Adaptive threshold adjustment decoding method, device, decoder and medium

Abstract

The present invention relates to a decoding method, device, decoder and medium for adaptive threshold adjustment. The method comprises: initializing soft information and setting a threshold; iteratively updating the check node based on the threshold according to the received soft information to generate check information and classification results; in the iterative process, adaptively adjusting the threshold according to the classification result, and judging whether to update the check node according to the classification result; the updated check node transmits the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result; performing decoding judgment according to the variable node update result, if the judgment fails, continuing the iterative processing until the preset number of iterations is reached, and outputting the decoding result. The method provided by the present invention can reduce the computational complexity, speed up the decoding speed, and improve the robustness of the decoding performance.

Description

Technical Field

[0001] The present invention relates to the field of mobile communication technology, and in particular to a decoding method, device, decoder and medium for adaptive threshold adjustment. Background Art

[0002] LDPC (Low-Density Parity-Check Code) is a forward error correction code. Due to its performance close to the channel capacity, it is widely used in various high-speed communication systems, such as satellite communications, wireless communications, storage devices, and broadcasting systems.

[0003] The decoding process of LDPC codes is usually based on iterative algorithms, such as the BP (Belief Propagation) algorithm. Although it has excellent error correction capabilities, the computational complexity of the BP algorithm increases significantly with the increase in LDPC code length and the complexity of the modulation scheme. In particular, when the noise environment is harsh, more iterations will lead to greater delays.

[0004] In addition, in the decoding process, the reasonable setting of the threshold is also crucial. If the threshold is not set properly during the decoding process, it will affect the efficiency of iteration and the bit error performance. Setting a threshold that is too high may lead to high complexity and increase the decoding time; setting a threshold that is too low may lead to premature termination of decoding and increase the decoding error. Therefore, how to reduce the decoding complexity while improving the decoding speed and bit error performance has become an urgent problem to be solved. Summary of the invention

[0005] Based on this, it is necessary to provide a decoding method, device, decoder and medium with adaptive threshold adjustment that can reduce computational complexity, speed up decoding speed and improve decoding performance in response to the above technical problems.

[0006] A decoding method with adaptive threshold adjustment, the method comprising:

[0007] Initialize soft information; set threshold;

[0008] According to the received soft information, the check node is iteratively updated based on the threshold to generate check information and classification results; in the iterative process, the threshold is adaptively adjusted according to the classification result, and whether to update the check node is determined according to the classification result;

[0009] The updated check node transmits the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result;

[0010] A decoding decision is made according to the update result of the variable node. If the decision is not passed, the iterative process is continued until a preset number of iterations is reached, and a decoding result is output.

[0011] A decoding device with adaptive threshold adjustment, the device comprising:

[0012] The initial setting module is used to initialize soft information and set thresholds;

[0013] An adaptive adjustment module, configured to iteratively update the check node based on the threshold according to the received soft information, and generate check information and classification results; in the iterative process, adaptively adjust the threshold according to the classification result, and determine whether to update the check node according to the classification result;

[0014] An updating module, which is used for the updated check node to transmit the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result;

[0015] The decoding decision module is used to make a decoding decision according to the update result of the variable node. If the decision is not passed, the iterative processing is continued until a preset number of iterations is reached, and the decoding result is output.

[0016] A decoder adopts the decoding method of adaptive threshold adjustment to perform decoding.

[0017] A computer-readable storage medium stores a computer program, which implements the steps of the decoding method for adaptive threshold adjustment when executed by a processor.

[0018] The above-mentioned decoding method, device, decoder and medium with adaptive threshold adjustment first initialize soft information and set a threshold; then, according to the received soft information, the check node is iteratively updated based on the threshold to generate check information and classification results; in the iterative process, the threshold is adaptively adjusted according to the classification result, and it is determined whether to update the check node according to the classification result; the updated check node transmits the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result; a decoding decision is made according to the variable node update result, and if the decision fails, the iterative processing continues until a preset number of iterations is reached, and the decoding result is output.

[0019] The method provided by the present invention can not only improve the flexibility and accuracy of information processing and improve decoding efficiency by adaptively adjusting the threshold value through classification results, but also can be widely used in different decoding modes, dynamically adapt to various channel changes, and maintain good decoding performance under different decoding conditions. According to the classification results, it is judged whether to update the check node, and the check information of the updated check node is passed to the connected variable node, and the node that is not updated is not processed, which can reduce unnecessary calculation and resource waste, effectively reduce calculation complexity, improve decoding speed, reduce decoding time, and have strong robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying creative work.

[0021] Figure 1 A schematic diagram of a flow chart of a decoding method for adaptive threshold adjustment in one embodiment;

[0022] Figure 2 A schematic diagram of a framework for adaptively adjusting a threshold value according to a classification result in one embodiment;

[0023] Figure 3 It is a structural block diagram of a decoding device with adaptive threshold adjustment in one embodiment.

[0024] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. 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.

[0026] It can be understood that the technical solutions between the various embodiments of the present invention can be combined with each other, but it must be based on the fact that ordinary technicians in the field can implement it. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0027] The following will describe the implementation of the present invention in detail with reference to the accompanying drawings in the embodiment diagram of the present invention.

[0028] Example 1

[0029] The present embodiment discloses a decoding method with adaptive threshold adjustment, which can not only improve the flexibility and accuracy of information processing and improve decoding efficiency by adaptively adjusting the threshold through classification results, but also can be widely used in different decoding methods, dynamically adapt to various channel changes, and maintain good decoding performance under different decoding conditions. Whether to update the check node is determined according to the classification result, and the check information is passed to the connected variable node for the updated check node, and the unupdated node is not processed, which can reduce unnecessary calculations and resource waste, effectively reduce the calculation complexity, improve the decoding speed, reduce the decoding time, and has strong robustness. The decoding method provided by the present invention includes but is not limited to all decoding algorithms applicable to LDPC codes, such as BP decoding method, MS decoding method, NMS decoding method, etc. For ease of understanding, the subsequent embodiments are mainly explained with LDPC codes, but they are not used as a limitation to the scheme of the present invention.

[0030] like Figure 1 As shown, the decoding method for adaptive threshold adjustment provided by this embodiment includes the following steps:

[0031] Step 201, initialize soft information and set thresholds.

[0032] Step 202, according to the received soft information, the check nodes are iteratively updated based on the threshold to generate check information and classification results; during the iteration process, the threshold is adaptively adjusted according to the classification result, and it is determined whether to update the check nodes according to the classification result.

[0033] Step 203: The updated check node transmits the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result.

[0034] Step 204, a decoding decision is made according to the variable node update result. If the decision is not passed, the iterative process is continued until a preset number of iterations is reached, and a decoding result is output.

[0035] In the specific implementation process of step 201, the soft information is used as the initial information of the variable node to be transmitted to the check node to form the initial state of the decoding. At the same time, an initial threshold is set As a benchmark reference, it is used to judge the reliability of the check nodes and variable nodes in the initial state, and in subsequent calculations, the initial threshold is adaptively adjusted according to the iterative calculation .

[0036] In the specific implementation process of step 202, the check node is iteratively updated based on the adaptive threshold method to generate check information and classification results. The check information includes the updated probability value, trust judgment result or other indicators, which are mainly used to reflect the reliability and accuracy of the current information. The check information will provide an update of the variable node state to help with subsequent decoding decisions, thereby determining whether the decoding requirements are met or whether further iteration is required.

[0037] There are four main classification results. The first type of check node is that the check equation is established and the soft information value is greater than the threshold; the second type of check node is that the check equation is established and the soft information value is less than the threshold; the third type of check node is that the check equation is not established and the soft information value is less than the threshold; the fourth type of check node is that the check equation is not established and the soft information value is greater than the threshold. Among them, the check equation reflects the relationship between the variable nodes in the decoding process, which is mainly used to check the correctness of the codeword. If the check equation is not established, it means that there may be an error in the codeword. Soft information is the probability information used in the decoding process. It reflects the degree of confidence in a certain codeword position in the decoding process. If the soft information is less than the threshold, it means that the uncertainty is high and there may be strong noise interference.

[0038] It can be seen that when the check node belongs to the first category, it indicates that the check node is relatively stable at the current moment; when the check node belongs to the second category, it indicates that the check node is less stable at the current moment; and when the check node belongs to the third and fourth categories, it indicates that the check node is unstable at the current moment. Based on this, the present invention adaptively adjusts the threshold to optimize the iterative process; it can also focus on unstable check nodes to determine whether the check nodes need to be updated, thereby reducing unnecessary calculation overhead.

[0039] Specifically, the threshold is adaptively adjusted according to the classification result, including: in any iteration process, the classification result has the following combination:

[0040] The first combination includes a first-type check node, a second-type check node, and a third-type check node.

[0041] The second combination includes the first type of check nodes, the second type of check nodes, and the fourth type of check nodes.

[0042] The third combination includes the first type of check nodes and the second type of check nodes.

[0043] The fourth combination includes the first type of check nodes, the second type of check nodes, the third type of check nodes and the fourth type of check nodes.

[0044] See also Figure 2When the classification result is the first combination, the threshold remains unchanged; when the classification result is the second combination, the threshold is increased; when the classification result is the third combination, the threshold is decreased; when the classification result is the fourth combination, the threshold is increased.

[0045] According to the combination of classification results obtained in each iterative process, the information of the variable node can be appropriately received according to the combination where all the current check nodes are located, so as to adaptively adjust the threshold dynamically, thereby optimizing the iterative process, improving the decoding efficiency, accelerating the decoding speed, optimizing the use of computing resources and the robustness of the system. The main reason why the threshold corresponding to the check node of the first combination is not changed is that there are some check nodes that are not saturated but the corresponding check equation is established, so it is only necessary to further consolidate the unsaturated check node on this basis. The main reason for the increase in the threshold corresponding to the check node of the second combination is that there are both currently saturated check nodes and unsaturated check nodes whose soft information is greater than the threshold, indicating that the currently saturated check node is a pseudo-saturated node, and the threshold needs to be further increased. The check node needs to receive the information of all the variable nodes connected to it. The main reason for the reduction in the threshold corresponding to the check node of the third combination is that the check equations are all established, then the decoded data at this time is correct and the current iterative processing can be ended. In order to facilitate the complexity of the later decoding process, the threshold needs to be appropriately reduced. The main reason why the threshold corresponding to the check node of the fourth combination needs to be increased is that the four situations corresponding to the check node are all present, which means that the stable check node at this time is also a pseudo-stable check node, and the threshold needs to be increased to transform the pseudo-stable into stable.

[0046] Determining whether to update the check node according to the classification result includes: when the check node is a first-class check node, not updating the check node; when the check node is a second-class check node, partially updating the check node; when the check node is a third-class check node or a fourth-class check node, completely updating the check node.

[0047] It can be understood that when the check node is a first type of check node, it indicates that the check node is relatively stable at the current moment, and there is no need to update the variable node connected to the check node.

[0048] When the check node is a second-class check node, it indicates that the check node is less stable at the current moment and needs to be partially updated. Specifically, for each check node, it is necessary to sort the variable nodes connected to it in increasing order, and then select the information of the first w variable nodes and pass them to the check node. The information of these variable nodes will be used to update the soft information of the check node to improve its stability and decoding performance.

[0049] When the check node is a third-type check node or a fourth-type check node, it indicates that the check node is unstable at the current moment and all check nodes need to be updated. Specifically, for each check node, the information of all variable nodes connected to the check node is directly transmitted to the check node to ensure that the decoding process is more accurate and efficient.

[0050] In this way, there is no need to update all the check nodes, which reduces the computational overhead in the decoding process, reduces the computational complexity, speeds up the entire decoding process, enhances system robustness and reduces bit error rate, and improves the overall decoding performance and communication quality.

[0051] In the specific implementation process of step 203, the check node transmits the generated check information to the connected variable node through the feedback mechanism. After receiving the check information, the variable node calculates in combination with its own initial soft information, updates its state, and generates a variable node update result, which is the new soft information. The variable node stores the new soft information and feeds back the new state to the check node, forming a cycle. Through this step, the effective flow of information between the check node and the connected variable is ensured, so as to perform dynamic adjustment and optimization; the variable node update result provides a basis for subsequent decoding decisions, ensuring that each iteration can use the latest information to improve decoding accuracy.

[0052] In the specific implementation process of step 204, the latest variable node update result is used to analyze the soft information of the current variable node and make a decoding decision; after the decision, the accuracy of the decoding result is checked. If the decision is passed, it means that the current state has met the decoding requirements and the system will end the iteration. If the decision is not passed, check whether the preset number of iterations has been reached. If not, return to the check node for further iterative updates to obtain more accurate information until the preset number of iterations is reached and the decoding result is output. It can be understood that the decoding decision is the core of the decoding process and directly affects the accuracy of the final output. Through the feedback of the decision, the system can dynamically adjust the iterative process to ensure optimized decoding under changing channel conditions. Through multiple iterations and feedback mechanisms, it can still provide reliable decoding results in the presence of noise and interference.

[0053] Although this embodiment Figure 1 The steps in the process are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of the steps, and the steps can be executed in other orders. Figure 1At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0054] Example 2

[0055] Based on the decoding method with adaptive threshold adjustment in Embodiment 1, this embodiment discloses a decoding device with adaptive threshold adjustment, such as Figure 3 As shown, the decoding device with adaptive threshold adjustment includes: an initial setting module 401, an adaptive adjustment module 402, an update module 403 and a decoding decision module 404, wherein:

[0056] The initial setting module 401 is used to initialize soft information and set a threshold.

[0057] The adaptive adjustment module 402 is used to iteratively update the check nodes based on the threshold according to the received soft information, and generate check information and classification results; in the iterative process, the threshold is adaptively adjusted according to the classification result, and whether to update the check nodes is determined according to the classification result.

[0058] The updating module 403 is used for the updated check node to transmit the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result;

[0059] The decoding decision module 404 is used to make a decoding decision according to the variable node update result. If the decision is not passed, the iterative processing is continued until a preset number of iterations is reached, and the decoding result is output.

[0060] In this embodiment, the specific working process and working principle of the initial setting module 401, the adaptive adjustment module 402, the update module 403 and the decoding decision module 404 are the same as those in the method of embodiment 1, so they are not described in detail in this embodiment. Each unit module can be implemented in whole or in part by software, hardware and a combination thereof, and each unit module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above unit modules.

[0061] Example 3

[0062] This embodiment provides a decoder, which uses the decoding method of adaptive threshold adjustment in Embodiment 1 to perform parallel decoding on the received data to be decoded. It is worth noting that the decoder provided in this embodiment is suitable for data to be decoded including an information part and a check part, such as LDPC code.

[0063] The following steps are involved:

[0064] Step 301: According to an information transmission protocol, a parity check matrix under different code rates and code lengths is converted into a quasi-cyclic parity check matrix.

[0065] Specifically, the data to be decoded processed by the decoder in the information transmission protocol includes an information part and a check part; the length of the data to be decoded is , the length of the information part is , the length of the check part is = - .

[0066] According to the information part and the check part, the parity check matrix is ​​divided into two parts: the information matrix and the check matrix. The size of the parity check matrix is OK columns, the size of the information matrix is OK The size of the check matrix is OK List.

[0067] According to the check bit accumulator address corresponding to different code rates in the information transmission protocol The constants of the parameters in the bit rate dependence The remainder is calculated to obtain the points corresponding to different cycles, and the remainders obtained are 0, 1, 2, ..., .

[0068] Select from the remainders obtained above The parity check matrix is ​​transformed row by row according to the check bit accumulator addresses corresponding to different remainders to obtain a row simplified matrix H_row; then the check part corresponding to the row simplified matrix H_row is transformed column by column to obtain a quasi-cyclic parity check matrix.

[0069] Among them, according to the check bit accumulator address , perform row transformation on the parity check matrix to obtain a row simplified matrix, which is expressed as:

[0070] ;

[0071] In the formula, Indicates the number of rows after processing. represents the number of rows corresponding to the unprocessed parity check matrix, Indicates The address of the check bit accumulator; represents the bit rate dependency constant; Indicates the length of the block; Indicates the number of rows in the matrix.

[0072] According to the row simplification matrix, the H matrix with different code rates is constructed, that is, , the expression is:

[0073] ;

[0074] In the formula, Represents the matrix after simplifying the matrix transformation.

[0075] Then the row transformation of H matrix is ​​performed, that is, when Before the Matrix The column is composed of multiple quasi-circular submatrices, then the size of the submatrix is .

[0076] Based on this, the check part corresponding to the row simplification matrix is ​​transformed into columns to obtain a quasi-cyclic parity check matrix, which is expressed as:

[0077] .

[0078] Step 302: Based on the quasi-cyclic parity check matrix, the corresponding position of the check information in the received data to be decoded is transformed.

[0079] Specifically, determine how many parallel paths are used to input the data to be decoded. For example, in the DVB-S2 standard protocol, the data to be decoded is input in 40 parallel paths. Therefore, 40 paths of information to be decoded are input in parallel in one clock, and written into 40 RAMs (Random Access Memory). The specific address allocation is shown in the following formula:

[0080] ;

[0081] In the above matrix, the rows represent a total of 40 RAMs, the columns represent the number of RAMs occupied in each RAM, and the values ​​in the matrix represent the addresses of the data to be decoded that are input to the decoding device.

[0082] In order to adapt to the various LDPC codes with different code rates and code lengths in DVB-S2, two ROMs (Read-Only Memory) need to be configured to store the data to be decoded in The first RAM and in this The number of addresses in the RAM .

[0083] Through the The number of addresses in the RAM , you can Accurately read the corresponding value from one of the RAMs.

[0084] Step 303: decoding is performed using a partially parallel layered decoding method. During the decoding process, adaptive threshold adjustment is performed based on the method in Embodiment 1.

[0085] It is worth noting that before decoding, the random H matrix is ​​converted into a parity check matrix in step 301, and the position of the data to be decoded is changed by column permutation in step 302. In the present embodiment, when explaining the decoder, the 360-way parallel architecture is mainly used to decode the LDPC code under the FPGA architecture, and its main purpose is to adapt to the decoding of multiple code rates in the DVB-S2 standard protocol. When it is other information transmission protocols, other architectures can be used accordingly, and the number of parallel input paths can be adjusted accordingly.

[0086] Example 4

[0087] This embodiment discloses a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the method in the above-mentioned embodiment 1 is implemented.

[0088] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0089] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above-mentioned embodiments only express several implementation modes of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A decoding method with adaptive threshold adjustment, characterized in that: The method comprises: Initialize soft information and set threshold; According to the received soft information, the check node is iteratively updated based on the threshold to generate check information and classification results; in the iterative process, the threshold is adaptively adjusted according to the classification result, and whether to update the check node is determined according to the classification result; The updated check node transmits the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result; Perform a decoding decision according to the update result of the variable node, and if the decision fails, continue to iterate until a preset number of iterations is reached, and output a decoding result; The classification results include: The first type of check node: the check equation is established and the soft information value is greater than the threshold; The second type of check node: the check equation is established and the soft information value is less than the threshold; The third type of check node: the check equation is not established and the soft information value is less than the threshold; The fourth type of verification node: the verification equation is not established and the soft information value is greater than the threshold; Adaptively adjusting the threshold according to the classification result includes: In any iteration process, the classification results have the following combinations: The first combination includes a first-type check node, a second-type check node, and a third-type check node; The second combination includes the first type of check nodes, the second type of check nodes, and the fourth type of check nodes; A third combination includes a first-type check node and a second-type check node; A fourth combination includes a first-type check node, a second-type check node, a third-type check node, and a fourth-type check node; When the classification result is the first combination, the threshold remains unchanged; when the classification result is the second combination, the threshold is increased; when the classification result is the third combination, the threshold is decreased; when the classification result is the fourth combination, the threshold is increased; Determining whether to update the check node according to the classification result includes: When the check node is a first type of check node, the check node is not updated; When the check node is a second type of check node, partially updating the check node; When the check nodes are third-type check nodes or fourth-type check nodes, all the check nodes are updated.

2. A decoding device with adaptive threshold adjustment, characterized in that: The decoding method with adaptive threshold adjustment according to claim 1, wherein the device comprises: The initial setting module is used to initialize soft information and set thresholds; An adaptive adjustment module, configured to iteratively update the check node based on the threshold according to the received soft information, and generate check information and classification results; in the iterative process, adaptively adjust the threshold according to the classification result, and determine whether to update the check node according to the classification result; An updating module, which is used for the updated check node to transmit the check information to the connected variable node, and the variable node is updated accordingly according to the received check information to obtain the variable node update result; The decoding decision module is used to make a decoding decision according to the update result of the variable node. If the decision is not passed, the iterative processing is continued until a preset number of iterations is reached, and the decoding result is output.

3. A decoder, characterized in that: include: The decoding is performed using the decoding method with adaptive threshold adjustment as described in claim 1.

4. The decoder according to claim 3, characterized in that The data to be decoded processed by the decoder in the information transmission protocol includes an information part and a check part; wherein the length of the data to be decoded is , the length of the information part is , the length of the check part is ; According to the information part and the check part, the parity check matrix is ​​divided into two parts: the information matrix and the check matrix, wherein the size of the parity check matrix is OK columns, the size of the information matrix is OK The size of the check matrix is OK List; According to the dependency constant of the check bit accumulator address on the code rate Find the remainder and select Performing row transformation on the parity check matrix using check bit accumulator addresses corresponding to different remainders to obtain a row simplified matrix; A column transformation is performed on the check part corresponding to the row simplification matrix to obtain a quasi-cyclic parity check matrix.

5. The decoder according to claim 4, characterized in that According to the check bit accumulator address, the parity check matrix is ​​transformed row by row to obtain a row simplified matrix, which is expressed as: ； In the formula, Indicates the number of rows after processing. represents the number of rows corresponding to the unprocessed parity check matrix, Indicates The address of the check bit accumulator; represents the bit rate dependency constant; Indicates the length of the block; Indicates the number of rows in the matrix.

6. The decoder according to claim 5, characterized in that The check part corresponding to the row simplification matrix is ​​transformed into columns to obtain a quasi-cyclic parity check matrix, which is expressed as follows: 。 7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the decoding method with adaptive threshold adjustment according to claim 1 are implemented.

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