is transposed to obtain the transposed data, and the preset parameter, coefficient matrix, transposed data and sequence data are represented according to the preset linear equation expression to obtain the target linear equation.

[0127] It should be noted that the target linear equation is: the matrix multiplication of the preset parameters, the coefficient matrix and the transposed data is equal to the sequence data. Among them, each sequence data generates a target linear equation.

[0128] For example, the preset parameters are:

[0129]

[0130] Transposed data is: X T , taking the sequence data R00 as an example, obtain the coefficient matrix A00 of the sequence data R00, and by combining the preset linear equation expression, the target linear equation can be obtained:

[0131]

[0132] Step S2212, obtain the coefficient matrix in the target linear equation to obtain coefficient matrix data.

[0133] In step S2212, the coefficient matrix is ​​obtained by converting the target linear equation to obtain coefficient matrix data.

[0134] By executing steps S2211 to S2212, the coefficient matrix of each sequence data is obtained, and the preset parameters, coefficient matrix, transposed data and sequence data are expressed according to the preset linear equation expression to obtain the target linear equation. The coefficient matrix is ​​obtained by converting the target linear equation to obtain coefficient matrix data. The quadratic coefficients of the sequence data are extracted and the quadratic coefficients are linearized.

[0135] Reference Figure 5 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S221 to S233.

[0136] Step S231, transposing the coefficient matrix data to obtain transposed matrix data;

[0137] In step S231, each coefficient matrix data is transposed to obtain corresponding transposed matrix data.

[0138] For example: the coefficient matrix data A21 is:

[0139]

[0140] The transposed matrix data of the coefficient matrix data A21 is:

[0141]

[0142] Step S232, performing a solution process with the sum of the transposed matrix data being zero to obtain third solution space data;

[0143] In step S232, the value of each transposed matrix data is equal to zero, and all solutions of each transposed matrix data are obtained according to the null space solution method to obtain the third solution space data.

[0144] For example: Transpose matrix data A 21 T The third solution space data is:

[0145]

[0146] Step S233: Aggregate the third solution space data and the initial solution space data to obtain target solution space data.

[0147] In step S233, the third solution space data and the initial solution space data are aggregated and combined to obtain a target solution space data.

[0148] For example, the initial solution space data of coefficient matrix data A21 is:

[0149]

[0150] The target solution space data of coefficient matrix data A21 is:

[0151]

[0152] By executing steps S231 to S233, first, each coefficient matrix data is transposed to obtain corresponding transposed matrix data. Then, the value of each transposed matrix data is equal to zero, and all solutions of each transposed matrix data are obtained according to the null space solution method to obtain the third solution space data. Finally, the third solution space data and the initial solution space data are summarized and combined to obtain the target solution space data.

[0153] Reference Figure 6, shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S234 to S236.

[0154] Step S234, performing corresponding processing on the coefficient matrix data according to a preset processing rule to obtain conversion matrix data;

[0155] In step S234, the preset diagonal data of the coefficient matrix data is numerically converted according to a preset processing rule to obtain conversion matrix data.

[0156] It should be noted that the result of adding the corresponding preset diagonal data after conversion is consistent with the result of adding the preset diagonal data before conversion.

[0157] For example, after the coefficient matrix data A21 is converted into a conversion matrix data:

[0158]

[0159] Among them, other non-zero data except the preset diagonal data, such as coefficient matrix data A 21 The element in the second row and third column of is 4, and its diagonal data is 0. The sum of the diagonal data (the element in the third row and second column) is 4. Then it can make the conversion matrix data A 21 t1 The second row and third column of the element is 3, and the diagonal element (the third row and second column element) is 1, and the sum after addition is 4, which can also generate the quadratic multivariate nonlinear equation. That is: the transformation matrix data A 21 t1 The preset diagonal data "1" and "3" correspond to the coefficient matrix data A 21 The preset diagonal data "0" and "4" of the conversion matrix data A 21 t1 The sum of the preset diagonal data and the coefficient matrix data A 21 The sum of the preset diagonal data is equal.

[0160] Step S235, performing a solution process with the sum of the conversion matrix data being zero to obtain fourth solution space data;

[0161] In step S235, the value of each transformation matrix data is equal to zero, and all solutions of each transformation matrix data are obtained according to the null space solution method to obtain the fourth solution space data.

[0162] It should be noted that the fourth solution space data generated by each conversion matrix data may be equal or unequal, so the generated fourth solution space data must be merged to obtain the complete solution of the conversion matrix data.

[0163] Step S236, aggregating the third solution space data, the fourth solution space data and the initial solution space data to obtain target solution space data.

[0164] In step S236, the third solution space data, the fourth solution space data and the initial solution space data are aggregated and combined to obtain a target solution space data.

[0165] By executing steps S234 to S236, first, the preset diagonal data of the coefficient matrix data is numerically converted according to the preset processing rules to obtain conversion matrix data. Then, the value of each conversion matrix data is equal to zero, and all solutions of each conversion matrix data are obtained according to the null space solution method to obtain the fourth solution space data. The third solution space data, the fourth solution space data and the initial solution space data are summarized and combined to obtain a target solution space data.

[0166] Reference Figure 7 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S241 to S246.

[0167] Step S241, obtaining two linearly related target solution space data;

[0168] In step S241, two linearly related target solution space data among a plurality of target solution space data are obtained.

[0169] It should be noted that the linear correlation is: For example: If a.X+bY=0 holds, then X and Y are said to be linearly correlated, where X and Y represent two target solution space data.

[0170] For example: NullSpace(A 20 all ) and NullSpace(A 21 all ).

[0171] Step S242, performing column-wise splicing processing on the two target solution space data to obtain corresponding spliced ​​solution space data;

[0172] In step S242, the last row position of one target solution space data and the first row position of another target solution space data are spliced ​​to obtain corresponding spliced ​​solution space data.

[0173] Step S243, transposing the spliced ​​solution space data to obtain transposed solution space data;

[0174] By executing step S242 to step S243, for example: the target solution space data NullSpace (A 20 all ):

[0175]

[0176]

[0177] NullSpace(A 20 all ) and NullSpace(A 21 all ) are concatenated and transposed to obtain:

[0178]

[0179]

[0180]

[0181] It should be noted that the last 12 columns and the first 40 columns need to be analyzed separately and are not zero to indicate that the two spaces are linearly related. Otherwise, it is meaningless if the solution space is zero.

[0182] Step S244, truncating and transposing the preset columns of the transposed solution space data to obtain truncated solution space data;

[0183] In step S244, the transposed solution space data is intercepted according to the preset column data, and then the intercepted transposed solution space data is transposed to obtain intercepted solution space data.

[0184] It should be noted that the corresponding preset column data are preset according to the number of columns of the two spliced ​​target solution space data, and the number of columns of the target solution space data is consistent with the preset column data.

[0185] For example: the target solution space data NullSpace (A 20 all ) has 40 columns (the first 40 columns) of solution base data, and the target solution space data NullSpace (A 21 all ) has 12 columns (last 12 columns), and the target solution space data NullSpace (A 20 all ) and the target solution space data NullSpace(A 21 all) The solution base data of the spliced ​​solution space data after splicing has 52 columns, and the preset column data of the first 40 columns or the last 12 columns of the transposed solution space data are intercepted and transposed. Among them, the first 40 columns and the last 12 columns are not zero at the same time to indicate that the two solution space sets have non-zero solutions, and the intersection of the two target solution space data can be obtained.

[0186] The transposed solution space data is to intercept the first 40 columns of data, then obtain the target solution space data corresponding to the intercepted first 40 columns of data, that is, NullSpace (A 20 all ), and the transposed solution space data and the target solution space data NullSpace(A 20 all ) are multiplied.

[0187] Step S245, multiplying the target solution space data and the intercepted solution space data and solving with the sum being zero to obtain the intersection solution space data;

[0188] In step S245, the target solution space data and the intercepted solution space data are processed by a multiplication algorithm, and the result of the multiplication is solved with the sum being zero to obtain the intersection solution space data.

[0189] It should be noted that the intersection solution space data includes multiple solution basis data. When the solution basis data is all 0, the solution basis data of all 0 will be removed.

[0190] For example: the target solution space data NullSpace (A 20 all ) and the target solution space data NullSpace(A 20 all ) and multiply the corresponding intercepted solution space data and solve it with the sum equal to zero to obtain:

[0191] {{0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}, {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}},

[0192] Remove all 0 decomposition data to get:

[0193] {{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1} ,{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0}}

[0194] By executing steps S241 to S245, first, two linearly related target solution space data among multiple target solution space data are obtained. Then, the last row position of one target solution space data and the first row position of another target solution space data are spliced ​​to obtain corresponding spliced ​​solution space data. Secondly, the spliced ​​solution space data is transposed to obtain transposed solution space data. Then, the transposed solution space data is intercepted according to the preset column data, and the intercepted transposed solution space data is transposed to obtain the intercepted solution space data. Finally, the target solution space data and the intercepted solution space data are multiplied by an algorithm, and the result of the multiplication is solved with the sum of zero to obtain the intersection solution space data.

[0195] It should be noted that, by repeatedly executing step S241 to step S245, the intersection solution space data of all arbitrary two target solution space numbers that are linearly correlated are obtained.

[0196] Reference Figure 8 , shows a flow chart of a data processing method in an embodiment of the present invention. In addition, this embodiment discloses a data processing method, which specifically includes but is not limited to steps S251 to S252.

[0197] Step S251, obtaining combined solution space data according to the intersection solution space data;

[0198] In step S251, the number and value range of solution basis data of each intersection solution space data are obtained, and the corresponding number of combined solution space data are obtained according to the number and value range.

[0199] It should be noted that the number of the obtained combined solution space data is consistent with the number of solution basis data of the intersection solution space data.

[0200] For example: the target solution space data NullSpace (A 20 all ) and the target solution space data NullSpace(A 20 all ) and multiply the corresponding intercepted solution space data and solve it with the sum equal to zero to obtain:

[0201] {{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1} ,{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0}}

[0202] The number of solution basis data is 8, and the numerical range of the solution basis data is: {-2, -1, 0, 1, 2} and {-2, -1, 1, 2}.

[0203] The combined solution space data is obtained according to the number of solution basis data and the numerical range of the solution basis data:

[0204] Xssarray

[0205] ={{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,0,1,2},{-2,-1,0,1,2}}

[0206] Step S252: performing solution processing on the combined solution space data according to a preset solution algorithm to obtain communication evaluation data.

[0207] In step S252, the combined solution space data is substituted into a preset solution algorithm for solution to obtain communication evaluation data.

[0208] For example: The combined solution space data is:

[0209] Xssarray

[0210] ={{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,0,1,2},{-2,-1,0,1,2}}

[0211] Solve to obtain communication evaluation data:

[0212] {0,0,0,0,4,0,0,-4,4,0,0,0,0,-4,4,0,-4,0}, {0,0,0,0,-4,4,0,4,0,0,0,0,-4,4,0,-4,0}

[0213] {0,0,0,0,2,1,0,-2,3,0,0,0,0,-2,3,0,-2,-1}, {0,0,0,0,-2,3,0,2,1,0,0,0,0,-2,3,0,-2,-1}

[0214] {0,0,0,0,2,1,0,-2,3,0,0,0,0,2,1,0,2,-3}, {0,0,0,0,-2,3,0,2,1,0,0,0,0,2,1,0,2,-3}

[0215] {0,0,0,0,4,0,0,-4,4,0,0,0,0,4,0,0,4,-4}, {0,0,0,0,-4,4,0,4,0,0,0,0,4,0,0,4,-4}

[0216] {0,0,0,0,4,0,0,-4,4,0,0,0,0,-4,0,0,-4,4}, {0,0,0,0,-4,4,0,4,0,0,0,0,0,-4,0,0,-4,4}

[0217] {0,0,0,0,2,1,0,-2,3,0,0,0,0,-2,-1,0,-2,3}, {0,0,0,0,-2,3,0,2,1,0,0,0,0,-2,-1,0,-2,3}

[0218] {0,0,0,0,2,1,0,-2,3,0,0,0,0,2,-3,0,2,1}, {0,0,0,0,-2,3,0,2,1,0,0,0,0,2,-3,0,2,1}

[0219] {0,0,0,0,4,0,0,-4,4,0,0,0,0,4,-4,0,4,0}, {0,0,0,0,-4,4,0,4,0,0,0,0,4,-4,0,4,0}

[0220] {0,0,0,0,-2,3,0,4,-1,0,0,0,0,-2,3,0,-4,1}, {0,0,0,0,4,0,0,-2,2,0,0,0,0,-4,4,0,-2,0}

[0221] {0,0,0,0,-4,4,0,2,0,0,0,0,0,4,0,0,2,-2}, {0,0,0,0,2,1,0,-4,3,0,0,0,0,2,1,0,4,-3}

[0222] By executing steps S251 to S252, the number and numerical range of solution basis data of each intersection solution space data are obtained, and the corresponding number of combined solution space data are obtained based on the number and numerical range. The combined solution space data is substituted into the preset solution algorithm for solution to obtain communication evaluation data, which greatly reduces the complexity of the calculation.

[0223] In addition, refer to Fig. 9 An embodiment of the present invention discloses a data processing device. The data processing device includes: an acquisition module 100, an analysis module 200, an acquisition unit 210, a conversion unit 220, a summary unit 230, an intersection unit 240 and a solution unit 250. Among them, the analysis module 200 includes: an acquisition unit 210, a conversion unit 220, a summary unit 230, an intersection unit 240 and a solution unit 250. The acquisition module 100, the analysis module 200, the acquisition unit 210, the conversion unit 220, the summary unit 230, the intersection unit 240 and the solution unit 250 are all communication connected.

[0224] The acquisition module 100 acquires communication transmission data. The analysis module 200 performs data analysis on the communication transmission data to obtain communication evaluation data. The acquisition unit 210 acquires sequence data of the communication transmission data. The conversion unit 220 performs linear operation conversion processing on the sequence data to obtain initial solution space data. The summary unit 230 summarizes the initial solution space data to obtain target solution space data. The intersection unit 240 acquires the data of the intersection in the target solution space data to obtain the intersection solution space data. The solution unit 250 performs solution processing on the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data.

[0225] The acquisition module 100 acquires the transmission data after the spatial matrix communication coding to obtain the communication transmission data, and the analysis module 200 solves and analyzes the correlation coefficient data of the communication transmission data to obtain the communication evaluation data. The analysis module 200 solves and analyzes the correlation coefficient data of the communication transmission data, including: first, the acquisition unit 210 acquires the autocorrelation equation of the communication transmission data to obtain the sequence data. Then, the conversion unit 220 linearizes the sequence data according to the quadratic coefficients of each sequence data, and reduces the sequence data to a linear equation system to obtain the initial solution space data. Secondly, the summary unit 230 obtains more solution space data of each sequence data, and summarizes the solution space data and the initial solution space data to obtain the target solution space data. Then, the intersection unit 240 obtains the data where all the target solution space data have intersections to obtain the intersection solution space data. Finally, the solution unit 250 solves the intersection solution space data according to the preset solution algorithm, and obtains the intersection solution space numerical solution to obtain the communication evaluation data.

[0226] The operation process of the data processing device of this embodiment is specifically described as above. Figure 1 and Figure 2 The data processing method steps S100 to S200 and steps S210 to S250 are not repeated here.

[0227] Another embodiment of the present invention discloses a data processing device, the data processing device comprising: at least one processor, and a memory connected to the at least one processor in communication; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute Figure 1 Steps S100 to S200 of the method, Figure 2 Steps S210 to S250 of the method, Figure 3 Steps S221 to S224 of the method, Figure 4 Step S2211 and step S2212 of the method, Figure 5 Steps S221 to S233 of the method, Figure 6 Steps S234 to S236 of the method, Figure 7 Steps S241 to S245 of the method and Figure 8 Any one of the data processing methods in step S251 and step S252 of the method.

[0228] Another embodiment of the present invention discloses a computer-readable storage medium, the computer-readable storage medium comprising: the computer-readable storage medium stores computer-executable instructions, the computer-executable instructions are used to enable a computer to execute Figure 1 Steps S100 to S200 of the method, Figure 2 Steps S210 to S250 of the method, Figure 3 Steps S221 to S224 of the method, Figure 4 Step S2211 and step S2212 of the method, Figure 5 Steps S221 to S233 of the method, Figure 6 Steps S234 to S236 of the method, Figure 7 Steps S241 to S245 of the method and Figure 8 Any one of the data processing methods in step S251 and step S252 of the method.

[0229] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0230] It will be appreciated by those skilled in the art that all or some of the steps and systems in the disclosed method above may be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or may be implemented as hardware, or may be implemented as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or a non-transitory medium) and a communication medium (or a temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that may be used to store desired information and may be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically embodies computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0231] The embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in the relevant technical field without departing from the purpose of the present invention. In addition, the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

Claims

1. A data processing method, characterized in that: include: Acquire the transmission data after the space matrix communication encoding to obtain the communication transmission data; Performing data analysis on the communication transmission data to obtain communication evaluation data; The performing data analysis on the communication transmission data to obtain communication evaluation data includes: Obtaining an autocorrelation equation of the communication transmission data to obtain sequence data; Performing linear operation conversion processing on the sequence data to obtain initial solution space data; Summarizing the initial solution space data to obtain target solution space data; Acquire the data of the intersection in the target solution space data to obtain the intersection solution space data; The intersection solution space data is processed according to a preset solution algorithm to obtain the communication evaluation data, wherein the communication evaluation data is a solution for generating perfect Gaussian integer sequence data, and the perfect Gaussian integer sequence data is used for communication channel estimation.

2. The data processing method according to claim 1, characterized in that: The performing linear operation conversion processing on the sequence data to obtain initial solution space data includes: Obtaining coefficient matrix data corresponding to the sequence data; The value of the coefficient matrix data is set to zero, and all solutions of the coefficient matrix data are obtained to obtain first solution space data, wherein the first solution space data includes a plurality of solution basis data, and each row of the first solution space data corresponds to one solution basis data in the plurality of solution basis data; Add any two of the solution basis data among a plurality of the first solution space data, and / or multiply the solution basis data by a preset scalar to obtain a calculation result, combine the solution basis data of the first solution space data and the calculation result to obtain second solution space data, wherein the calculation result is the solution basis data; All the first solution space data and all the second solution space data are combined into the initial solution space data.

3. The data processing method according to claim 2, characterized in that: The step of obtaining coefficient matrix data corresponding to the sequence data includes: The sequence data is expressed by a preset linear equation expression to obtain a target linear equation, wherein the preset linear equation expression is formed by combining preset parameters, a coefficient matrix and transposed data of the preset parameters; The coefficient matrix in the target linear equation is obtained to obtain the coefficient matrix data.

4. The data processing method according to claim 1, characterized in that: The summarizing and processing the initial solution space data to obtain target solution space data includes: Obtaining coefficient matrix data corresponding to the sequence data; Transposing the coefficient matrix data to obtain transposed matrix data; Setting the value of the transposed matrix data to zero and finding all solutions of the transposed matrix data to obtain third solution space data; The third solution space data and the initial solution space data are aggregated to obtain the target solution space data.

5. The data processing method according to claim 4, characterized in that: The step of aggregating the initial solution space data to obtain target solution space data further includes: Performing numerical conversion processing on preset diagonal data of the coefficient matrix data according to preset processing rules to obtain conversion matrix data; Setting the value of the transformation matrix data to zero and finding all solutions of the transformation matrix data to obtain fourth solution space data; The third solution space data, the fourth solution space data and the initial solution space data are aggregated to obtain the target solution space data.

6. The data processing method according to any one of claims 1 to 5, characterized in that: The obtaining of the data of the intersection in the target solution space data to obtain the intersection solution space data includes: Acquire two linearly related target solution space data; The two target solution space data are spliced ​​in column direction to obtain corresponding spliced ​​solution space data; Transposing the spliced ​​solution space data to obtain transposed solution space data; Cutting and transposing the preset columns of the transposed solution space data to obtain cut solution space data; The target solution space data is multiplied by the intercepted solution space data and the result is solved with the sum being zero to obtain the intersection solution space data.

7. The data processing method according to any one of claims 1 to 5, characterized in that: The processing of the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data includes: Acquire combined solution space data according to the intersection solution space data; The combined solution space data is solved according to the preset solution algorithm to obtain the communication evaluation data.

8. A data processing device, characterized in that: include: An acquisition module is used to acquire the transmission data after the space matrix communication encoding to obtain the communication transmission data; An analysis module, used for performing data analysis on the communication transmission data to obtain communication evaluation data; The analysis module comprises: An acquisition unit, used for acquiring an autocorrelation equation of the communication transmission data to obtain sequence data; A conversion unit, used for performing linear operation conversion processing on the sequence data to obtain initial solution space data; A summarizing unit, used for summarizing the initial solution space data to obtain target solution space data; An intersection unit, used to obtain the data of the intersection in the target solution space data to obtain the intersection solution space data; A solution unit is used to process the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data, wherein the communication evaluation data is a solution for generating perfect Gaussian integer sequence data, and the perfect Gaussian integer sequence data is used for communication channel estimation.

9. A data processing device, characterized in that: include: at least one processor, and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the data processing method according to any one of claims 1 to 7.

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