A soft information aided general hard decision decoding method, device and medium

Abstract

The application discloses a soft information assisted general hard decision decoding method, device and medium; the method is applied to a digital communication system: a sending end encodes and modulates information sequences, and transmits the information sequences to a receiving end through a channel; the receiving end obtains hard decision bit data and corresponding soft information, marks the hard decision bits based on the soft information, and constructs a to-be-decoded unit and an associated relationship thereof according to a coding structure; only for the positions corresponding to high-unreliable bits and unreliable bits, candidate test error pattern sequences are generated, the sequences are used for hard decision decoding of each to-be-decoded unit, the hard decision bit data is updated according to a decoding result, and the decoding is iteratively executed until a preset stop condition is met, and finally, a decoding result is output. The application can reduce an error pattern search space, reduce decoding complexity and error correction risk, and improve data transmission reliability.

Description

Technical Field

[0001] This invention belongs to the field of channel decoding technology, specifically relating to a soft-information-assisted general hard-decision decoding method, device, and medium. Background Technology

[0002] In high-speed fiber optic communication, data storage, and other highly reliable digital communication systems, forward error correction (FEC) is a key technology for ensuring data transmission reliability. As transmission rates and system throughput continue to increase, decoders need to balance power consumption, hardware complexity, and decoding latency while providing high gain. Hard-decision decoding offers advantages such as low complexity and low power consumption, but its decoding performance is typically limited; soft-decision decoding, while achieving higher gain, usually has higher implementation complexity and resource consumption.

[0003] Therefore, utilizing a small amount of soft information to improve decoding performance within the hard-decision decoding framework, balancing complexity and performance, has significant research value and engineering implications. In recent years, guessing random additive noise decoding has received widespread attention as a general hard-decision decoding approach. This type of method generates trial error patterns and tests them one by one to determine the error pattern that makes the received sequence a valid codeword. However, existing methods, lacking soft information guidance, typically involve exhaustive searching of a large number of bit positions, resulting in excessive redundant searches, high computational overhead, and a high risk of miscorrection.

[0004] Taking product code iterative decoding as an example, if error patterns are directly generated for all bit positions of each component codeword, a large number of invalid attempts will still be made under high signal-to-noise ratio conditions, resulting in unnecessary complexity overhead. Therefore, how to construct a general hard-decision decoding framework that can guide the error pattern generation and search process with soft information, and flexibly implement it in specific code types, has become an urgent technical problem to be solved. Summary of the Invention

[0005] The present invention aims to overcome the shortcomings of the prior art by proposing a general hard-decision decoding method, device, and medium assisted by soft information. The goal is to mark the credibility of received bits through channel soft information, constrain the generation range of error patterns and optimize the search order by marking the results, thereby improving decoding performance while maintaining the low complexity advantage of hard-decision decoding.

[0006] The present invention adopts the following technical solution to solve the technical problem: The present invention discloses a general hard-decision decoding method assisted by soft information, characterized in that it is applied to a digital communication scenario consisting of a transmitter, a channel, and a receiver. The receiver includes a hard-decision demodulator, a soft-decision demodulator, and a general hard-decision decoder assisted by soft information. The general hard-decision decoding method includes the following steps: Step 1: The sending end obtains the information sequence. I And use a preset encoding method to encode the information sequence I Perform channel coding to generate coded data blocks. C ; Step 2: The sending end sends data blocks. C Modulation is performed to obtain the symbol matrix to be transmitted. X ; Step 3: Symbol Matrix to be Transmitted X After being transmitted through a noisy channel to the receiving end, the received symbol sequence matrix is ​​obtained. Y ; Step 4: The receiving end uses a hard decision demodulator to... Y The process is performed to obtain the hard decision bit matrix. B ; Soft decision demodulator Y Calculations are performed to obtain the soft information matrix. L ; Step 5: Soft-information-assisted universal hard-decision decoder based on... L The log-likelihood ratio for each row and column in the middle. B The corresponding row and column bits are used to mark the credibility, resulting in... B The tagging information; the tagging information values ​​include: high reliability bit HRB, unreliable bit UB, and high unreliability bit HUB; Step 6: According to the encoding structure corresponding to the preset encoding method, convert the hard decision bit matrix... B The hard decision bits are organized into multiple units to be decoded, and the associated units to be decoded for each unit are determined. Step 7: Based on the marking information, generate a candidate test error pattern sequence only for the positions corresponding to the high unreliable bit HUB and unreliable bit UB in each unit to be decoded, according to the confidence category and quantity of the error positions. Based on the candidate test error pattern sequence, hard-decision decoding is performed on each unit to be decoded, and the decoding result of each unit is used to update the decoding process. B ; Hard-decision decoding is performed on the updated hard-decision bit matrix until a preset stopping condition is met, thus obtaining the final decoding result. ; Based on the preset encoding method, the final decoding result The information sequence was recovered from the middle I′ .

[0007] The present invention provides a general hard-decision decoding method with soft information assistance, wherein step 5 includes: Step 5.1, Definition This is the first credibility threshold. This is the second credibility threshold, and ; Step 5.2, let Representing the soft information matrix L The Middle i Line 1 j Log-likelihood ratio, let B The Middle i Line 1 j column bits are denoted as ; when At that time, then order The corresponding tag information is HRB; when At that time, then order The corresponding tagging information is UB; when At that time, then order The corresponding tag information is HUB.

[0008] Furthermore, step 6 includes: Step 6.1: Let any unit to be decoded be 1× n A binary row vector of dimension, denoted as ,in, Indicates the unit to be decoded The Middle j Hard decision bits at each position, ; Indicates the length of the unit to be decoded; Step 6.2: Based on the hard decision bits contained in each unit to be decoded, establish the association relationship between each unit to be decoded; connect the units to be decoded... Other units to be decoded that share at least one hard decision bit are identified as The associated unit to be decoded.

[0009] Furthermore, step 7 includes: Step 7.1, Definition As the distance boundary, The range of values ​​is ; Define the state set of the unit to be decoded ,in, Indicates the number of units to be decoded. Indicates the first The decoding status of each unit to be decoded. The range of values ​​is ; This indicates that the i-th unit to be decoded may contain an error bit. Indicates the first i One unit to be decoded was successfully decoded. Indicates the firsti One unit to be decoded failed to be decoded; Define the data before decoding and decoded data and initialize distance limits. , S If all elements in the set are 0, let... ; Step 7.2, based on B The tagging information , S and Hard-decision decoding is performed sequentially on all units whose decoding state is 0. If decoding is successful, the state of the corresponding unit is set to 1, and the states of associated units affected by the decoding result are set to 0. If decoding fails, the state of the corresponding unit is set to 2. After decoding all units whose state is 0, the decoded data is obtained. ; Step 7.3: Determine if the preset stopping condition is met; if so, proceed. As the final decoding result output; if it does not meet the requirements, then according to ,right , S and After the update, return to step 7.2 and execute sequentially; Step 7.4: Based on the preset encoding method, extract the final decoding result. The information sequence was recovered from the middle I′ .

[0010] Furthermore, step 7.2 includes: Step 7.2.1: Read the unit to be decoded The tagging information in; Define a set of highly unreliable location indices Among them, the set of highly unreliable location indices Each element in the code is a unit to be decoded. A bit position index marked as HUB; Define an unreliable location index set Among them, the unreliable location index set Each element in the code is a unit to be decoded. A bit position index marked as UB; Step 7.2.2, Define the first i The test error pattern is 1× n A 3D binary row vector, denoted as ,in, Indicates the first i Test error pattern The Middle j Bits at each position; Highly unreliable location index set The system enumerates the indices of each position, assigning a 1 to the bit at the corresponding position index for each enumeration and setting the bits at the remaining positions to 0. The resulting set of all test error patterns is denoted as [the set of patterns]. ; Highly unreliable location index set Enumerate any two distinct position indices, assign the bit value of the corresponding position to 1, and assign the bit value of the remaining positions to 0. The set of all test error patterns generated is denoted as . ; Unreliable location index set The system enumerates the indices of each position, assigning a 1 to the bit at the corresponding position index for each enumeration and setting the bits at the remaining positions to 0. The resulting set of all test error patterns is denoted as [the set of patterns]. ; Highly unreliable location index set Enumerate any three different position indices, assign the bit value of the position corresponding to the three enumerated position indices to 1, and assign the bit value of the remaining positions to 0. The set of all test error patterns generated is denoted as . ; For each set of highly unreliable location indices and unreliable location index set Enumerate a position index, assign the bit value of the two positions corresponding to the enumerated position indices to 1, and assign the bit value of the remaining positions to 0. The set of all generated test error patterns is denoted as . ; in, Indicates the first i Test error pattern Middle in the set of highly unreliable position indices The number of positions that are assigned a value of 1; Indicates the first i Test error pattern In the unreliable location index set The number of positions that are assigned a value of 1; Indicates the first i Test error pattern The total number of positions in the middle that are assigned a value of 1; and , , , , These are used to test scenarios where one HUB location, two HUB locations, one UB location, three HUB locations, and one HUB location and one UB location both malfunction simultaneously. Step 7.2.3: Construct different distance boundaries The following is an ordered sequence of error patterns ; make The ordered sequence of error patterns corresponding to the time Depend on composition; make The ordered sequence of error patterns corresponding to the time Depend on , It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; Step 7.2.4, Definition This is the parity check matrix for the encoding method of the current unit to be decoded, and it is used for... Perform verification: like Satisfy the verification relationship Then directly output the decoding result. And determine if the decoding is successful; otherwise, iterate through... Each element in; If in Find satisfy Candidate error patterns Then output the decoding result. It determines whether the decoding was successful; otherwise, it outputs the decoding result. The decoding was deemed to have failed.

[0011] Furthermore, step 7.3 includes: If the state set of the unit to be decoded SIf all elements in the array are 1, then... Output the final decoding result and exit the iteration; If the state set of the unit to be decoded S All elements in the array are non-zero and Then Output the final decoding result and exit the iteration; like and If consistent, then Output the final decoding result and exit the iteration; like and Inconsistent set of states of units to be decoded S If there exists an element that is 0, then let Assign to and will S After resetting the element with a value of 2 to 0, return to step 7.2 to continue execution; like and Inconsistent set of states of units to be decoded S All elements in the middle are not 0 and Less than 5, let Assign to , Assign to and will S After resetting the element with a value of 2 to 0, return to step 7.2 to continue execution.

[0012] The present invention provides an electronic device, which includes a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the electronic device performs the method.

[0013] The present invention provides a computer-readable storage medium on which a computer program is stored, wherein when the computer program is executed by a processor, the method is implemented.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention utilizes channel soft information to divide received bits into three different confidence levels through two thresholds, excluding highly reliable bits from the error pattern search space, and generating candidate error patterns only for unreliable bits and highly unreliable bits, thereby reducing the search space and decoding complexity. 2. This invention classifies candidate error patterns according to the type and number of flipped bits, and organizes the search order in conjunction with distance limits, so that more likely error patterns are tried first, thereby improving search efficiency and reducing the risk of false correction. Detailed Implementation

[0015] The present invention will be further described below with reference to embodiments. It should be noted that these embodiments are only for explaining the present invention and are not intended to limit the scope of protection of the present invention. For other code types that can divide the units to be decoded according to the coding structure, establish the association relationship between the units to be decoded, and use the verification relationship to determine the validity of the decoding result, the soft information-assisted general hard decision decoding method of the present invention can be used. This embodiment uses product codes as an example for illustration.

[0016] This embodiment uses BCH(31,21,5) code as the row and column component codes of the product code. The code length of this component code is... Information bit length The parity bit length is 10, the product code matrix is ​​a 31×31 bit matrix, the modulation method is BPSK modulation, and the transmission channel is an additive white Gaussian noise channel. A general hard-decision decoding process with soft information assistance is as follows.

[0017] Step 1: The sending end acquires a 441-bit information sequence. I and information sequence I The information bits are arranged into a 21×21 dimensional information bit matrix. Each row of the information bit matrix is ​​encoded using BCH(31,21,5) code to generate the corresponding row parity bits; then each column of the row-encoded matrix is ​​encoded to generate the corresponding column parity bits, thus obtaining a 31×31 dimensional encoded data block. C .

[0018] Step 2: The sending end processes the encoded data block. C Each bit in the matrix is ​​BPSK modulated to obtain a 31×31 dimensional symbol matrix to be transmitted. X Specifically, bit 0 is mapped to symbol 1, and bit 1 is mapped to symbol 2. 1, that is:

[0019] in, Represents data block C The Middle i Line 1 j Column bits, Represents the matrix of symbols to be sent X The Middle i Line 1 j Modulation symbols of the column, The value is 1 or 1.

[0020] Step 3: Symbol Matrix to be Transmitted X After being transmitted through an additive white Gaussian noise channel, the signal is received at the receiver, which then obtains the received symbol sequence matrix. Y ,in:

[0021] in, With a mean of 0 and a variance of Gaussian white noise, Represents the received symbol sequence matrix Y The Middle i Line 1 j The noisy BPSK symbol of the column.

[0022] Step 4: The hard decision demodulator at the receiving end... Y Hard decision is performed on each noisy BPSK symbol in the matrix to obtain a 31×31 hard decision bit matrix. B .when season ;when season .

[0023] The soft decision demodulator at the receiving end Y The log-likelihood ratio of each noisy BPSK symbol in the matrix is ​​calculated to obtain the soft information matrix. L Under the BPSK modulation and additive white Gaussian noise channel conditions of this embodiment, the log-likelihood ratio is... It can be represented as: .

[0024] The absolute value of the log-likelihood ratio is used to characterize the reliability of the hard decision result: the larger the absolute value, the lower the probability of the corresponding hard decision bit being wrong; the smaller the absolute value, the higher the probability of the corresponding hard decision bit being wrong, and the more worthy the corresponding bit is to be tested first.

[0025] Step 5: The soft-information-assisted universal hard-decision decoder uses the soft-information matrix. L For hard decision bit matrix B Each bit in the data is marked with a confidence level to obtain... B The tagging information includes: High Reliability Bit (HRB), Unreliable Bit (UB), and High Unreliable Bit (HUB).

[0026] definition This is the first credibility threshold. This is the second credibility threshold, and In this embodiment, it is set .

[0027] For hard decision bits : when At that time, Marked as High Reliability Bit (HRB); when At that time, Marked as unreliable bit UB; when At that time, Marked as a high unreliable bit HUB.

[0028] The threshold mentioned above is only one specific value. In practical applications, it can be determined based on the code type, channel conditions, signal-to-noise ratio, and decoding performance requirements. and .

[0029] set up The absolute value of the log-likelihood ratio can be divided into three non-overlapping intervals: high reliability, generally unreliable, and highly unreliable, from largest to smallest. Excluding the location corresponding to the HRB from the range of candidate test error patterns can avoid performing a large number of invalid tests on obviously reliable locations; further distinguishing between UB and HUB allows HUB locations with a higher probability of error to participate in testing first, thus balancing the search range and search order.

[0030] In this embodiment and This can be achieved through pre-simulation: within the target operating signal-to-noise ratio range, two thresholds are varied, decoding performance and the number of candidate test error patterns are compared, and then a set of values ​​that balances performance and complexity is selected. For example, when the absolute value of the log-likelihood ratio of a certain bit is 11, 6, and 2, it is labeled as HRB, UB, and HUB respectively according to the thresholds in this embodiment. In addition to fixed thresholds, thresholds can also be adaptively determined based on the current signal-to-noise ratio, the quantile of the soft information distribution, or the relative order of bits in each data block to be decoded.

[0031] Step 6: Based on the encoding structure of the product code, convert the hard decision bit matrix... B The hard decision bits are organized into multiple units to be decoded, and the associated units to be decoded for each unit are determined.

[0032] Specifically, B The 31 row vectors in the code are used as 31 rows of decoding units. B The 31 column vectors in the original text are transposed and used as 31 columns of decoding units, resulting in a total of... There are 31 units to be decoded. Each unit is a 1×31-dimensional binary row vector, represented as follows: .

[0033] No. i The line of units to be decoded and the first j Each column of units to be decoded shares a hard decision bit. Therefore, the row-to-decode unit and the column-to-decode unit are identified as related units to be decoded. Hard decision bits are not shared between two different row-to-decode units, nor are hard decision bits shared between two different column-to-decode units.

[0034] Step 7: Based on the tagging information of each hard decision bit, generate a candidate test error pattern sequence only for the positions corresponding to HUB and UB in the unit to be decoded, and perform iterative hard decision decoding on each unit to be decoded.

[0035] Step 7.1: Define distance limits Its value range is .

[0036] Define the state set of the unit to be decoded .in, Indicates the first Decoding status of the units to be decoded: This indicates that the corresponding unit to be decoded may contain erroneous bits and needs to be decoded; This indicates that the corresponding unit to be decoded has been successfully decoded; This indicates that the corresponding unit to be decoded failed to decode. In this embodiment, successful decoding means that the current unit to be decoded, or the result obtained after testing according to the candidate test error pattern, satisfies the verification relationship of the corresponding encoding method. For the BCH code used in this embodiment, the verification relationship is based on the check matrix. A defined verification relationship.

[0037] Define the data before decoding and decoded data and initialize distance limits. , S If all elements in the set are 0, let... ; Step 7.2, based on B The tagging information , S and Hard-decision decoding is performed sequentially on the units to be decoded whose state is 0 according to a preset order.

[0038] Each round of decoding begins from the current... Extract the unit to be decoded For the current unit to be decoded Based on the tagging information of each bit, determine the set of highly unreliable position indices. and unreliable location index set .in, Depend on The bits marked as HUB are composed of bit position indices. Depend on The bits marked UB are composed of bit position indices.

[0039] Definition of the first i Test error pattern This is a 1×31 dimensional binary row vector. In the test error pattern, a value of 1 indicates that the position is an error to be tested, and a value of 0 indicates that the position does not belong to the current test error. Based on the confidence category and quantity of the error positions to be tested, the following set of test error patterns is generated: To use enumeration The set of all test error patterns generated by assigning a value of 1 to the position corresponding to each enumerated position index and a value of 0 to the remaining positions; that is... .

[0040] To use enumeration The set of all test error patterns generated by assigning a value of 1 to the corresponding position of any two distinct position indices in each enumeration and a value of 0 to all other positions is given; that is... .

[0041] To use enumeration The set of all test error patterns generated by assigning a value of 1 to the position corresponding to each enumerated position index and a value of 0 to the remaining positions is defined as follows: .

[0042] To use enumeration The set consists of all test error patterns generated by assigning a value of 1 to the corresponding three positions at any three different positions in the array, and assigning a value of 0 to the remaining positions; that is, .

[0043] To enumerate separately and The set consists of all test error patterns generated by assigning a value of 1 to the corresponding positions of the two enumerated position indices and a value of 0 to the remaining positions. That is... .

[0044] When the number of elements in the corresponding position index set is insufficient to generate a certain type of test error pattern, the corresponding test error pattern set is empty.

[0045] According to distance limits The above set of test error patterns is organized into the following ordered sequence of error pattern attempts: make hour, Depend on composition; make hour, Depend on , It is assembled sequentially; make hour, Depend on , and It is assembled sequentially; make hour, Depend on , and It is assembled sequentially; make , Depend on , and It is assembled sequentially; in, and In respectively , Based on search and Not included Therefore, the search ranges corresponding to different distance boundaries do not need to be continuously accumulated.

[0046] Parity check matrix using BCH(31,21,5) code For the current unit to be decoded Perform verification: like Then output directly. It then determines that the current unit to be decoded has been successfully decoded.

[0047] like Then according to The test error patterns are selected in the order of arrangement. and calculate .

[0048] If the first satisfying condition is found Test error patterns Then The decoding result is used as the current unit to be decoded, and the decoding is determined to be successful; if traversing... If no test error pattern that satisfies the check relationship is found after exhausting all test error patterns, then retain it. The result remains unchanged, and decoding is deemed a failure.

[0049] When the current unit to be decoded is successfully decoded, its decoding result is written to... And set the corresponding decoding status to 1.

[0050] If the decoding result causes a change in one or more hard decision bits of the current unit to be decoded, the state of the unit to be decoded associated with the changed hard decision bit is set to 0, so that it can participate in decoding again in subsequent processes.

[0051] When the current unit to be decoded fails to decode, its state is set to 2, and the corresponding hard decision bit remains unchanged.

[0052] Following the above method, all rows and columns of units to be decoded are traversed sequentially, and the units with a state of 0 during traversal are decoded once; after completing one round of row and column traversal, the decoded data is obtained. .

[0053] The state of the unit to be decoded associated with the changed shared bit is reset to 0 because the previous check result or decoding failure conclusion of the associated unit to be decoded was obtained based on the old bit, and it should be allowed to be decoded again after the shared bit is updated. Unaffected units to be decoded can maintain their original state, thereby avoiding the indiscriminate reprocessing of all units to be decoded.

[0054] Step 7.3: Determine whether the preset stopping conditions are met in the following order: If the state set S If all elements in the set are 1, then... As the final decoding result Output the result and exit the iteration; like and Inconsistent, and the set of states S If there exists an element with a value of 0, then let... ,Will S All elements with a value of 2 are reset to 0, and the process returns to step 7.2 to continue execution; like and Inconsistency, set of states S All elements in the array are non-zero and Then let , ,Will S All elements with a value of 2 are reset to 0, and the process returns to step 7.2 to continue execution; If the state set S All elements are non-zero and Then As the final decoding result Output the result and exit the iteration; like and If consistent, then As the final decoding result Output the result and exit the iteration.

[0055] Step 7.4: Based on the preset encoding method, extract the final decoding result. The information sequence was recovered from the middle I′ ; In this embodiment, both row and column component codes use the systematic form of BCH(31,21,5) code, with information bits located in the first 21 positions of each component codeword. Therefore, the final decoding result... The 21×21 dimensional region formed by the intersection of the first 21 rows and the first 21 columns is the recovered information bit matrix. The receiving end extracts 441 information bits from the information bit matrix and follows the information sequence in step 1. I The information bits are arranged in the same order when written into the information bit matrix, thus recovering an information sequence of length 441 bits. I′ .

[0056] Step 8: Decode the resulting message sequence I′ With transmitted information bits I By comparing the soft-information-assisted hard-decision decoding method of this embodiment with the traditional hard-decision decoding method that does not use soft information for bit confidence marking and candidate error pattern constraints, the bit error rate is calculated by counting the number of erroneous bits.

[0057] Simulation results show that when the bit error rate is At the same time, the method in this embodiment can achieve a signal-to-noise ratio gain of approximately 1.0 dB compared to the traditional hard-decision decoding method. Using the average number of candidate test error pattern checks performed per unit to be decoded as an indicator of decoding complexity, the average decoding complexity of the method in this embodiment is reduced by approximately 50%.

[0058] This embodiment also provides an electronic device. The electronic device includes a processor and a memory, in which a computer program is stored. When the computer program is executed by the processor, the electronic device performs the aforementioned soft-information-assisted general hard-decision decoding method.

[0059] This embodiment also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the aforementioned soft-information-assisted general hard-decision decoding method.

Claims

1. A general hard-decision decoding method assisted by soft information, characterized in that, This method is applied in digital communication scenarios consisting of a transmitter, a channel, and a receiver. The receiver includes a hard-decision demodulator, a soft-decision demodulator, and a general-purpose hard-decision decoder with soft-information assistance. The general-purpose hard-decision decoding method includes the following steps: Step 1: The sending end obtains the information sequence. I And use a preset encoding method to encode the information sequence I Perform channel coding to generate coded data blocks. C ; Step 2: The sending end sends data blocks. C Modulation is performed to obtain the symbol matrix to be transmitted. X ; Step 3: Symbol Matrix to be Transmitted X After being transmitted through a noisy channel to the receiving end, the received symbol sequence matrix is ​​obtained. Y ; Step 4: The receiving end uses a hard decision demodulator to... Y The process is performed to obtain the hard decision bit matrix. B ; Soft decision demodulator Y Calculations are performed to obtain the soft information matrix. Λ ; Step 5: Soft-information-assisted universal hard-decision decoder based on... Λ The log-likelihood ratio for each row and column in the middle. B The corresponding row and column bits are used to mark the credibility, resulting in... B The tagging information; the values ​​of the tagging information include: high reliability bit HRB, unreliable bit UB, and high unreliability bit HUB; Step 6: According to the encoding structure corresponding to the preset encoding method, convert the hard decision bit matrix... B The hard decision bits are organized into multiple units to be decoded, and the associated units to be decoded for each unit are determined. Step 7: Based on the marking information, generate a candidate test error pattern sequence only for the positions corresponding to the high unreliable bit HUB and unreliable bit UB in each unit to be decoded, according to the confidence category and quantity of the error positions. Based on the candidate test error pattern sequence, hard-decision decoding is performed on each unit to be decoded, and the decoding result of each unit is used to update the decoding process. B ; Hard-decision decoding is performed on the updated hard-decision bit matrix until a preset stopping condition is met, thus obtaining the final decoding result. ; Based on the preset encoding method, the final decoding result Information sequence recovered from I′ .

2. A general hard-decision decoding method with soft information assistance according to claim 1, characterized in that, Step 5 includes: Step 5.1, Definition This is the first credibility threshold. This is the second credibility threshold, and ; Step 5.2, let Representing the soft information matrix Λ The Middle Line number Log-likelihood ratio, let B The Middle Line number column bits are denoted as ; when At that time, then order The corresponding tag information is HRB; when At that time, then order The corresponding tag information is UB; when At that time, then order The corresponding tag information is HUB.

3. A general hard-decision decoding method with soft information assistance according to claim 1, characterized in that, Step 6 includes: Step 6.1: Let any unit to be decoded be 1× n A binary row vector of dimension, denoted as ,in, Indicates the unit to be decoded The Middle Hard decision bits at each position, ; Indicates the length of the unit to be decoded; Step 6.2: Based on the hard decision bits contained in each unit to be decoded, establish the association relationship between each unit to be decoded; connect the units to be decoded... Other units to be decoded that share at least one hard decision bit are identified as The associated unit to be decoded.

4. A general hard-decision decoding method with soft information assistance according to claim 1, characterized in that, Step 7 includes: Step 7.1, Definition As the distance boundary, The range of values ​​is ; Define the state set of the unit to be decoded ,in, Indicates the number of units to be decoded. Indicates the first The decoding status of each unit to be decoded. The range of values ​​is ; This indicates that the i-th unit to be decoded may contain an error bit. Indicates the first i One unit to be decoded was successfully decoded. Indicates the first i One unit to be decoded failed to be decoded; Define the data before decoding and decoded data and initialize distance limits. , S If all elements in the set are 0, let... ; Step 7.2, based on B The tagging information , S and Hard-decision decoding is performed sequentially on all units whose decoding state is 0. If decoding is successful, the state of the corresponding unit is set to 1, and the states of associated units affected by the decoding result are set to 0. If decoding fails, the state of the corresponding unit is set to 2. After decoding all units whose state is 0, the decoded data is obtained. ; Step 7.3: Determine if the preset stopping condition is met; if so, proceed. As the final decoding result output; if it does not meet the requirements, then according to ,right , S and After the update, return to step 7.2 and execute sequentially; Step 7.4: Based on the preset encoding method, extract the final decoding result. The information sequence was recovered from the middle I′ .

5. A general hard-decision decoding method with soft information assistance according to claim 4, characterized in that, Step 7.2 includes: Step 7.2.1: Read the unit to be decoded The tagging information in; Define a set of highly unreliable location indices Among them, the set of highly unreliable location indices Each element in the code is a unit to be decoded. A bit position index marked as HUB; Define an unreliable location index set Among them, the unreliable location index set Each element in the code is a unit to be decoded. A bit position index marked as UB; Step 7.2.2, Define the first i The test error pattern is 1× n A 3D binary row vector, denoted as ,in, Indicates the first i Test error pattern The Middle j Bits at each position; Highly unreliable location index set The system enumerates the indices of each position, assigning a 1 to the bit at the corresponding position index for each enumeration and setting the bits at the remaining positions to 0. The resulting set of all test error patterns is denoted as [the set of patterns]. ; Highly unreliable location index set Enumerate any two distinct position indices, assign the bit value of the corresponding position to 1, and assign the bit value of the remaining positions to 0. The set of all test error patterns generated is denoted as . ; Unreliable location index set The system enumerates the indices of each position, assigning a 1 to the bit at the corresponding position index for each enumeration and setting the bits at the remaining positions to 0. The resulting set of all test error patterns is denoted as [the set of patterns]. ; Highly unreliable location index set Enumerate any three different position indices, assign the bit value of the position corresponding to the three enumerated position indices to 1, and assign the bit value of the remaining positions to 0. The set of all test error patterns generated is denoted as . ; For each set of highly unreliable location indices and unreliable location index set Enumerate a position index, assign the bit value of the two positions corresponding to the enumerated position indices to 1, and assign the bit value of the remaining positions to 0. The set of all generated test error patterns is denoted as . ; in, Indicates the first i Test error pattern Middle in the set of highly unreliable position indices The number of positions that are assigned a value of 1; Indicates the first i Test error pattern In the unreliable location index set The number of positions that are assigned a value of 1; Indicates the first i Test error pattern The total number of positions in the middle that are assigned a value of 1; and , , , , These are used to test scenarios where one HUB location, two HUB locations, one UB location, three HUB locations, and one HUB location and one UB location both malfunction simultaneously. Step 7.2.3: Construct different distance boundaries The following is an ordered sequence of error patterns ; make The ordered sequence of error patterns corresponding to the time. Depend on composition; make The ordered sequence of error patterns corresponding to the time. Depend on , It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; make The ordered sequence of error patterns corresponding to the time Depend on , and It is assembled sequentially; Step 7.2.4, Definition This is the parity check matrix for the encoding method of the current unit to be decoded, and it is used for... Perform verification: like Satisfy the verification relationship Then directly output the decoding result. And determine if the decoding is successful; otherwise, iterate through... Each element in; If in Find satisfy Candidate error patterns Then output the decoding result. It determines whether decoding is successful; otherwise, it outputs the decoding result. The decoding was deemed to have failed.

6. A general hard-decision decoding method with soft information assistance according to claim 4, characterized in that, Step 7.3 includes: If the state set of the unit to be decoded S If all elements in the array are 1, then... Output the final decoding result and exit the iteration; If the state set of the unit to be decoded S All elements in the array are non-zero and Then Output the final decoding result and exit the iteration; like and If consistent, then Output the final decoding result and exit the iteration; like and Inconsistent set of states of units to be decoded S If there exists an element that is 0, then let Assign to and will S After resetting the element with a value of 2 to 0, return to step 7.2 to continue execution; like and Inconsistent set of states of units to be decoded S All elements in the middle are not 0 and Less than 5, let Assign to , Assign to and will S After resetting the element with a value of 2 to 0, return to step 7.2 to continue execution.

7. An electronic device comprising a processor and a memory, characterized in that, The memory stores a computer program, which, when executed by a processor, causes the electronic device to perform the method of any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When a computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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