LDPC-Hadamard complete sequence coding method suitable for anti-interference communication

Abstract

The invention discloses an LDPC-Hadamard complete sequence coding method suitable for anti-interference communication. The LDPC-Hadamard complete sequence coding method comprises the following steps: constructing a protograph LDPC-Hadamard code with a given target code length and code rate; the method comprises the following steps: inserting an SPC node and a newly added Hadamard variable node of which the degree is 2 between an LDPC variable node and a Hadamard check node in a protograph LDPC-Hadamard code Tanner graph, so as to form a new connection relationship; and traversing all the LDPC variable nodes to form an LDPC-Hadamard complete sequence code. The full-sequence coding method has the characteristic of Hadamard full-sequence transmission, so that anti-interference decoding can be carried out by utilizing the full-sequence characteristics of code words. In a typical Gaussian white noise channel, the performance of the scheme provided by the invention is similar to that of an original scheme, and in an interference channel, the complete sequence scheme provided by the invention has an obvious anti-interference advantage.

Description

Technical Field

[0001] The invention belongs to the technical field of communication, and in particular relates to an LDPC-Hadamard full sequence coding method suitable for anti-interference communication. Background Art

[0002] Early communication technologies were mainly simple modulation methods (such as AM and FM), which had limited resistance to interference. External noise, electromagnetic interference (EMI), and aliasing of other signals were the main threats to communication systems. At that time, anti-interference measures were mainly concentrated in the analog communication stage (radio broadcasting and early telephone systems, etc.). Due to technical limitations, anti-interference strategies mainly used simple hardware and signal design methods to enhance communication reliability. The core goal of these measures is to deal with environmental noise, electromagnetic interference, and limited interference signals. The main anti-interference measures are to increase signal power and improve antenna directivity.

[0003] With the emergence of digital communication, new directions have been brought to anti-interference technology, mainly including error correction coding (such as Hamming code, LDPC code), spread spectrum communication (DSSS, FHSS). Through signal coding, modulation, spread spectrum and other methods, the sensitivity of communication systems to interference is reduced and the reliability is significantly improved.

[0004] As a very special type of linear block code, LDPC code has excellent performance close to the Shannon limit. Its structure is composed of the check matrix Uniquely determined. It should be noted that the check matrix of the LDPC code is composed of "0" and "1", where the number of "1" is much smaller than the number of "0", and it is sparse, describing the linear relationship from the message bit to the check bit. There are two basic decoding algorithms for LDPC codes, namely the BF algorithm and the BP algorithm. The BF algorithm is the basis of the hard decision decoding mode. During the decoding process, only the information after the decision ("0" or "1") is used for iterative decoding. The BP algorithm is the basis of the soft decision decoding mode. During the iterative decoding process, the probability likelihood information extracted from the channel is used for iterative decoding. The decoding complexity of LDPC is low, which is suitable for parallel decoding, and high-throughput transmission can be achieved through fully parallel decoding. Therefore, LDPC codes can meet the high throughput and high reliability requirements of 5G.

[0005] In a typical BPSK Gaussian white noise channel, the LDPC-Hadamard hybrid coding and decoding method disclosed in the patent with publication number CN118868975A, whose LDPC-Hadamard code replaces the parity check constraint of the LDPC code with the Hadamard constraint and comes with additional Hadamard variable nodes, has excellent coding gain, but under interference conditions, its performance is not ideal due to the lack of corresponding anti-interference decoding mechanism. Summary of the invention

[0006] The present invention aims to solve one of the technical problems existing in the related art at least to a certain extent.

[0007] An object of the present invention is to provide an LDPC-Hadamard full-sequence coding method suitable for anti-interference communication, which makes anti-interference decoding of low-code-rate LDPC-Hadamard possible by utilizing the orthogonality and spread spectrum characteristics of the full-sequence Hadamard code, thereby significantly improving the anti-interference performance.

[0008] Another object of the present invention is to provide a decoding method corresponding to the above encoding method.

[0009] To this end, the present invention provides, on one hand, an LDPC-Hadamard full sequence coding method suitable for anti-interference communication, comprising: Construct the original model graph LDPC-Hadamard code with given target code length and code rate; Insert an SPC node (Single-Parity-Check) and a newly added Hadamard variable node between the LDPC variable node and the Hadamard check node in the Tanner graph of the original LDPC-Hadamard code to form a new connection relationship; All LDPC variable nodes are traversed until the entire Tanner graph completes the structural transformation and forms the LDPC-Hadamard full sequence code.

[0010] Preferably, after the entire Tanner graph completes the structural transformation, the Tanner graph consists of LDPC variable nodes, SPC nodes, Hadamard check nodes, original Hadamard variable nodes with a degree of 1, and newly added Hadamard variable nodes with a degree of 2.

[0011] Preferably, after the entire Tanner graph completes the structural transformation, the LDPC variable nodes of the Tanner graph are used as implicit variable nodes and are not sent to the channel; the original Hadamard variable nodes with degree 1 and the newly added Hadamard variable nodes with degree 2 are sent to the channel as encoding codewords.

[0012] As a preferred option, the check matrix of the LDPC-Hadamard full sequence code is Indicates that Represents the number of Hadamard check nodes, represents the number of hidden variable nodes, and the check matrix The weight of each row d c Are equal.

[0013] As a preference, the length of the complete LDPC-Hadamard full sequence encoding codeword is ,in ，r Represents the order of the Hadamard code.

[0014] Preferably, an SPC node and a newly added Hadamard variable node are inserted between the LDPC variable node and the Hadamard check node in the original model LDPC-Hadamard code Tanner graph to form a new connection relationship; the specific method is: Select the LDPC variable node in the original model LDPC-Hadamard coded Tanner graph, and cut off any edge connected to the Hadamard check node; Insert an SPC node at the cut edge, and add a Hadamard variable node with a degree of 2 between the SPC node and the Hadamard check node, so that the LDPC variable node is connected to the newly added Hadamard variable node through the SPC node; The newly added Hadamard variable node with degree 2 is connected to the disconnected Hadamard check node and sent to the channel as a coded codeword.

[0015] Preferably, the encoding codeword is Hadamard sequences, each of which is taken from the codewords in the Hadamard codeword space. is the number of Hadamard check nodes.

[0016] Another aspect of the present invention provides an LDPC-Hadamard full sequence decoding method suitable for anti-interference communication, comprising: Initialize the Hadamard check node information of the LDPC-Hadamard full sequence code and the implicit variable node information of the LDPC-Hadamard full sequence code according to the channel reception value; Update the Hadamard check node information of the LDPC-Hadamard full sequence code; Update the implicit variable node information of the LDPC-Hadamard full sequence code; Based on the implicit variable node information of the LDPC-Hadamard full sequence code, a decoding decision is made, and the number of iterations increases by one; if the decoding decision is successful, the decoding is terminated, otherwise it enters the next round of iteration process.

[0017] Preferably, the initializing the Hadamard check node information of the LDPC-Hadamard full sequence code comprises the following steps: For a given Hadamard code order r , channel reception vector The length is ,and . Handle vector Assign the values ​​to the matrix No. j OK, complete the j The channel information of the Hadamard check nodes (including the channel information of the Hadamard variable nodes with degree 1 and the channel information of the Hadamard variable nodes with degree 2) is assigned, No. j The line is ; Initialize the prior information matrix of the Hadamard check node (External information passed from the implicit variable node to the Hadamard check node), set all its values ​​to 0, where Indicates that when decoding i The hidden variable node is passed to the j The external information of a Hadamard check node.

[0018] Preferably, the initialization of the implicit variable node information of the LDPC-Hadamard full sequence code includes: Initialize the prior information matrix of the hidden variable node (External information passed from the Hadamard check node to the hidden variable node), set all its values ​​to 0, where Indicates that when decoding j The Hadamard check node is passed to the i The external information of a hidden variable node.

[0019] Preferably, the process of updating the Hadamard check node information of the LDPC-Hadamard full sequence code includes: Traverse all Hadamard check nodes ( j =1,2,…, m ), using the channel information of the Hadamard variable node with degree 1, the channel information of the Hadamard variable node with degree 2 and the prior information of the Hadamard check node as input, and sending it to the Hadamard anti-interference APP decoding module, which calculates and outputs the external information transmitted by the Hadamard check node to the implicit variable node (No. j The Hadamard check node is passed to the i The specific steps are: make is the subscript vector (Hadamard code information bit subscript vector). No. j Line save Middle j The subscripts of the non-zero elements in the row and The elements of each row are arranged in order. No. j The row stores j The complete prior information required for the Hadamard check node to be updated is the matrix No. j The row stores j The complete posterior information generated by the Hadamard check node after updating is initialized. and Set to all 0s.

[0020] For j Hadamard check nodes, in u When iterating, The subscript belongs to x The value of the element is assigned to No. j Subscript in row belongs to For example, when r =3, , ,but , , , .but: ; in: ; represents the covariance matrix of the signal after interference and noise are mixed, represents the inner product of two vectors, express r Hadamard matrix of order No. List, represents taking the real part of a complex number, The order is r The Hadamard codeword k Bit.

[0021] Then put The subscript belongs to x Assign the values ​​of the elements of the matrix No. jRow subscript belongs to The method is the same as above.

[0022] In the u At the iteration, j The Hadamard check node is passed to the i The external information of a hidden variable node is: .

[0023] Preferably, the updating of the implicit variable node information of the LDPC-Hadamard full sequence code comprises the following steps: Based on the belief propagation algorithm, the prior information of the hidden variable node input is used to calculate the external information passed to the Hadamard check node by the hidden variable node ( i The hidden variable node is passed to the j The external information of a Hadamard check node is: ; in, Indicates that except for j In addition to the Hadamard check nodes, i The hidden variable nodes are a set of Hadamard check nodes connected by SPC nodes.

[0024] Yet another aspect of the present invention provides a non-transitory computer-readable storage medium having computer instructions stored thereon, the computer instructions enabling a computer to execute the above-mentioned LDPC-Hadamard full sequence coding method suitable for anti-interference communication.

[0025] Yet another aspect of the present invention provides an electronic device, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus, and the processor calls the logic instructions in the memory to execute the above-mentioned LDPC-Hadamard full sequence coding method suitable for anti-interference communication.

[0026] On the other hand, the present invention provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the above-mentioned LDPC-Hadamard full sequence coding method suitable for anti-interference communication.

[0027] Beneficial effects: The LDPC-Hadamard full-sequence coding method suitable for anti-interference communication of the present invention utilizes the orthogonality and spread spectrum characteristics of the full-sequence Hadamard code to make anti-interference decoding of low-code-rate LDPC-Hadamard possible, and the anti-interference performance is significantly improved.

[0028] Compared with the existing LDPC-Hadamard coding technology, in a typical BPSK Gaussian white noise channel, the coding method proposed in the present invention has similar performance to the original LDPC-Hadamard coding technology. In an interference channel, since the codewords sent to the channel by this coding scheme are segments of Hadamard sequences, they can be regarded as a spread spectrum sequence, and spread spectrum technology can be used to suppress interference, the full sequence scheme proposed in the present invention has obvious anti-interference advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a flowchart of the LDPC-Hadamard full sequence coding method suitable for anti-interference communication in Example 1; Figure 2 It is a flowchart of the LDPC-Hadamard full sequence decoding method suitable for anti-interference communication in Example 2; Figure 3 This is a diagram showing the traditional LDPC Tanner graph technology; Figure 4 This is a diagram showing the Tanner graph technology for traditional LDPC-Hadamard; Figure 5 A diagram showing a new connection relationship between the left variable node and the Hadamard check node; Figure 6 A display diagram showing the structural transformation of the entire Tanner graph by traversing all left variable nodes; Figure 7 A comparison diagram comparing the Tanner graph of the LDPC-Hadamard full sequence coding scheme of the present invention with the Tanner graph of a traditional LDPC-Hadamard scheme; Figure 8 This is the decoding process of the LDPC-Hadamard full sequence decoding method proposed by the present invention. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments, and they should not be understood as limitations on the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In the description of the present invention, it should be understood that the terms used are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0031] Before describing the technical solution of the present invention in detail through specific embodiments, it is necessary to first introduce the knowledge points that may be involved in this application.

[0032] LDPC code is a linear block code that can be used as a linear block code ( n , k ) is defined, where n represents the length of the LDPC code, k Represents the number of information bits, which can be generated by encoding m = n - k check bits, each of which is obtained by using the k The code rate of LDPC code is obtained by performing different linear operations on each information bit. Rate = k / n There are two common ways to express LDPC codes nowadays. The first method is to use a check matrix, and the second method is a Tanner graph. The two are essentially the same. The check matrix of the LDPC code is a binary matrix. The number of "0" elements in this binary matrix is ​​much larger than the number of "1" elements. It has "sparseness", which is also the origin of LD (Low-Density) in the name of the LDPC code. Consider each column of the LDPC check matrix as a variable node, and each row of the LDPC check matrix as a check node. If the matrix i Line j If the element of the column is 1, it means i The check node and j The variable nodes are connected. If an edge is connected between them, a Tanner graph is formed, such as Figure 3 The Tanner graph of the LDPC is shown.

[0033] There are many LDPC coding methods. In engineering, in order to facilitate coding, an LDPC check matrix with a certain structure is designed, so that the coding complexity can be greatly reduced. In the present invention, the coding technology used is Gaussian elimination. This method uses the LDPC check matrix to Perform row and column transformation so that the original check matrix becomes as follows: ; According to the relationship between the generator matrix and the check matrix, the generator matrix is ​​obtained as follows: ; Finally, according to the coding rules of linear block codes, the information bits are right-multiplied by the generator matrix to obtain the LDPC codeword; Hadamard Matrix It is composed of "+1" and "-1". n × n A square matrix, and any different rows and columns in the matrix are orthogonal. The inner product of any row or column with itself is n The Hadamard matrix is ​​given by The loop is recursively generated as follows: ; in , r is the order of the Hadamard matrix, and also the order of the Hadamard code. The Hadamard codeword is A row or column of , In the present invention, if not specifically stated, Hadamard code refers to a biorthogonal system Hadamard code.

[0034] Information bit , if you want to use this information bit sequence b There is a simple way to generate a system Hadamard code: b (0) is 0, then s for[ b ( r ) b ( r -1)... b (1)] is represented in decimal, then the generated systematic Hadamard code is for No. s Column, if b (0)=1, then s for[ b (1) b (2)... b (r )] is a decimal representation of the system Hadamard code generated c for No. s List.

[0035] The above description is crucial to understanding the present invention and is an important supplement to the present invention.

[0036] Combine the following Figure 1-Figure 8 The present invention describes an LDPC-Hadamard full sequence coding method suitable for anti-interference communication.

[0037] Example 1: Figure 1 As shown, this embodiment provides an LDPC-Hadamard full sequence coding method suitable for anti-interference communication. It includes the following steps: S110, constructing an original graph LDPC-Hadamard code with given parameters based on the existing original graph LDPC-Hadamard code construction method.

[0038] Assuming the code length is 14 and the code rate is 2 / 7, the LDPC-Hadamard code constructed based on the existing original model graph LDPC-Hadamard code construction method is: ; Its Tanner diagram is as follows Figure 4 shown.

[0039] S120. Cut off any edge of the left variable node (i.e., LDPC variable node, which is located on the left side of the Tanner graph of this embodiment, and is referred to as the left variable node hereinafter for the convenience of explanation) connected to the Hadamard check node, and insert an SPC node and a right variable node (i.e., Hadamard variable node, which is located on the right side of the Tanner graph of this embodiment, and is referred to as the right variable node hereinafter for the convenience of explanation) with a newly added degree of 2, so that the left variable node is connected to the newly added right variable node through the SPC, and the newly added right variable node is simultaneously connected to the cut Hadamard node and sent to the channel.

[0040] In this embodiment, Figure 4 The left variable node of v 1 and Hadamard check node H 1. H 2, and insert two SPC nodes and two newly added right variable nodes at the same time, so that the left variable node is connected to the newly added right variable node through SPC, and the two newly inserted right variable nodes are connected to the Hadamard check node. v1 becomes an implicit variable node and is no longer sent to the channel. The structure changes as follows Figure 5 shown.

[0041] S130, repeat step S120, and repeatedly perform the above operation on all left variable nodes until completion v 2. v 3. v 4. v 5. v By cutting off the 6 edges, we get a LDPC-Hadamard full sequence code, such as Figure 6 As shown, the transmitted codeword is composed of the right variable nodes, while all the left variable nodes become implicit variable nodes and are no longer transmitted.

[0042] In order to better understand the LDPC-Hadamard full sequence coding method suitable for anti-interference communication proposed in the present invention, the LDPC-Hadamard full sequence coding scheme of the present invention will be compared with the existing LDPC-Hadamard coding scheme.

[0043] like Figure 7 As shown, the codeword sent to the channel by the existing LDPC-Hadamard coding scheme is composed of two parts, one part is the left variable node (LDPC variable node) of LDPC-Hadamard, and the other part is the right variable node of LDPC-Hadamard (which is expressed as a partial sequence of Hadamard codewords without information bits, that is, a Hadamard variable node with a degree of 1). The codewords sent by the LDPC-Hadamard full sequence coding scheme proposed in the present invention are all Hadamard codeword sequences (including Hadamard variable nodes with a degree of 1 and Hadamard variable nodes with a degree of 2). Because in the LDPC-Hadamard full sequence coding scheme, the LDPC variable nodes are not sent directly to the channel, but are connected to the SPC nodes to form the information bits of the Hadamard codewords, and are indirectly sent to the channel, so in this LDPC-Hadamard full sequence coding scheme, the LDPC variable nodes are also called implicit variable nodes. In terms of decoding, the messages of the existing LDPC-Hadamard coding scheme are directly propagated between LDPC variable nodes and Hadamard check nodes, while the information of the LDPC-Hadamard full sequence coding scheme proposed in the present invention is propagated between hidden variable nodes and Hadamard variable nodes with degree 2 through SPC nodes.

[0044] Embodiment 2: Since the LDPC-Hadamard full sequence coding scheme proposed in the present invention belongs to a generalized LDPC code, its decoding process is similar to that of the LDPC code, including implicit variable node update and Hadamard variable node update.

[0045] like Figure 2 As shown, this embodiment provides an LDPC-Hadamard full sequence decoding method suitable for anti-interference communication. The overall steps are as follows: S210: Initialize Hadamard check node information and LDPC-Hadamard implicit variable node information of the LDPC-Hadamard full sequence code according to the channel reception value; S220: Update Hadamard check node information of the LDPC-Hadamard full sequence code; S230: Update the implicit variable node information of the LDPC-Hadamard full sequence code; S240: Based on the implicit variable node information of the LDPC-Hadamard full sequence code, a decoding decision is made, and the number of iterations increases by one. If the decoding decision is successful, the decoding is terminated, otherwise the next round of iteration process is entered.

[0046] The following still takes the LDPC-Hadamard full sequence code of Example 1 as an example to describe in detail the steps of the decoding method.

[0047] like Figure 6 As shown, for the LDPC-Hadamard full sequence code shown above, the order of the Hadamard code is 3. For step S210, the specific steps are: S211. It is known that the order of the Hadamard code is 3, so the channel receiving vector y The length is ,and . Handle vector y j Assign the values ​​to the matrix No. j OK, complete the j The channel information of the Hadamard check nodes (including the channel information of the Hadamard variable nodes with degree 1 and the channel information of the Hadamard variable nodes with degree 2) is assigned, and No. j The row is represented as ; S212, initialize the prior information received by the Hadamard check node: .

[0048] S213, initialize the prior information received by the implicit variable node: .

[0049] S220 is described in detail using the first Hadamard check node: is the subscript vector (Hadamard code information bit subscript vector), the matrix The first line of The subscripts of the non-zero elements in the first row of the matrix are arranged in order. The first row of stores the complete prior information required for the first Hadamard check node to be updated. The first row of stores the complete posterior information generated by the first Hadamard check node after updating. and Set to all 0. Represented as a matrix In the first line of Represented as a matrix No. 1 in line i Elements of a column.

[0050] For the first Hadamard check node, u When iterating, The subscript belongs to x The value of the element is assigned to The subscripts in row 1 belong to The value of the element of ,but , ,but: ; in: ; Then put The subscript belongs to x Assign the values ​​of the elements of the matrix Subscript row 1 belongs to The method is the same as above.

[0051] Based on the above description, in u In the iteration, the external information transmitted by the first Hadamard check node to the hidden variable node connected to it is: ; In step S230, u At the iteration, i The external information transmitted by a hidden variable node to the Hadamard check node connected to it is: ; in Indicates i The set of Hadamard check nodes connected by SPC nodes to the hidden variable nodes, Indicates that except for j Hadmard check node, and i The hidden variable nodes are a set of Hadamard check nodes connected by SPC nodes.

[0052] In step S204, u At the iteration, i The decoding process of hidden variable nodes can be expressed as follows: ; when When it is greater than 0, i The hidden variable node is judged as 0, otherwise it is judged as 1. And the decoding sequence is set to ,if Satisfy the judgment conditions , it means that the decoding judgment is successful and the decoding ends. Otherwise, it enters the next round of iteration until the decoding is successful or the maximum number of iterations is reached (decoding fails).

[0053] The entire iterative decoding process is as follows Figure 8 shown.

[0054] Embodiment 3: This embodiment provides a non-transitory computer-readable storage medium having computer instructions stored thereon, the computer instructions causing a computer to execute an LDPC-Hadamard full sequence coding method suitable for anti-interference communication, the method comprising the following steps: Given target code length N and bit rate R , based on the original model graph construction method of LDPC-Hadamard code, construct LDPC-Hadamard code that meets the parameter requirements; Select the left variable node in the LDPC-Hadamard coded Tanner graph and cut off any edge connected to the Hadamard check node; Insert an SPC node at the cut edge, and add a right variable node between the SPC node and the Hadamard check node, so that the original left variable node is connected to the newly added right variable node through the SPC node; The newly added right variable node is simultaneously connected to the cut-off Hadamard check node and sent to the channel as a coded codeword; Repeat the above operation for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full sequence code.

[0055] Embodiment 4: This embodiment provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus. The processor may call the logic instructions in the memory to execute the LDPC-Hadamard full sequence coding method suitable for anti-interference communication, and the method includes the following steps: Given target code length N and bit rate R , based on the original model graph construction method of LDPC-Hadamard code, construct LDPC-Hadamard code that meets the parameter requirements; Select the left variable node in the LDPC-Hadamard coded Tanner graph and cut off any edge connected to the Hadamard check node; Insert an SPC node at the cut edge, and add a right variable node between the SPC node and the Hadamard check node, so that the original left variable node is connected to the newly added right variable node through the SPC node; The newly added right variable node is simultaneously connected to the cut-off Hadamard check node and sent to the channel as a coded codeword; Repeat the above operation for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full sequence code.

[0056] In addition, the logic instructions in the above-mentioned memory can be implemented in the form of software functional units and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0057] Embodiment 5: This embodiment provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute an LDPC-Hadamard full sequence coding method suitable for anti-interference communication. The method includes the following steps: Given target code length N and bit rate R , based on the original model graph construction method of LDPC-Hadamard code, construct LDPC-Hadamard code that meets the parameter requirements; Select the left variable node in the LDPC-Hadamard coded Tanner graph and cut off any edge connected to the Hadamard check node; Insert an SPC node at the cut edge, and add a right variable node between the SPC node and the Hadamard check node, so that the original left variable node is connected to the newly added right variable node through the SPC node; The newly added right variable node is simultaneously connected to the cut-off Hadamard check node and sent to the channel as a coded codeword; Repeat the above operation for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full sequence code.

[0058] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0059] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0060] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A LDPC-Hadamard full sequence coding method suitable for anti-interference communication, characterized in that: include: Construct the original model graph LDPC-Hadamard code with given target code length and code rate; Insert an SPC node and a newly added Hadamard variable node with a degree of 2 between the LDPC variable node and the Hadamard check node in the Tanner graph of the original model LDPC-Hadamard code to form a new connection relationship; All LDPC variable nodes are traversed until the entire Tanner graph completes the structural transformation and forms the LDPC-Hadamard full sequence code.

2. The encoding method according to claim 1, characterized in that After the entire Tanner graph completes the structural transformation, the Tanner graph consists of LDPC variable nodes, SPC nodes, Hadamard check nodes, original Hadamard variable nodes with degree 1, and newly added Hadamard variable nodes with degree 2.

3. The encoding method according to claim 2, characterized in that After the entire Tanner graph completes the structural transformation, the LDPC variable nodes of the Tanner graph are used as implicit variable nodes and are not sent to the channel; the original Hadamard variable nodes with degree 1 and the newly added Hadamard variable nodes with degree 2 are sent to the channel as encoding codewords.

4. The encoding method according to claim 3, characterized in that The check matrix of the LDPC-Hadamard full sequence code is Indicates that Represents the number of Hadamard check nodes, represents the number of hidden variable nodes, and the check matrix The weight of each row d c Are equal.

5. The encoding method according to claim 4, characterized in that: The length of the complete LDPC-Hadamard full sequence encoding codeword is ,in ，r Represents the order of the Hadamard code.

6. The encoding method according to claim 1, characterized in that: The method of inserting an SPC node and a newly added Hadamard variable node between the LDPC variable node and the Hadamard check node in the original model LDPC-Hadamard code Tanner graph to form a new connection relationship is as follows: Select the LDPC variable node in the original model LDPC-Hadamard coded Tanner graph, and cut off any edge connected to the Hadamard check node; Insert an SPC node at the cut edge, and add a Hadamard variable node with a degree of 2 between the SPC node and the Hadamard check node, so that the LDPC variable node is connected to the newly added Hadamard variable node through the SPC node; The newly added Hadamard variable node with degree 2 is connected to the disconnected Hadamard check node and sent to the channel as a coded codeword.

7. The encoding method according to claim 6, characterized in that: The codeword is encoded by Hadamard sequences, each of which is taken from the codewords in the Hadamard codeword space. is the number of Hadamard check nodes.

8. A non-transitory computer-readable storage medium, characterized in that: Computer instructions are stored thereon, and the computer instructions enable the computer to execute the LDPC-Hadamard full sequence coding method suitable for anti-interference communication as described in any one of claims 1-7.

9. An electronic device, characterized in that: include: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus, and the processor calls the logic instructions in the memory to execute the LDPC-Hadamard full sequence coding method suitable for anti-interference communication as described in any one of claims 1-7.

10. A computer program product, characterized in that The computer program product includes a computer program, which is stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer executes the LDPC-Hadamard full sequence coding method suitable for anti-interference communication as described in any one of claims 1-7.

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