Single-complex-based regular ldpc matrix construction method, system and storage medium

Abstract

The application discloses a simplex-based regular LDPC matrix construction method and system and a storage medium. The method comprises the following steps: generating a maximum element vector set according to the length and weight of a simplex vector required by an LDPC matrix; generating a first simplex set determined by each maximum element; processing the first simplex set to obtain a required second simplex set; constructing the indexes of the rows and columns of the LDPC matrix; determining the values of the elements in the LDPC matrix according to the second simplex set; and constructing the LDPC matrix according to the indexes of the rows and columns of the LDPC matrix and the values of the elements in the LDPC matrix. The application solves the problems of additional elimination of a 4-ring, high construction complexity and low construction efficiency in the related art.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of information technology, and particularly relates to a simplex-based regular LDPC matrix construction method, system and storage medium. BACKGROUND

[0002] LDPC code is a kind of linear error correction code, and a parity check matrix thereof has low density, which can obviously improve the reliability and efficiency of a communication system.

[0003] Currently, a regular LDPC matrix is mainly generated by a random construction method, that is, a regular LDPC matrix satisfying requirements is randomly generated, but since the randomly generated matrix method cannot meet the requirement that no 4-cycle exists in the matrix, an algorithm needs to be additionally designed to detect and eliminate the 4-cycle through matrix transformation; and in the matrix transformation process, the regularity of the regular LDPC matrix may be damaged; when the code length increases, that is, the matrix scale increases, the complexity will exponentially increase, which seriously reduces the LDPC matrix construction efficiency.

[0004] In order to solve the problems that the existing regular LDPC matrix construction needs to additionally eliminate 4-cycles, has high construction complexity and low construction efficiency, a simplex-based regular LDPC matrix construction method, system and storage medium are provided. SUMMARY

[0005] The simplex-based regular LDPC matrix construction method, system and storage medium are provided to at least solve the problems that the related art needs to additionally eliminate 4-cycles, has high construction complexity and low construction efficiency.

[0006] According to one embodiment of the application, a simplex-based regular LDPC matrix construction method is provided, which comprises the following steps:

[0007] generating a set of maximum element vectors according to the length and weight of simplex vectors required by an LDPC matrix;

[0008] generating a first simplex set determined by each maximum element;

[0009] processing the first simplex set to obtain a required second simplex set;

[0010] constructing indexes of rows and columns of the LDPC matrix;

[0011] determining the values of elements in the LDPC matrix according to the second simplex set;

[0012] constructing the LDPC matrix according to the indexes of rows and columns of the LDPC matrix and the values of elements in the LDPC matrix.

[0013] In one example embodiment, the step of generating a set of maximum vectors according to the length and weight of a simplex vector required by a LDPC matrix comprises the steps of:

[0014] determining the total length l and the required maximum weight m of a simplex vector according to the target LDPC matrix; the weight is the Hamming weight;

[0015] listing all vectors with weight m in binary vectors with length l, i.e.

[0016] constructing a set of maximum vectors with fixed weight m

[0017] In one example embodiment, the step of generating a first simplex set determined by each maximum vector comprises the steps of:

[0018] each maximum vector A i corresponds to a simplex set

[0019] constructing a first simplex set according to the set of maximum vectors

[0020] In one example embodiment, the step of processing the first simplex set to obtain a required second simplex set comprises the steps of:

[0021] removing vectors with weight less than or equal to m-2 and the vectors corresponding to the maximum vectors in each

[0022] retaining all vectors with weight m-1 in each to obtain the required second simplex set

[0023] In one example embodiment, the step of constructing the indices of rows and columns of the LDPC check matrix comprises the steps of:

[0024] using the second simplex set as the indices of the rows of the LDPC check matrix H;

[0025] all vectors with weight m-1 form a set using the set as the indices of the columns of the LDPC check matrix H.

[0026] In one example embodiment, the step of determining the values of the elements in the LDPC matrix according to the second simplex set comprises the steps of:

[0027] judging the second simplex set ​​whether the set is contained in the vector element in

[0028] If yes, the position element corresponding to the row or column in the LDPC matrix takes the value of "1", otherwise takes the value of "0".

[0029] In an exemplary embodiment, the constructing the LDPC matrix according to the index of the row and column of the LDPC matrix and the value of each element in the LDPC matrix comprises the steps of:

[0030] The LDPC matrix H is a matrix of , wherein

[0031] determining the column element according to whether the set is contained in the vector element in and constructing the column of the LDPC matrix according to the column element;

[0032] determining the row element according to whether the vector of the set is contained in the second simplicial complex set and constructing the row of the LDPC matrix according to the row element;

[0033] verifying the constructed LDPC matrix H according to the row weight and the column weight; the row weight The column weight γ = l - m + 1.

[0034] In an exemplary embodiment, further comprising the step of: if the number of rows of the constructed LDPC matrix H is greater than the number of columns, calculating the transpose matrix of the LDPC matrix H as the regular LDPC check matrix.

[0035] According to another embodiment of the present application, a computer readable storage medium storing a computer program for electronic data exchange is provided, wherein the computer program performs the above method.

[0036] According to another embodiment of the present application, a simplicial complex-based regular LDPC matrix construction system is provided, comprising:

[0037] a processor;

[0038] a memory;

[0039] and

[0040] one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs cause the computer to perform the above method.

[0041] The simplicial complex-based regular LDPC matrix construction method, system and storage medium of the present application have the following advantages:

[0042] (1) The present application determines row weight, column weight and characteristics quickly according to the mathematical properties of simplexes, and can directly define parameter performance compared with the existing random construction technical solutions.

[0043] (2) The present application avoids the formation of 4-cycles according to the properties of simplexes, and can directly avoid the use of 4-cycle detection algorithm and 4-cycle elimination algorithm compared with the existing LDPC matrix construction technical solutions, and avoids changing the regular LDPC matrix into an irregular LDPC matrix in the link of eliminating cycles.

[0044] (3) The present application directly generates an LDPC matrix according to two sets determined by simplexes, and does not need subsequent multiple operations on the matrix compared with the random construction technical solutions, which significantly reduces the complexity and improves the construction efficiency of the regular LDPC matrix when the code length increases. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 is a flowchart of a regular LDPC matrix construction method based on simplexes according to an embodiment of the present application;

[0046] Figure 2 is a flowchart of sub-step S01 according to an embodiment of the present application;

[0047] Figure 3 is a flowchart of sub-step S02 according to an embodiment of the present application;

[0048] Figure 4 is a flowchart of sub-step S03 according to an embodiment of the present application;

[0049] Figure 5 is a flowchart of sub-step S04 according to an embodiment of the present application;

[0050] Figure 6 is a flowchart of sub-step S05 according to an embodiment of the present application

[0051] Figure 7 is a flowchart of sub-step S06 according to an embodiment of the present application;

[0052] Figure 8 is a regular LDPC matrix constructed when l=5 and m=2 according to an embodiment of the present application;

[0053] Figure 9 is a regular LDPC matrix constructed when l=6 and m=3 according to an embodiment of the present application;

[0054] Figure 10 is a system structure schematic diagram of a regular LDPC matrix construction method based on simplexes according to an embodiment of the present application. DETAILED DESCRIPTION

[0055] The application will be described in detail below with specific embodiments. The following examples will help those skilled in the art to further understand the application, but do not limit the application in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the application. These are within the scope of protection of the application.

[0056] The parity check matrix H of the regular LDPC code satisfies the following four properties:

[0057] (1) The number of "1"s in each row is called row weight, denoted as p.

[0058] (2) The number of "1"s in each column is called column weight, denoted as g.

[0059] (3) The number of "1"s in the common position of any two rows (or columns) is denoted as l, and l≤1.

[0060] (4) p and g are much smaller than the number of rows and columns, respectively.

[0061] Let be a finite ring of order 2, and n be a positive integer. For any vector , its support set suppv is defined as the set of non-zero coordinate positions. The Hamming weight of vector wt H (v) can be defined as: wt H (v) = |supp(v)|, that is, the size of the support set.

[0062] In addition, there is a bijective relationship between and the power set 2 [n] of the set [n] = {1,..., n}, which is defined as: This means that each vector v in corresponds to a subset in 2 [n] . For example, if there is a vector v = (1, 1, 0, 1, 0), then suppv = {1, 2, 4} and its Hamming weight wt H (v) = |supp(v)| = 3.

[0063] For any two vectors u, v in , when , it is considered that The set is called a simple complex if for u e A and , then v e A. For a simple complex A, the maximal element is an element that is not inside any other element in A.

[0064] Let is the set of all maximal elements of Δ. For each Simplex complex Δ generated by F F is the set of all subsets of F. In the embodiment of the present application, the Each vector in corresponds to its support set.

[0065] Let be a simplex complex, the n-ary generating function associated with the set Δ is:

[0066]

[0067] where

[0068] For example, if Δ is a simplex complex of and its maximal element set is then Correspondingly, |Δ| = 5, Δ = {0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1, 1}.

[0069] For another example, the vector v = 1, 1, 0, 1, 0 as a separate maximal element, its generating function Correspondingly, Δ = 8, at this time Δ = {0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0,

[0070] 1, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0}, according to the property of the simplex complex, there is no two identical maximal elements, each vector element can be judged whether it is contained in the simplex complex set by the support set mapping, that is, the vector is mapped into the relationship between the sets by the simplex complex.

[0071] After removing part of the elements, Δ = {1, 1, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 0}, at this time Δ = suppv = 3, under this relationship, all the simplex complexes produced by the maximal elements with weight 3 have at most one element in the intersection under the condition of only retaining the vectors with weight 2, thus mathematically ensuring that the constructed regular LDPC matrix does not exist 4-cycles, so that 4-cycles do not need to be eliminated, the complexity is greatly reduced and the construction efficiency is improved.

[0072] A simplex complex-based regular LDPC matrix construction method according to an embodiment of the present application, a flow chart is shown as Figure 1 , comprising the steps of:

[0073] Step S01, generating a maximal element vector set according to the length and weight of the simplex complex vector required by the LDPC matrix;

[0074] Step S02, generating a first simplicial complex set determined by each maximal element;

[0075] Step S03, processing the first simplicial complex set to obtain a required second simplicial complex set;

[0076] Step S04, constructing indexes of rows and columns of the LDPC matrix;

[0077] Step S05, determining values of elements in the LDPC matrix according to the second simplicial complex set;

[0078] Step S06, constructing the LDPC matrix according to the indexes of rows and columns of the LDPC matrix and the values of elements in the LDPC matrix.

[0079] In an exemplary embodiment, step S01 includes generating a maximal element vector set according to a length and weight of a required simplicial complex vector of the LDPC matrix, as shown in a flowchart Figure 2 , including steps of:

[0080] Step S011, determining a total length l of the simplicial complex vector and a required maximal element weight m according to the target LDPC matrix;

[0081] Step S012, listing all vectors with the weight m in binary vectors with the length l;

[0082] Step S013, constituting a maximal element vector set A with the fixed weight m.

[0083] In the embodiment, the total length l of the simplicial complex vector and the required maximal element weight m are determined according to the target LDPC matrix, where l and m are positive integers, and 1

[0084] For example, if l=5 and m=2, all vectors with the weight 2 in binary vectors with the length 5 are found, and there are totally maximal elements A with the weight 2 i , 1≤i≤10.

[0085] In an exemplary embodiment, step S02 includes generating a first simplicial complex set determined by each maximal element, as shown in a flowchart Figure 3 , including steps of:

[0086] Step S021, each maximal element vector corresponds to a simplicial complex set;

[0087] Step S022, obtaining the first simplicial complex set M according to the maximal element vector set.​

[0088] In this embodiment, each maximal vector A i Corresponding to a single complex set According to the first set of maximal vectors to get a simple complex set

[0089] For example, as an example of extraction A1 = 0, 0, 0, 1, 1, at this time the simple complex generated by A1 The first set of simple complex Composed of all .

[0090] In an exemplary embodiment, step S03, processing the first set of simple complex to get the required second set of simple complex, flow chart as Figure 4 Shown, including the steps:

[0091] Step S031, remove each simple complex set in the weight is less than or equal to m-2 and the corresponding vector of the maximal vector;

[0092] Step S032, all vectors with weight m-1 are retained, thereby obtaining the required second set of simple complex.

[0093] In this embodiment, all vectors with weight wt(v) = m-1 constitute the set Wherein Remove the vector and the corresponding vector of the maximal vector in the weight is less than or equal to m-2, and retain all vectors with weight m-1, to obtain At this time In this way, the required second set of simple complex is obtained For example, after processing

[0094] Obtained In this way, the second set of simple complex Can be obtained

[0095] In an exemplary embodiment, step S04, constructing the index of the row and column of the LDPC check matrix, the flow chart as Figure 5 Shown, including the steps:

[0096] Step S041, the second set of simple complex is used as the index of the row of the LDPC check matrix H;

[0097] Step S042, the set V composed of vectors with weight m-1 is used as the index of the column of the LDPC check matrix H.

[0098] In this embodiment, the second set of simple complex an index of a row of the LDPC check matrix H; a set of vectors with weight m-1 an index of a column of the LDPC check matrix H.

[0099] Example,

[0100]

[0101] an index of a row of the LDPC check matrix H corresponding to v1~v5, i.e. the column elements of the LDPC check matrix H are constructed according to v1~v5.

[0102] a set of all vectors with weight wt(v)=m-1=1 v2=0,0,0,1,0, v3=(0,0,1,0,0), v4=(0,1,0,0,0), v5=(1,0,0,0,0)}, an index of a column of the LDPC check matrix H corresponding to v1~v5, i.e. the column elements of the LDPC check matrix H are constructed according to v1~v5.

[0103] In one exemplary embodiment, the step S05 of determining the value of each element in the LDPC matrix according to whether the corresponding vector element is contained in the second simplicial complex set, the flow chart is shown as Figure 6 , comprising the steps of:

[0104] Step S051, judging whether the vector element in the set is contained in the second simplicial complex set;

[0105] Step S052, if yes, the position element of the corresponding row or column in the LDPC matrix takes the value of "1", otherwise, the value is "0".

[0106] In this embodiment, it is judged whether the corresponding vector element in the set is contained in the second simplicial complex set ; if the corresponding vector element is contained, the position element of the corresponding row or column in the LDPC matrix takes the value of "1", otherwise, the value is "0".

[0107] Example, for the simplicial complex in the second simplicial complex set, it contains v1=0,0,0,0,1 and v2=0,0,0,1,0, therefore, the elements of the first column of the first row and the first column of the second row in the LDPC matrix take the value of "1", and the remaining elements of the first column take the value of "0".

[0108] ​In one example embodiment, the step S06 of constructing the LDPC matrix according to the indexes of the rows and columns of the LDPC matrix and the values of the elements in the LDPC matrix comprises the steps of: Figure 7 as shown in the flow chart, comprising the steps of:

[0109] Step S061 of determining the column elements according to whether the vectors in the set V are contained in the second simplicial complex set and constructing the columns of the LDPC matrix according to the column elements;

[0110] Step S062 of determining the row elements according to whether the vectors in the set V are contained in the second simplicial complex set and constructing the rows of the LDPC matrix according to the row elements;

[0111] Step S063 of verifying the constructed LDPC matrix H according to the row weight and the column weight.

[0112] In this embodiment, the LDPC matrix H is a matrix of According to whether the vectors in the set V are contained in the second simplicial complex set the column elements are determined to be 1 or 0 according to whether the vectors in the set V are contained in the second simplicial complex set the row elements are determined to be 1 or 0 according to whether the set V of vectors with weight m-1 is contained in the second simplicial complex set , and the rows of the LDPC matrix are constructed according to the row elements, so as to construct the LDPC matrix. The constructed LDPC matrix H is verified according to the row weight and the column weight; the row weight The column weight γ = l-(m-1) = l-m+1. In an example, the column elements are determined to be 1 or 0 according to whether the vectors in the set V are contained in the second simplicial complex set

[0113] The row elements are determined to be 1 or 0 according to whether the vectors in the set V are contained in the second simplicial complex set , and the rows of the LDPC matrix are constructed according to the row elements, so as to obtain the LDPC matrix. As shown in Figure 8 , the regular LDPC check matrix constructed when l = 5 and m = 2 is shown.

[0114] In one example embodiment, the method further comprises the step of: if the number of rows of the constructed LDPC matrix H is greater than the number of columns, calculating the transpose matrix of the LDPC matrix H as the regular LDPC check matrix.

[0115] ​​​​In this embodiment, generally, since the linear code has three main parameters: code length n, dimension k, minimum distance d, the check matrix is an (n-k) x n matrix, so when constructing, a matrix with the number of rows less than the number of columns is selected as the regular LDPC check matrix. If the number of rows of the LDPC matrix H constructed according to the method described in the embodiment is greater than the number of columns, the transpose matrix of the LDPC matrix H is calculated as the regular LDPC check matrix, and the row and column parameters of the transpose matrix H T of the LDPC matrix H are opposite to those of H.

[0116] In another example, if the total length l = 6 of the simple complex vector is determined according to the target LDPC matrix, the required maximum element weight m = 3, at this time, the required second simple complex set

[0117]

[0118] The vector set with all weights of 2 v2 = 0, 0, 0, 1, 0, 1, v3 = 0, 0, 0, 1, 1, 0, v4 = 0, 0, 1, 0, 0, 1, v5 = 0, 0, 1, 0, 1, 0, v6 = 0, 0, 1, 1, 0, 0, v7 =

[0119] 0, 1, 0, 0, 0, 1, v8 = 0, 1, 0, 0, 1, 0, v9 = 0, 1, 0, 1, 0, 0, v 10 = 0, 1, 1, 0, 0, 0, v 11 =

[0120] 1, 0, 0, 0, 0, 1, v 12 = 1, 0, 0, 0, 1, 0, v 13 = 1, 0, 0, 1, 0, 0, v 14 = 1, 0, 1, 0, 0, 0, v 15 = 1, 1, 0, 0, 0, 0}.

[0121] According to whether the vector set is contained in the second simple complex set , the column element is determined to be 1 or 0, and the column of the LDPC matrix is constructed in this way; according to whether the vector set is contained in the second simple complex set , the row element is determined to be 1 or 0, and the row of the LDPC matrix is constructed in this way, so as to obtain the LDPC matrix, as shown in Figure 9 , which is a regular LDPC matrix constructed when l = 6 and m = 3.

[0122] A computer readable storage medium of an embodiment of the present application stores a computer program for electronic data exchange, wherein the computer program causes a computer to execute the method of the above-mentioned embodiments. The computer readable storage medium of the present embodiment can be any one or more of a storage medium of a communication client, a storage medium of a communication cloud server, a storage medium of a communication background server, or a storage medium of a database.

[0123] A simplex-based regular LDPC matrix construction system of an embodiment of the present application has a structural schematic diagram as shown in Figure 10

[0124] a processor;

[0125] a memory;

[0126] and

[0127] one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs cause the computer to execute the method of the above-mentioned embodiments. The processor can be any one or more of a processor of a communication client, a processor of a communication cloud server, a processor of a communication background server, or a processor of a database.

[0128] Of course, those skilled in the art should recognize that the above embodiments are only used to illustrate the present application, and are not intended to limit the present application, and any changes and modifications to the above embodiments within the scope of the present application will fall within the scope of the present application.​

Claims

1. A computer readable storage medium storing a computer program for electronic data interchange, wherein, The computer program makes a computer execute a simplex-complexity-based regular LDPC matrix construction method, and the computer readable storage medium is any one or more of a storage medium of a communication client, a storage medium of a communication cloud server, a storage medium of a communication background server, or a storage medium of a database; the simplex-complexity-based regular LDPC matrix construction method comprises: According to the length and weight of the simplex complex vector required by the LDPC matrix, a set of maximum element vectors is generated; the step of generating the set of maximum element vectors according to the length and weight of the simplex complex vector required by the LDPC matrix comprises the steps that the total length l and the required maximum element weight m of the simplex complex vector are determined according to the target LDPC matrix; the weight is the Hamming weight; all vectors with the weight m are listed in the binary vector with the length l, that is ; a set of maximum element vectors with the fixed weight m is constituted ; Generating a first set of simplexes determined by each maximal element; the generating a first set of simplexes determined by each maximal element comprises the step of: each maximal element vector Ai corresponds to a set of simplexes , ; obtaining a first set of simplexes from the set of maximal element vectors ; Processing the first set of simplexes to obtain the desired second set of simplexes; the process of processing the first set of simplexes to obtain the desired second set of simplexes includes the step of: removing each Vectors with weights less than or equal to m-2 and vectors corresponding to maximal elements; retain each Given all vectors with weight m-1, we obtain This yields the desired second simplex complex set. ; constructing indexes of rows and columns of the LDPC matrix; the step of constructing the indexes of rows and columns of the LDPC matrix comprises the step of: constructing a second simple complex set a set of vectors with all weights of m-1 as indexes of rows of the LDPC matrix H constructing a set of vectors with all weights of m-1 as indexes of columns of the LDPC matrix H a set of vectors with all weights of m-1 as indexes of columns of the LDPC matrix H The values of elements in the LDPC matrix are determined according to the second simplex complex set; the step of determining the values of elements in the LDPC matrix according to the second simplex complex set comprises the steps of judging whether the vector elements in the set are contained in the second simplex complex set; if yes, the position elements corresponding to the rows or columns in the LDPC matrix are valued as "1", otherwise, the values are "0". ​​ The LDPC matrix is constructed according to indexes of rows and columns of the LDPC matrix and values of elements in the LDPC matrix; the LDPC matrix is constructed according to indexes of rows and columns of the LDPC matrix and values of elements in the LDPC matrix, comprising: the LDPC matrix H is a matrix of , wherein , ; column elements are determined according to whether a set of vectors in a second simplicial complex set contains a set of vectors in , and columns of the LDPC matrix are constructed according to the column elements; row elements are determined according to whether a set of vectors in a set is contained in the second simplicial complex set , and rows of the LDPC matrix are constructed according to the row elements; the constructed LDPC matrix H is verified according to row weights and column weights; the row weight ; and the column weight ; If the number of rows of the constructed LDPC matrix H is greater than the number of columns, a transposed matrix of the LDPC matrix H is calculated as a regular LDPC matrix.

2. A simplicial complex based regular LDPC matrix construction system, characterized by comprise: a processor; the processor is any one or more of a processor of a communication client, a processor of a communication cloud server, a processor of a communication background server, or a processor of a database; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the programs make a computer execute a simplex-complexity-based regular LDPC matrix construction method, and the simplex-complexity-based regular LDPC matrix construction method comprises: According to the length and weight of the simplex complex vector required by the LDPC matrix, a set of maximum element vectors is generated; the step of generating the set of maximum element vectors according to the length and weight of the simplex complex vector required by the LDPC matrix comprises the steps that the total length l and the required maximum element weight m of the simplex complex vector are determined according to the target LDPC matrix; the weight is the Hamming weight; all vectors with the weight m are listed in the binary vector with the length l, that is ; a set of maximum element vectors with the fixed weight m is constituted ; generating a first set of simplexes determined by each maximal element; the generating a first set of simplexes determined by each maximal element comprises the step of: each maximal element vector Ai corresponds to a set of simplexes , ; obtaining a first set of simplexes according to the maximal element vector set ; The first simplicial complex is processed to obtain a required second simplicial complex; the processing of the first simplicial complex to obtain the required second simplicial complex comprises the steps of: removing vectors corresponding to maximal elements in the sum of vectors with weights less than or equal to m-2; and retaining all vectors with weights equal to m-1 to obtain a set of vectors with weights equal to m-1 . Thus, the required second simplicial complex is obtained . constructing indexes of rows and columns of the LDPC matrix; the step of constructing the indexes of rows and columns of the LDPC matrix comprises the step of: constructing a second simple complex set a set of vectors with all weights of m-1 as indexes of rows of the LDPC matrix H constructing a set a set of vectors with all weights of m-1 as indexes of columns of the LDPC matrix H The values ​​of each element in the LDPC matrix are determined based on the second simplex set; the determination of the values ​​of each element in the LDPC matrix based on the second simplex set includes the following steps: determining the second simplex set. Does it contain a set? If the vector element is a vector element, then the element at the corresponding row or column position in the LDPC matrix is ​​set to "1"; otherwise, it is set to "0". The LDPC matrix is constructed according to indexes of rows and columns of the LDPC matrix and values of elements in the LDPC matrix; the LDPC matrix is constructed according to indexes of rows and columns of the LDPC matrix and values of elements in the LDPC matrix, comprising: the LDPC matrix H is a matrix of , wherein , ; column elements are determined according to whether the second simple complex set contains the vector in the set , and columns of the LDPC matrix are constructed according to the column elements; row elements are determined according to whether the vector in the set is contained in the second simple complex set , and rows of the LDPC matrix are constructed according to the row elements; the constructed LDPC matrix H is verified according to row weights and column weights; the row weight ; the column weight ; If the number of rows of the constructed LDPC matrix H is greater than the number of columns, a transposed matrix of the LDPC matrix H is calculated as a regular LDPC matrix.

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