LDPC-Hadamard Full Sequence Coding Method for Anti-Interference Communication

Abstract

The present invention discloses an LDPC-Hadamard full-sequence coding method applicable to anti-interference communication, including: constructing a protograph LDPC-Hadamard code with a given target code length and code rate; inserting SPC nodes and a newly added Hadamard variable node of degree 2 between LDPC variable nodes and Hadamard check nodes in the Tanner graph of the protograph LDPC-Hadamard code to form a new connection relationship; traversing all LDPC variable nodes to form an LDPC-Hadamard full-sequence code. The full-sequence coding method of the present invention has the characteristic of Hadamard full-sequence transmission, enabling it to use the full-sequence characteristics of the codeword for anti-interference decoding. In a typical additive white Gaussian noise channel, the performance of the proposed scheme in the present invention is similar to that of the original scheme, while in an interference channel, the full-sequence scheme proposed in the present invention has an obvious anti-interference advantage.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and particularly relates to an LDPC-Hadamard full-sequence coding method applicable to anti-interference communication. Background Art

[0002] Early communication technologies mainly employed simple modulation methods (such as AM, FM), with limited resistance to interference. External noise, electromagnetic interference (EMI), and the aliasing of other signals were the main threats to communication systems. At that time, anti-interference means mainly focused on the analog communication stage (such as radio broadcasts and early telephone systems). Due to technological limitations, anti-interference strategies mainly enhanced the reliability of communication through simple hardware and signal design methods. The core objective of these means was to cope with environmental noise, electromagnetic interference, and limited interference signals, and their main anti-interference means included increasing signal power, improving antenna directivity, etc.

[0003] With the emergence of digital communication, it brought new directions to anti-interference technologies. These mainly include error correction coding (such as Hamming codes, LDPC codes), spread spectrum communication (DSSS, FHSS). Through methods such as signal coding, modulation, and spread spectrum, 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 codes have excellent performance close to the Shannon limit, and their structure is uniquely determined by the parity-check matrix It should be noted that the parity-check matrix of LDPC codes consists of "0"s and "1"s, where the number of "1"s is much less than the number of "0"s, having sparsity, which describes the linear relationship from message bits to check bits. LDPC codes have two basic decoding algorithms, namely the BF algorithm and the BP algorithm. The BF algorithm is the basis of the hard decision decoding mode, and only the information after decision ("0" or "1") is used for iterative decoding during the decoding process. The BP algorithm is the basis of the soft decision decoding mode, and the probability likelihood information extracted from the channel is used for iterative decoding during the iterative decoding process. The decoding complexity of LDPC is low and 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, for the LDPC-Hadamard hybrid encoding and decoding method disclosed in the patent with the publication number CN118868975A, its LDPC-Hadamard code replaces the parity-check constraint of the LDPC code with a Hadamard constraint and is accompanied by additional Hadamard variable nodes. Although it has excellent coding gain, under interference conditions, due to the lack of a corresponding anti-interference decoding mechanism, its performance is not ideal. Summary of the Invention

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

[0007] An object of the present invention is to provide an LDPC-Hadamard full-sequence coding method applicable to anti-interference communication. By utilizing the orthogonality and spread-spectrum characteristics of the full-sequence Hadamard code, it makes the anti-interference decoding of low-code-rate LDPC-Hadamard possible and significantly improves the anti-interference performance.

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

[0009] To this end, on the one hand, the present invention provides an LDPC-Hadamard full-sequence coding method applicable to anti-interference communication, including:

[0010] Constructing a protograph LDPC-Hadamard code with a given target code length and code rate;

[0011] Inserting an SPC node (Single-Parity-Check) and a new Hadamard variable node between the LDPC variable nodes and Hadamard check nodes in the Tanner graph of the protograph LDPC-Hadamard code to form a new connection relationship;

[0012] Traversing all LDPC variable nodes until the structural transformation of the entire Tanner graph is completed to form an LDPC-Hadamard full-sequence code.

[0013] Preferably, after the structural transformation of the entire Tanner graph, the Tanner graph is composed of LDPC variable nodes, SPC nodes, Hadamard check nodes, original Hadamard variable nodes with degree 1, and new Hadamard variable nodes with degree 2.

[0014] Preferably, after the structural transformation of the entire Tanner graph, 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 new Hadamard variable nodes with degree 2 are sent to the channel as encoded codewords.

[0015] Preferably, the parity-check matrix of the LDPC-Hadamard full-sequence code is represented by where represents the number of Hadamard check nodes, represents the number of implicit variable nodes, and the parity-check matrix The row weight of each rowd c All are equal.

[0016] Preferably, the length of the complete LDPC-Hadamard full-sequence encoded codeword is , where ，r represents the order of the Hadamard code.

[0017] Preferably, between the LDPC variable nodes and the Hadamard check nodes in the protograph LDPC-Hadamard code Tanner graph, an SPC node and a newly added Hadamard variable node are inserted to form a new connection relationship; the specific method is:

[0018] Select the LDPC variable nodes in the protograph LDPC-Hadamard encoded Tanner graph, and cut any one of the edges connecting to the Hadamard check nodes;

[0019] Insert an SPC node at the cut edge, and add a Hadamard variable node of degree 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;

[0020] The newly added Hadamard variable node of degree 2 is connected to the cut Hadamard check node and sent to the channel as the encoded codeword.

[0021] Preferably, the encoded codeword is composed of Hadamard sequences, and each Hadamard sequence is taken from the codewords in the Hadamard codeword space, is the number of Hadamard check nodes.

[0022] On the other hand, the present invention provides an LDPC-Hadamard full-sequence decoding method applicable to anti-jamming communication, including:

[0023] According to the channel received value, initialize the Hadamard check node information and the LDPC-Hadamard full-sequence code implicit variable node information of the LDPC-Hadamard full-sequence code;

[0024] Update the Hadamard check node information of the LDPC-Hadamard full-sequence code;

[0025] Update the implicit variable node information of the LDPC-Hadamard full-sequence code;

[0026] Based on the information of the hidden variable nodes of the LDPC-Hadamard full sequence code, perform decoding decision, and increase the number of iterations by one; if the decoding decision is successful, end the decoding, otherwise enter the next iteration process.

[0027] Preferably, the initialization of the Hadamard check node information of the LDPC-Hadamard full sequence code includes the following steps:

[0028] For a given order of the Hadamard code r , the length of the channel received vector is , and . Assign the value of the sub-vector to the th row of the matrix j to complete the assignment of the channel information of the j nd Hadamard check node (including the channel information of the Hadamard variable nodes of degree 1 and the channel information of the Hadamard variable nodes of degree 2), The j th row of is denoted as

[0029] Initialize the prior information matrix (the extrinsic information passed from the hidden variable nodes to the Hadamard check nodes), and set all its values to 0, where represents the extrinsic information passed from the i th hidden variable node to the j th Hadamard check node during decoding.

[0030] Preferably, the initialization of the LDPC-Hadamard full sequence code hidden variable node information includes:

[0031] Initialize the prior information matrix (the extrinsic information passed from the Hadamard check nodes to the hidden variable nodes), and set all its values to 0, where represents the extrinsic information passed from the j th Hadamard check node to the i th hidden variable node during decoding.

[0032] Preferably, the process of updating the Hadamard check node information of the LDPC-Hadamard full sequence code includes:

[0033] Traverse all Hadamard check nodes ( j = 1, 2,..., m) Using the channel information of the Hadamard variable nodes with degree 1, the channel information of the Hadamard variable nodes with degree 2, and the prior information of the Hadamard check nodes as inputs, they are sent to the Hadamard anti-interference APP decoding module, which calculates and outputs the extrinsic information passed from the Hadamard check nodes to the latent variable nodes (The extrinsic information passed from the j th Hadamard check node to the i th latent variable node). The specific steps are as follows:

[0034] Let be the subscript vector (Hadamard code information bit subscript vector). The th row of the matrix j stores the subscripts of the non-zero elements in the th row of j and the elements in each row are arranged in sequence. The th row of the matrix stores the complete prior information required for the update of the j th Hadamard check node. The j th row of the matrix stores the complete posterior information generated after the update of the j th Hadamard check node. At initialization, j and are set to all 0. For the

[0035] th Hadamard check node, at the j th iteration, assign the values of the elements in u whose subscripts belong to to the values of the elements in x whose subscripts belong to the j th row. For example, when = 3, r , , then , , , . Then: . Then:

[0036] ;

[0037] Where:

[0038] ;

[0039] represents the covariance matrix of the signal after mixing interference and noise. represents the inner product of two vectors, represents r the -th column of the Hadamard matrix of order represents taking the real part of a complex number, r represents the k -th bit of the Hadamard codeword of order

[0040] Then, assign the values of the elements whose subscripts belong to to the elements of matrix x in the j -th row whose subscripts belong to in the same way as above.

[0041] At the u -th iteration, the extrinsic information passed from the j -th Hadamard check node to the i -th latent variable node is:

[0042] .

[0043] Preferably, the updating of the latent variable node information of the LDPC-Hadamard full sequence code includes the following steps:

[0044] Based on the belief propagation algorithm, using the prior information input by the latent variable node, calculate the extrinsic information passed from the latent variable node to the Hadamard check node (the extrinsic information passed from the i -th latent variable node to the j -th Hadamard check node) as:

[0045] ;

[0046] where represents the set of Hadamard check nodes connected to the j -th latent variable node through the SPC node except for the i -th Hadamard check node.

[0047] Another aspect of the present invention provides a non-transitory computer-readable storage medium, on which computer instructions are stored, and the computer instructions cause the computer to execute the above-mentioned LDPC-Hadamard full sequence coding method applicable to anti-interference communication.

[0048] In another aspect, the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus. The processor calls the logical instructions in the memory to execute the above-mentioned LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication.

[0049] In yet another aspect, the present invention provides a computer program product. The computer program product 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 encoding method applicable to anti-interference communication.

[0050] Beneficial effects: The LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication of the present invention makes use of the orthogonality and spread-spectrum characteristics of the full-sequence Hadamard code, making it possible for low-code-rate LDPC-Hadamard anti-interference decoding, and significantly improving the anti-interference performance.

[0051] Compared with the existing LDPC-Hadamard coding technology, in a typical BPSK Gaussian white noise channel, the coding method proposed by the present invention has similar performance to the original LDPC-Hadamard coding technology. However, in an interference channel, since the codewords sent to the channel by this coding scheme are segments of Hadamard sequences, which can be regarded as a kind of spread-spectrum sequence, and spread-spectrum technology can be used to suppress interference, the full-sequence scheme proposed by the present invention has obvious anti-interference advantages. Description of the Drawings

[0052] Figure 1 It is a flowchart of the LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication in Embodiment 1;

[0053] Figure 2 It is a flowchart of the LDPC-Hadamard full-sequence decoding method applicable to anti-interference communication in Embodiment 2;

[0054] Figure 3 It is a display diagram of the Tanner graph technology of traditional LDPC;

[0055] Figure 4 It is a display diagram of the Tanner graph technology of traditional LDPC-Hadamard;

[0056] Figure 5 It is a display diagram of the formation of a new connection relationship between the left variable node and the Hadamard check node;

[0057] Figure 6The display diagram for completing the structural transformation traversing all left variable nodes of the entire Tanner graph;

[0058] Figure 7 The comparison diagram for comparing the Tanner graph of the LDPC-Hadamard full sequence coding scheme of the present invention with the Tanner graph of the traditional LDPC-Hadamard scheme;

[0059] Figure 8 The decoding process of the LDPC-Hadamard full sequence decoding method proposed by the present invention. Specific embodiments

[0060] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments, and they should not be construed as limiting the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall 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 the purpose of description and cannot be construed as indicating or implying relative importance.

[0061] Before elaborating on the technical solutions of the present invention through specific embodiments, it is necessary to first introduce the knowledge points that the present application may involve.

[0062] LDPC code is a linear block code and can be defined by a linear block code ( n , k ), where n represents the length of the LDPC code, k represents the number of information bits. Through encoding, m = n - k check bits can be generated, and each check bit is obtained by performing different linear operations on the k information bits. From the definition of the code rate, the code rate Rate = k / n。Nowadays, there are two common representation methods for LDPC codes. The first method is using the parity-check matrix, and the second method is the Tanner graph. In fact, they are essentially the same. The parity-check matrix of an LDPC code is a binary matrix, and the number of elements "0" in this binary matrix is much larger than the number of elements "1", showing "sparsity", which is also the origin of LD (Low-Density) in the name of LDPC code. Regarding each column of the LDPC parity-check matrix as a variable node and each row as a parity-check node. If the element in the i row and the j column of the matrix is 1, it means that the i th parity-check node is connected to the j th variable node. If an edge is connected between them, a Tanner graph is formed, as shown in the Figure 3 Tanner graph of LDPC shown.

[0063] There are many encoding methods for LDPC codes. In engineering, to facilitate encoding, an LDPC parity-check matrix with a certain structure is designed to greatly reduce the encoding complexity. In the present invention, the encoding technique adopted is Gaussian elimination. This method performs row and column transformations on the LDPC parity-check matrix so that the original parity-check matrix becomes the following form:

[0064] ;

[0065] Then, according to the relationship between the generator matrix and the parity-check matrix, the generator matrix is obtained as:

[0066] ;

[0067] Finally, according to the encoding rule of linear block codes, the information bits are multiplied on the right by the generator matrix to obtain the LDPC codeword;

[0068] Hadamard matrix is a n × n square matrix composed of "+1" and "-1", 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 generated by circular recursion as follows:

[0069] ;

[0070] where , r is the order of the Hadamard matrix and also the order of the Hadamard code. The Hadamard codeword is composed of A certain row or column is mapped , implemented. In the present invention, if not specifically indicated, the Hadamard code represents the biorthogonal system Hadamard code.

[0071] Let the information bit , if this information bit sequence b is to be used to generate the systematic Hadamard code, there is a simple method: if b (0) is 0, then let s be b ( r ) b ( r -1)... b (1)]'s decimal representation, then the generated systematic Hadamard code is 's s column. If b (0) = 1, then let s be b (1) b (2)... b ( r )]'s decimal representation, then the generated systematic Hadamard code c is 's s column.

[0072] The above description is crucial for understanding the present invention and is an important supplement to the present invention.

[0073] Next, the LDPC-Hadamard full-sequence coding method provided by the present invention applicable to anti-interference communication will be described in conjunction with Figures 1 - 8 .

[0074] Example 1: As Figure 1 shown, this example provides an LDPC-Hadamard full-sequence coding method applicable to anti-interference communication. The method includes the following steps:

[0075] S110. Construct a protograph LDPC-Hadamard code with given parameters based on the existing protograph LDPC-Hadamard code construction method.

[0076] Assume that the code length is 14 and the code rate is 2 / 7. The LDPC-Hadamard code constructed based on the existing protograph LDPC-Hadamard code construction method is:

[0077] ;

[0078] Its Tanner graph is as follows Figure 4 shown.

[0079] S120. Cut any one of the edges connecting the left variable nodes (i.e., LDPC variable nodes, which are located on the left side of the Tanner graph in this embodiment. For convenience of description, they are hereinafter referred to as left variable nodes) to the Hadamard check nodes. At the same time, insert an SPC node and a newly added right variable node with degree 2 (i.e., Hadamard variable nodes, which are located on the right side of the Tanner graph in this embodiment. For convenience of description, they are hereinafter referred to as right variable nodes), 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-off Hadamard node and sent to the channel.

[0080] In this embodiment, for Figure 4 the left variable nodes v 1 connected to the Hadamard check nodes H 1, H 2, cut the edges. At the same time, insert 2 SPC nodes and 2 newly added right variable nodes, so that the left variable node is connected to the newly added right variable node through the SPC, and connect the two inserted newly added right variable nodes to the Hadamard check nodes. At the same time, the left variable node v 1 becomes an implicit variable node and is no longer sent to the channel. The structural change is as Figure 5 shown.

[0081] S130. Repeat step S120 and repeatedly perform the above operations on all left variable nodes until the cutting of the edges of v 2, v 3, v 4, v 5, v 6 is completed, obtaining an LDPC-Hadamard full-sequence code, as Figure 6 shown. Its transmitted codeword is composed of right variable nodes, and all left variable nodes become implicit variable nodes and are no longer sent.

[0082] To better understand the LDPC-Hadamard full-sequence encoding method proposed by the present invention for anti-interference communication, the LDPC-Hadamard full-sequence encoding scheme of the present invention will be compared with the existing LDPC-Hadamard encoding scheme.

[0083] As Figure 7As shown in the figure, the codeword sent to the channel by the existing LDPC-Hadamard coding scheme consists of two parts. One part is the left variable nodes of LDPC-Hadamard (LDPC variable nodes), and the other part is the right variable nodes of LDPC-Hadamard (which appears as a partial sequence of the Hadamard codeword after removing the information bits, that is, the Hadamard variable nodes of degree 1). However, the codeword sent by the LDPC-Hadamard full-sequence coding scheme proposed by the present invention is entirely a Hadamard codeword sequence (including Hadamard variable nodes of degree 1 and Hadamard variable nodes of degree 2). Because in the LDPC-Hadamard full-sequence coding scheme, the LDPC variable nodes are not directly sent to the channel, but are connected to the SPC nodes to form the information bit positions of the Hadamard codeword and are indirectly sent to the channel. Therefore, 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 the LDPC variable nodes and the Hadamard check nodes, while the information of the LDPC-Hadamard full-sequence coding scheme proposed by the present invention is propagated between the hidden variable nodes and the Hadamard variable nodes of degree 2 through the SPC nodes.

[0084] Embodiment 2: Since the LDPC-Hadamard full-sequence coding scheme proposed by the present invention belongs to a generalized LDPC code, its decoding process is similar to that of the LDPC code, including updating the implicit variable nodes and updating the Hadamard variable nodes.

[0085] As Figure 2 shown, this embodiment provides an LDPC-Hadamard full-sequence decoding method applicable to anti-jamming communication. The general steps are as follows:

[0086] S210: Initialize the Hadamard check node information and the LDPC-Hadamard implicit variable node information of the LDPC-Hadamard full-sequence code according to the channel received value;

[0087] S220: Update the Hadamard check node information of the LDPC-Hadamard full-sequence code;

[0088] S230: Update the LDPC-Hadamard full-sequence code implicit variable node information;

[0089] S240: Perform decoding decision based on the implicit variable node information of the LDPC-Hadamard full sequence code, and increase the number of iterations by one. If the decoding decision is successful, end the decoding; otherwise, enter the next round of iteration process.

[0090] Next, still taking the LDPC-Hadamard full sequence code in Embodiment 1 as an example, each step of the decoding method will be described in detail.

[0091] As Figure 6 shown, for the above-mentioned LDPC-Hadamard full sequence code, the order of the Hadamard code is 3. For step S210, the specific steps are as follows:

[0092] S211. Given that the order of the Hadamard code is 3, then the length of the channel received vector y is , and . Assign the value of the sub-vector y j to the th row of the matrix j to complete the assignment of the channel information of the j th Hadamard check node (including the channel information of the Hadamard variable node with degree 1 and the channel information of the Hadamard variable node with degree 2), and represent the th row of j as ;

[0093] S212. Initialize the prior information received by the Hadamard check node: .

[0094] S213. Initialize the prior information received by the implicit variable node: .

[0095] Taking the first Hadamard check node as an example, S220 will be described in detail:

[0096] is the subscript vector (Hadamard code information bit subscript vector). The first row of the matrix stores the subscripts of the non-zero elements in the first row of , and each row is arranged in sequence. The first row of the matrix stores the complete prior information required for the update of the first Hadamard check node. The first row of the matrix stores the complete posterior information generated after the update of the first Hadamard check node. Initially, set and to all 0. Assign Represented as a matrix The first row of Represented as a matrix The element in the first row and the i column of

[0097] For the first Hadamard check node, at the u iteration, The values of the elements whose subscripts belong to x in are assigned the values of the elements whose subscripts belong to in the first row of where , then , then:

[0098] ;

[0099] Where:

[0100] ;

[0101] After that, The values of the elements whose subscripts belong to x in are assigned to the elements in the first row of matrix whose subscripts belong to

[0102] Based on the above description, at the u iteration, the extrinsic information passed from the first Hadamard check node to the connected latent variable node is:

[0103] ;

[0104] In step S230, at the u iteration, the extrinsic information passed from the i th latent variable node to the connected Hadamard check node is:

[0105] ;

[0106] Where represents the set of Hadamard check nodes connected to the i th latent variable node through the SPC node, represents the set of Hadamard check nodes connected to the j th Hadamard check node, excluding the i th Hadamard check node, and connected to the

[0107] In step S204, at the uAt the i th iteration, the decoding process of the

[0108] th hidden variable node can be expressed by the following formula:

[0109] When is greater than 0, the i th hidden variable node is judged as 0, otherwise it is judged as 1. And set the decoding sequence as . If meets the decision condition , it means that the decoding decision is successful, and the decoding ends. Otherwise, enter the next iteration until the decoding is successful or the maximum number of iterations is reached (decoding failure).

[0110] The entire iterative decoding process is as shown in Figure 8 .

[0111] Embodiment 3: This embodiment provides a non-transitory computer-readable storage medium, on which computer instructions are stored. The computer instructions cause the computer to execute an LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication. The method includes the following steps:

[0112] Given a target code length N and a code rate R , based on the original graph construction method of LDPC-Hadamard code, construct an LDPC-Hadamard encoding that meets the parameter requirements;

[0113] Select the left variable nodes in the Tanner graph of the LDPC-Hadamard encoding, and cut off any one of the edges connecting to the Hadamard check nodes;

[0114] Insert an SPC node at the cut edge, and add a new 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;

[0115] The newly added right variable node is simultaneously connected to the cut-off Hadamard check node and sent as an encoded codeword to the channel;

[0116] Repeat the above operations for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full-sequence code.

[0117] Embodiment 4: This embodiment provides an electronic device, which may include: a processor, a communications interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus. The processor can call the logical instructions in the memory to execute the LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication. This method includes the following steps:

[0118] Given a target code length N and a code rate R , based on the protograph construction method of LDPC-Hadamard codes, construct an LDPC-Hadamard encoding that meets the parameter requirements;

[0119] Select the left variable nodes in the Tanner graph of the LDPC-Hadamard encoding, and cut any one of the edges connecting to the Hadamard check nodes;

[0120] 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;

[0121] The newly added right variable node is simultaneously connected to the cut Hadamard check node and sent to the channel as an encoded codeword;

[0122] Repeat the above operations for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full-sequence code.

[0123] In addition, when the logical instructions in the above-mentioned memory are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. And the aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0124] Embodiment 5: A computer program product is provided in this embodiment. The computer program product includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the LDPC-Hadamard full-sequence encoding method applicable to anti-interference communication. The method includes the following steps:

[0125] Given a target code length N and a code rate R , based on the protograph construction method of LDPC-Hadamard code, construct an LDPC-Hadamard encoding that meets the parameter requirements;

[0126] Select the left variable nodes in the Tanner graph of the LDPC-Hadamard encoding, and cut off any one of the edges connecting to the Hadamard check node;

[0127] Insert an SPC node at the cut-off edge, and add a new right variable node between the SPC node and the Hadamard check node, so that the original left variable node is connected to the new right variable node through the SPC node;

[0128] The newly added right variable node is simultaneously connected to the cut-off Hadamard check node and sent to the channel as an encoded codeword;

[0129] Repeat the above operations for all left variable nodes until the entire Tanner graph is transformed to form an LDPC-Hadamard full-sequence code.

[0130] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0131] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable 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.

[0132] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. And these modifications or replacements do not make the essence of the corresponding technical solutions deviate 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; An SPC node and a newly added Hadamard variable node with a degree of 2 are inserted 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; 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; 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 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, Represents the order of the Hadamard code.

6. The encoding method according to claim 1, 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.

7. 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 1-6.

8. 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 1-6.

9. 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 1-6.

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