Transmission pattern generation method and system for high-sparsity multi-user transmission

Abstract

The invention discloses a transmission pattern generation method and system for high-sparsity multi-user transmission, and mainly solves the problems that in the prior art, in an ODMA random access model, the number of users is large, and the bit error rate performance of a system is low. According to the implementation scheme, binary information bits sent by a user are divided into two information bit sequences, the first information bit sequence is converted into a decimal number, coding modulation is conducted on the second information bit sequence, and a modulation symbol sequence is obtained; the method comprises the following steps: generating an all-zero matrix according to a known first information bit sequence length, a modulation symbol sequence length and a transmission time slot number determined in advance, iteratively updating the matrix, continuously searching updating positions of matrix elements by generating a path tree, and finally, updating the initial all-zero matrix into a binary sparse matrix, namely a multi-user transmission pattern. According to the invention, the bit error rate of the system is reduced, the system performance for coping with access requirements of more active users is improved, and the method can be used for high-sparsity multi-user transmission in mass machine type communication.

Description

Technical Field

[0001] The present invention belongs to the field of communication technology, and in particular relates to a transmission pattern generation method and system, which can be used for high-sparse multi-user transmission of massive machine type communications. Background Art

[0002] Massive machine type communication (mMTC) is one of the three major application scenarios of the fifth generation mobile communication system 5G defined by 3GPP. In the mMTC scenario, in order to reduce transmission resource consumption and reduce transmission delay, a solution is often adopted in which active devices can directly transmit data without prior request and approval, that is, the unauthorized GF access solution. Since the active device does not send an access request in advance, the base station cannot obtain the specific information of the active device. Therefore, in the traditional GF access solution, there are the following two problems: 1) For massive devices, each device needs to be allocated a unique pilot sequence, resulting in more resource consumption. 2) An activity detection solution is required at the receiving end to identify the identity of the active device, which increases the transmission delay.

[0003] In response to the problems of traditional access solutions in mMTC scenarios, Polyanskiy proposed a new random access solution, namely, unidentified random access, in "A perspective on massive random-access" in 2017. In this scenario, the transmission data packet is small, and the base station only cares about recovering the set of sent messages, and does not need to identify the identity of active users, thus saving the cost of identifying user identities.

[0004] The patent with application number CN202310812717.5 discloses a large-scale multiple access method based on adaptive matching pursuit. It receives the uplink signals of multiple users through the base station and models them as block sparse vectors, and uses the vector to reconstruct the new uplink reception signal equation; then uses the adaptive matching pursuit algorithm based on the block sparse model to perform active user detection and reconstruct the user's sent data. Although this method can realize random access of large-scale terminals without identification under the premise of reducing the user terminal overhead, it is only applicable to the sporadic burst uplink transmission scenario of large-scale terminals, so the system performance is poor when dealing with the demand for access by more active users.

[0005] Jian Xiang Yan proposed an unsourced multiple access scheme, switch division multiple access (OAMD), for large-scale machine type communications in the paper "ODMA Transmission and Joint Pattern and Data Recovery for Unsourced Multiple Access". In this scheme, the message of each active user is divided into two parts, the first part is used to determine the switch pattern, and the second part is encoded and transmitted in a time-hopping manner according to the switch pattern. By utilizing the sparse characteristics of ODMA, the user's switch pattern is blindly detected from the received signal without the help of a pilot, and the switch pattern detection and data decoding are iteratively performed on a sparse graph to improve the overall reliability of the system. This scheme can carry the access needs of more active users, but as the number of active users continues to increase, the system bit error rate will increase sharply. Summary of the invention

[0006] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and propose a transmission pattern generation method and system for high-sparse multi-user transmission, so as to optimize the sparsity of the ODMA transmission pattern, reduce the system bit error rate, and improve the system performance when dealing with the access needs of more active users.

[0007] To achieve the above purpose, the technical solution of the present invention is as follows:

[0008] Technical solution 1:

[0009] A transmission pattern generation method for high-sparse multi-user transmission, characterized by comprising:

[0010] The binary information bits u of length B sent by user K k Divided into u ks and u kc Two parts, and the first information bit sequence u ks Convert to a decimal number d k , for the second information bit sequence u kc Perform coding modulation to obtain a length of n c The modulation symbol sequence w k , where u ks The length of B s ,u kc The length of B c =BB s ;

[0011] According to the known parameter B s 、n c And the number of transmission time slots n determined in advance, generate a binary sparse matrix As a multi-user transmission pattern, is the column length of the matrix, the row length of the matrix is ​​consistent with the number of transmission time slots n, and the row weight of the matrix is ​​consistent with the modulation symbol sequence w k The length n c Consistency;

[0012] User K selects the dth k row, used to transmit the modulation symbol sequence w k .

[0013] Further, the second information bit sequence u kc Perform coded modulation, including:

[0014] Through u kc Perform channel coding to generate codewords where v k,j ∈{0,1} is the jth code element of the codeword obtained after the information bit of the kth user is channel encoded, 1≤j≤n d , the code rate of this code is B c / n d ;

[0015] Codeword v k Perform QPSK modulation to obtain the modulation symbol sequence: where w k,l is the lth modulation symbol of the modulation symbol sequence after the information bit of the kth user is coded and modulated, 1≤l≤n c ;

[0016] Further, the generating of a binary sparse matrix A includes: given a target matrix A, the row and column lengths are n and and row weight n c , initially generate the full zero matrix of the matrix;

[0017] Update the all-zero matrix row by row until the first The update of the row results in a binary sparse matrix A, where

[0019] Technical solution 2:

[0020] A transmission pattern generation system for high-sparse multi-user transmission, comprising:

[0021] A coding and modulation module, used to obtain relevant parameters for generating a multi-user transmission pattern;

[0022] A path tree generation module is used to generate a path tree with the current row node as the root node, and pass the generated path tree to the column node selection module;

[0023] A column node selection module, used for selecting a suitable column node in the path tree and transferring the selected column node to the transmission pattern generation module;

[0024] The matrix generation module is used to generate a multi-user transmission pattern according to the result transmitted by the column node selection module, and transmit the updated transmission pattern back to the path tree generation module for further updating until the transmission pattern generation is completed.

[0025] Technical solution 3:

[0026] A computer program product, comprising a computer program, characterized in that when the computer program is executed by a processor, the multi-user transmission pattern generation method described in any one of Technical Solution 1 and Technical Solution 2 is implemented.

[0027] Compared with the prior art, the present invention has the following advantages:

[0028] The present invention generates a multi-user transmission pattern, thereby reducing the mutual collision of information between users during multi-user transmission, achieving more sparse multi-user transmission, and improving system performance when dealing with the access needs of more active users;

[0029] In the process of generating the transmission pattern, the present invention utilizes the current matrix Construct a path tree with the i-th row as the root node, update the all-zero matrix row by row, and obtain the update state of each step of the transmission pattern, which reduces the computational complexity;

[0030] The present invention is due to the second information bit sequence u kc In the process of coded modulation, the code word v k QPSK modulation is performed to obtain a shorter modulation symbol sequence, which can make the line weight in the generated transmission pattern smaller, improve the sparsity in the multi-user information transmission process, and reduce the system bit error rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a flow chart for implementing embodiment 1 of the method for generating a transmission pattern for high-sparse multi-user transmission of the present invention.

[0032] Figure 2 for Figure 1 Medium coding modulation sub-flow chart;

[0033] Figure 3 This is a schematic diagram of generating a path tree in Example 1 of the present invention.

[0034] Figure 4 A structural block diagram of a transmission pattern generation system for high-sparse multi-user transmission according to the present invention;

[0035] Figure 5The figure is a simulation result diagram of the signal-to-noise ratio-bit error rate in an ODMA system using the method of the present invention and the random transmission pattern generation method respectively. DETAILED DESCRIPTION

[0036] The embodiments and effects of the present invention are described in detail below with reference to the accompanying drawings.

[0037] Embodiment 1, a transmission pattern generation method for high-sparse multi-user transmission.

[0038] This example is to generate a transmission pattern in an ODMA system. In this system, multiple users need to send binary information bits of the same length. The message is matched with the corresponding transmission pattern through a determined coding modulation scheme, and finally the transmission pattern selects the corresponding time slot for transmission. Generating the transmission pattern requires multiple updates to the corresponding all-zero matrix, and each update requires generating the corresponding path tree of the current matrix to determine the position of the updated element.

[0039] Reference Figure 1 The implementation steps of this example include the following:

[0040] Step 1: The user transmitting end determines the coding modulation scheme, determines the transmission pattern parameters, and obtains the modulation symbol sequence.

[0041] like Figure 2 As shown, the implementation of this step includes the following:

[0042] 1.1) User K sends binary information bits u of length B k Divide into two parts of different lengths u ks and u kc ,in:

[0043] The first information bit sequence u ks The length of B s , which is used to determine the second information bit sequence u kc In which time slot is the transmission performed?

[0044] The second information bit sequence u kc The length of B c =BB s , used to pass the first information bit sequence u after coding modulation ks Transmitting in the determined transmission time slot;

[0045] Since the binary information bits sent by different users are not necessarily the same, the two parts divided by each user are not necessarily the same;

[0046] 1.2) For the first information bit sequence u ks The length is chosen to reduce the probability of user collision:

[0047] If the first information bit sequence u in the binary information bits of different users ks The same will eventually cause the different users to select the same preamble code, and eventually cause the different users to transmit information in exactly the same time slot, making the information completely collide and unable to be decoded; therefore, the first information bit sequence u in the binary information bit can be appropriately increased ks length to reduce the probability of user collision;

[0048] However, increasing the first information bit sequence u in the binary information bit ks The length of B s , which will increase the random access resource cost and simulation experiment cost. Therefore, in the example, it is necessary to select a suitable first information bit sequence u according to the actual situation. ks The length of B s , which is not specifically limited here;

[0049] 1.3) The first information bit sequence u ks Convert to a decimal number d k , which can be used to determine the second information bit sequence u by subsequently selecting a row in the transmission pattern kc The specific transmission time slot;

[0050] 1.4) Use RA code to generate the second information bit sequence u kc Perform channel coding to generate codeword v k :

[0051]

[0052] where v k,j ∈{0,1} is the jth code element of the codeword obtained after the information bit of the kth user is channel encoded, 1≤j≤n d

[0053] 1.5) For codeword v k Perform QPSK modulation to obtain the modulation symbol sequence w k :

[0054]

[0055] where w k,a is the ath modulation symbol in the modulation symbol sequence after the information bit of the kth user is coded and modulated, 1≤a≤n c .

[0056] Step 2: Generate an all-zero matrix based on the parameters obtained in step 1 and an initial fixed value n.

[0057] 2.1) Set an initial fixed value n as the row length of the all-zero matrix, indicating that the fixed channel resource is n time slots. 2.2) According to the u obtained in step 1 ks Length B s , let the column length of the all-zero matrix be Because the binary information bits sent by the user are only 0 and 1, the length is B s The binary information bits can represent decimal number;

[0058] 2.3) According to the modulation symbol sequence w obtained in step 1 k The length n c , let the row weight of the all-zero matrix be n c .

[0059] When the all-zero matrix is ​​updated to obtain the transmission pattern, each row in the transmission pattern will have n c The first position is 1, and the remaining positions are 0; the position where the element is 1 in the transmission pattern indicates that the time slot can be used to carry the symbol in the modulation symbol sequence sent by user K, and the position where the element is 0 indicates that the time slot is closed and cannot carry symbols.

[0060] Step 3: Generate a path tree.

[0061] Common methods for generating path trees include depth-first search-based generation methods and breadth-first search-based generation methods.

[0062] The generation method based on depth-first search usually generates along a path in a recursive manner until a leaf node is reached, then returns to the last generated node to determine whether there are other paths to generate the current node. If so, continue to generate along the new path until all paths are generated. If not, continue to return to the last generated node to determine whether there are other paths to generate the current node, and repeat the above steps until all leaf nodes are generated.

[0063] The generation method based on breadth-first search usually generates tree nodes by layer, and after the nodes of the current layer are generated, it will enter the next layer until all leaf nodes are generated;

[0064] Since the depth-first search algorithm may cause stack overflow when the number of tree layers is large, and the number of generated layers cannot be controlled,

[0065] This example adopts a generation method based on breadth-first search to reduce the path tree generation time and computational complexity by setting the maximum number of layers of the generated path tree.

[0066] Reference Figure 3 As shown, the implementation of this step includes the following:

[0067] 3.1) Set row counter i to indicate that the current update is to row i, where The initial value of i is 1;

[0068] 3.2) Let column counter k be k, which means k elements have been updated in row i, where 0≤k≤n c , the initial value of k is 0;

[0069] 3.3) Define the current matrix for updating the all-zero matrix as

[0070] 3.4) Through the current matrix Constructs a matrix about the current matrix The bipartite graph of

[0071] 3.5) According to the obtained bipartite graph Row node r i is the path tree R i The root node of R i Each path in is a sequence of row nodes and column nodes appearing alternately, its leaf nodes are all column nodes, and each node on each path appears only once;

[0072] 3.6) Set the number of layers of the path tree parameter d, and each layer consists of a layer of row nodes and a layer of column nodes, and set the initial value of d to 0;

[0073] 3.7) In a bipartite graph Find the distance row node r i The nearest column node is taken as R i Middle root node r i The child node of the path tree is constructed at the 0th level.

[0074] 3.8) According to the bipartite graph In the tree R i Add all the connection trees R i The edge from the 0th layer column node to the corresponding row node of the 1st layer, and then connect the path tree R i From all row nodes in the first layer to their nearest column nodes, we get the path tree R i 1st layer;

[0075] 3.9) Similarly, according to the bipartite graph In the tree R i Add all the connection trees R i The edge from the column node of the d-1th layer to the row node corresponding to the dth layer, and then connect the path tree R i From all row nodes in the dth layer to their nearest column nodes, we get the path tree R i The dth layer, at this time, the number of layers d itself is increased by 1;

[0076] 3.10) Repeat step 3.9) until the path tree R i When a certain layer is reached and cannot be expanded any further, the path tree R is completed. i 's construction.

[0077] Step 4: According to the path tree R i For the current matrix renew.

[0078] 4.1) For the path tree R i , let the distance d(r i ,c j ) is the root node r i To column node c j The length of the shortest path, the selected path tree R i The Lth layer of Represents the path tree R i and the root node r i The set of column nodes whose distance is less than 2L+1, let express The complement of all column nodes is represented by C = {c1, c2, ..., c j ,…,c n},but Where j∈{1,2,......,n}, n is the total number of column nodes;

[0079] 4.2) According to the number of layers L selected in step 4.1, from the path tree R i Select the qualifying column that meets one of the following two conditions:

[0080] Case 1: The path tree cannot be expanded after reaching the Lth layer, and the candidate set Size is less than n; this situation indicates that in the current matrix The bipartite graph of In the row node r i Since not all column nodes are reachable, we select row node r i Unreachable column nodes can avoid adding additional short cycles to the current matrix. In this case, the current matrix exist Select a column node c with the minimum column weight j ;

[0081] Second case: This situation shows that in the current matrix The bipartite graph of In the row node r iAll column nodes are reachable. In this case, selecting any column node will generate an additional cycle. In order to maximize the sparse transmission of the transmission pattern, the path tree R i Select distance r in the (L+1)th layer i The farthest column node c j ;

[0082] 4.3) According to the column node c obtained in step 4.2) j , that is, the j-th column of the matrix and the i-th row currently being updated, get a specific position in the matrix, that is, the i-th row and j-th column, set the element at this position to 1, and add 1 to the column counter k itself, and then complete an element update.

[0083] Step 5: After completing an element update, it is necessary to determine whether the transmission pattern has been updated.

[0084] 5.1) Determine whether the row weight of the current row meets the requirements, that is, whether it reaches the target row weight n c ,

[0085] If not, it means that the current row has not been updated yet and you need to return to step 3.3);

[0086] If yes, it means that the current row has been updated. At this time, the column counter k needs to be set to zero and step 5.2 is executed;

[0087] 5.2) Determine whether the current row is the last row of the matrix:

[0088] If not, it means that although the current row has been updated, it still needs to be updated to complete the generation of the transmission pattern. At this time, the row counter i itself needs to be increased by 1, and return to step 3.3);

[0089] If so, it means that the current behavior is the last row of the matrix and the transmission pattern has been generated.

[0090] The generated transmission pattern can be used for high-sparse multi-user transmission, that is, user K can be obtained according to the decimal number d obtained in step 1.3). k , select the dth k The modulation symbol sequence w is transmitted k .

[0091] Example 2: Transmission pattern generation system for high-sparse multi-user transmission.

[0092] Reference Figure 4 This example includes a coding modulation module 1, a matrix generation module 2, a path tree generation module 3, and a column node selection module 4, wherein:

[0093] A coding and modulation module, used to obtain relevant parameters for generating a multi-user transmission pattern;

[0094] A matrix generation module, which is initially used to generate an all-zero matrix, and subsequently updates the all-zero matrix to generate a multi-user transmission pattern according to the results transmitted by the column node selection module, and transmits the updated transmission pattern to the path tree generation module;

[0095] A path tree generation module is used to generate a path tree with the current row node as the root node, and pass the generated path tree to the column node selection module;

[0096] The column node selection module is used to select a suitable column node in the path tree and pass the selected column node to the matrix generation module.

[0097] The system works as follows:

[0098] The coding and modulation module 1 encodes and modulates the bits sent by the user to obtain parameters for the matrix generation module, including the length of the first information bit sequence B s , modulation symbol sequence length n c ; Matrix generation module 2 is based on the first information bit sequence length B provided by the coding modulation module 1 s , modulation symbol sequence length n c , and an initial fixed parameter n, first generate an initial all-zero matrix, then iteratively update the current all-zero matrix according to the result output by the column node selection module 4, and pass the current updated matrix to the path tree generation module 3 until the current matrix iteration is completed to obtain the transmission pattern; the path tree generation module 3 builds a path tree with the current row node being updated in the current matrix as the root node according to the current matrix provided by the matrix generation module 2, and passes the path tree to the column node selection module 4; the column node selection module 4 selects a suitable column node according to the path tree provided by the path tree generation module 3, and passes the selected column node to the matrix generation module 2.

[0099] Embodiment 3, computer program product

[0100] The present invention provides a computer program product, including a computer program, which 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 above-mentioned multi-user transmission pattern generation method, which includes: determining a coding modulation scheme for a binary bit sequence sent by a user; generating an all-zero matrix according to parameters obtained after coding modulation and iteratively updating the matrix; generating a path tree for selecting appropriate column nodes; and selecting column nodes according to the path tree for iterative updating of the matrix.

[0101] The effect of the present invention can be further illustrated by the following simulation experiment.

[0102] 1. Simulation data parameters

[0103] Assume that the number of users in the ODMA random access model is 140, the coding scheme is RA coding with a code rate of 1 / 5, and the modulation scheme is QPSK modulation.

[0104] 2. Simulation content and result analysis

[0105] Under the above conditions, the present invention and the existing random transmission pattern generation method are used to generate transmission patterns in the ODMA random access model, and the error probabilities of each user under different signal-to-noise ratios are compared. The results are as follows: Figure 5 .

[0106] from Figure 5 It can be seen that when the signal-to-noise ratio is less than 1.8dB, its impact on the error probability of each user accounts for the largest proportion, and the advantage of the present invention cannot be seen at this time; when the signal-to-noise ratio is greater than 1.8dB, when the transmission pattern generated by the present invention is used for the ODMA random access model, the error probability of each user is smaller than that of using the randomly generated transmission pattern for the ODMA random access model. For example, when the signal-to-noise ratio is about 2.2dB, the error probability of each user using the randomly generated transmission pattern method is about 15%, while the error probability of each user using the present invention is about 6%, indicating that the use of the present invention can bring significant performance improvement to the ODMA random access scheme.

[0107] The above descriptions are only a few specific examples of the present invention and do not constitute any limitation to the present invention. It is obvious that for professionals in this field, after understanding the content and principles of the present invention, they may make various modifications and changes in form and details without departing from the principles and structures of the present invention. However, these modifications and changes based on the ideas of the present invention are still within the scope of protection of the claims of the present invention.

[0108] It should be noted that the step numbers in the specification and claims of the present invention are only for a clear description of the implementation scheme of the present invention to facilitate understanding, and the order of the numbers is not limited.

Claims

1. A transmission pattern generation method for high-sparse multi-user transmission, characterized in that: include: The binary information bits u of length B sent by user K k Divided into u ks and u kc Two parts, and the first information bit sequence u ks Convert to a decimal number d k , for the second information bit sequence u kc Perform coding modulation to obtain a length of n c The modulation symbol sequence w k , where u ks The length of B s ,u kc The length of B c =BB s ; According to the known parameter B s 、n c And the number of transmission time slots n determined in advance, generate a binary sparse matrix As a multi-user transmission pattern, 2 Bs is the column length of the matrix, the row length of the matrix is ​​consistent with the number of transmission time slots n, and the row weight of the matrix is ​​consistent with the modulation symbol sequence w k The length n c Consistent.

2. The method according to claim 1, characterized in that The second information bit sequence u kc Coded modulation is performed, and its implementation includes the following: 2a) By kc Perform channel coding to generate codewords where v k,j ∈{0,1} is the jth code element of the codeword obtained after the information bit of the kth user is channel encoded, 1≤j≤n d , the code rate of this code is B c / n d ; 2b) For codeword v k Perform QPSK modulation to obtain the modulation symbol sequence: where w k,l is the lth modulation symbol of the modulation symbol sequence after the information bit of the kth user is coded and modulated, 1≤l≤n c。 3. The method according to claim 1, characterized in that The benefit is based on the known parameter B s 、n c And the number of transmission time slots n determined in advance, a binary sparse matrix A is generated, and its implementation includes the following: 3a) Given a target matrix A, the row and column lengths are n and and row weight n c , initially generate the full zero matrix of the matrix; 3b) Update the all-zero matrix row by row until the first The update of the row results in a binary sparse matrix A, where 4. The method according to claim 3, characterized in that Step 3b) updates the all-zero matrix row by row, and its implementation includes the following: 3b1) Set row counter i to indicate that the current update is to row i, where The initial value of i is 1; 3b2) Set column counter k to indicate that k elements have been updated in row i, where 0≤k≤n c , the initial value of k is 0; 3b3) Define the current matrix for updating the all-zero matrix as Using the current matrix Construct a path tree with the i-th row as the root node; 3b4) Each time an element is updated, a column that meets the requirements needs to be selected according to the constructed path tree, and then the element pointed to by the i-th row and the selected column is updated to 1, and the counter k itself is increased by 1, thus completing an element update; 3b5) Determine whether k is equal to n c : If k is not equal to n c , then return to step 3b3); If k is equal to n c , then execute step 3b5); 3b6) Check whether i is equal to If i is not equal to Then let i itself increase by 1, and let k equal to 0, and then return to step 3b3); If i is equal to Then the update is ended and the binary sparse matrix A is obtained.

5. The method according to claim 4, characterized in that Step 3b3) uses the current matrix Construct a path tree with the i-th row as the root node. Its implementation includes the following: 3b3a) Through the current matrix Constructs a matrix about the current matrix The bipartite graph of 3b3b) According to the obtained bipartite graph Row node r i is the path tree R i The root node of R i Each path in is a sequence of row nodes and column nodes appearing alternately, its leaf nodes are all column nodes, and each node on each path appears only once; 3b3c) Set the layer number parameter d of the path tree, and each layer consists of a layer of row nodes and a layer of column nodes, and set the initial value of d to 0; 3b3d) in a bipartite graph Find the distance row node r i The nearest column node is taken as R i Middle root node r i The child node of the path tree is constructed at the 0th level. 3b3e) According to the bipartite graph In the tree R i Add all the connection trees R i The edge from the 0th layer column node to the corresponding row node of the 1st layer, and then connect the path tree R i From all row nodes in the first layer to their nearest column nodes, we get the path tree R i 1st layer; 3b3f) And so on, according to the bipartite graph In the tree R i Add all the connection trees R i The edge from the column node of the d-1th layer to the row node corresponding to the dth layer, and then connect the path tree R i From all row nodes in the dth layer to their nearest column nodes, we get the path tree R i The dth layer, at this time, the number of layers d itself is increased by 1; 3b3g) Repeat step 3b3f) until the path tree R i When a certain layer is reached and cannot be expanded any further, the construction of the path tree is completed.

6. The method according to claim 4, characterized in that In step 3b4), each time an element is updated, a column that meets the requirements is selected according to the constructed path tree, and its implementation includes the following: 3b4a) For the path tree R i , let the distance d(r i ,c j ) is the root node r i To column node c j The length of the shortest path, the selected path tree R i The Lth layer of Represents the path tree R i and the root node r i The set of column nodes whose distance is less than 2L+1, let express The complement of all column nodes is represented by C = {c1, c2, ..., c j ,…,c n },but Where j∈{1,2,......,n}, n is the total number of column nodes; 3b4b) According to the number of layers L selected in step 3b4a), from the path tree R i Select the qualifying column that meets one of the following two conditions: Case 1: The path tree cannot be expanded after reaching the Lth layer, and the candidate set Size To be less than n; at this time according to the current matrix exist Select a column node c with the minimum column weight j ; The second case: Under the condition of i Select distance r in the (L+1)th layer i The farthest column node c j .

7. A transmission pattern generation system for high-sparse multi-user transmission, comprising: A coding and modulation module, used to obtain relevant parameters for generating a multi-user transmission pattern; A matrix generation module, which is initially used to generate an all-zero matrix, and subsequently updates the all-zero matrix to generate a multi-user transmission pattern according to the results transmitted by the column node selection module, and transmits the updated transmission pattern to the path tree generation module; A path tree generation module is used to generate a path tree with the current row node as the root node, and pass the generated path tree to the column node selection module; The column node selection module is used to select a suitable column node in the path tree and pass the selected column node to the matrix generation module.

8. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for generating a multi-user transmission pattern according to any one of claims 1 to 6 is implemented.

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