Chase soft decoding method and device

Abstract

The present application relates to the field of communications, and discloses a Chase soft decoding method and device. The method comprises: soft demodulating the constellation point cloud and obtaining a log-likelihood ratio; obtaining a trial sequence according to the log-likelihood ratio; performing a hard decision on the constellation point cloud and obtaining a hard decision result; correcting the hard decision result using the trial sequence; hard decoding the corrected hard decision result and obtaining a candidate codeword set; comparing the hard decision result with the candidate codeword set and selecting the best candidate codeword as the decoding result. The present application can avoid the influence of the log-likelihood ratio quantization error, making the hard decision result more accurate, thereby improving the decoding performance.

Description

Technical Field

[0001] The present application relates to the field of electronic information technology, and in particular to a Chase soft decoding method and device. Background Art

[0002] In 1972, D. Chase proposed an iterative soft decoding method that can achieve performance close to maximum likelihood decoding and is applicable to various block codes with medium and short code lengths and medium error correction capabilities. It is now called the Chase algorithm. The candidate codewords of the Chase algorithm are generated around some search centers using limited distance decoding, and these search centers are codewords obtained by adding hard decision vectors to some error patterns determined based on the reliability metric of the received vector.

[0003] The main process of Chase algorithm is as follows: Figure 1 As shown:

[0004] 1. According to the log-likelihood ratio (LLR) output by the soft demodulation module, find the symbol position with a higher probability of error (i.e., the module "find the P minimum values ​​with the smallest absolute value" in the figure below).

[0005] 2. Based on the P minimum values, construct a binary trial set and obtain a trial sequence.

[0006] 3. Use each trial sequence to correct the hard decision bit sequence and input the corrected sequence into several hard decision decoders.

[0007] 4. The hard decision decoder performs decoding to obtain a set of candidate code words.

[0008] 5. Compare the candidate codeword set with the hard decision bit sequence, and select a candidate codeword as the final decoding result based on a certain optimal criterion.

[0009] The hard decision bit sequence is obtained by taking the sign bit of the LLR, which is affected by its fixed-point quantization bit width. The smaller the fixed-point quantization bit width of the LLR, the greater the error of the hard decision bit obtained. In actual chips, in order to reduce power consumption, the quantization bit width of the LLR is usually small, so the error of the hard decision bit is large.

[0010] This section is intended to provide a background or context to the embodiments of the present application as recited in the claims. The description herein is not admitted to be prior art as disclosed by virtue of its inclusion in this section. Summary of the invention

[0011] The purpose of the present application is to provide a Chase soft decoding method and device to avoid the influence of a small fixed-point quantization bit width of a log-likelihood ratio on a decision error.

[0012] The present application discloses a Chase soft decoding method, comprising:

[0013] Soft demodulate the constellation point cloud and obtain the log-likelihood ratio;

[0014] Obtaining a trial sequence according to the log-likelihood ratio;

[0015] Performing hard decision on the constellation point cloud and obtaining a hard decision result;

[0016] Using the trial sequence to modify the hard decision result;

[0017] Hard decoding the modified hard decision result to obtain a candidate codeword set; and

[0018] The hard decision result is compared with the candidate codeword set and the best candidate codeword is selected as the decoding result.

[0019] In a preferred embodiment, the step of obtaining a trial sequence according to the log-likelihood ratio further comprises:

[0020] The absolute value of the log-likelihood ratio is calculated, P absolute values ​​with the smallest absolute values ​​are selected to form a minimum value set, and the minimum value set is combined into a binary trial sequence.

[0021] In a preferred example, the step of performing hard decision on the constellation point cloud and obtaining a hard decision result further includes:

[0022] The constellation points in the constellation point cloud are respectively compared with predefined decision thresholds to obtain hard decision results.

[0023] In a preferred example, when PAM4 modulation is adopted, the predefined decision thresholds include -2, 0, and 2, and the following formula is used to perform hard decision on the constellation point;

[0024]

[0025] Wherein, r represents a constellation point, and hdBit represents a hard decision bit obtained according to r.

[0026] In a preferred example, when QAM16 modulation is adopted, the predefined decision thresholds include -2, 0, and 2, and the following formula is adopted to perform hard decision on the constellation point;

[0027]

[0028] hdBit=[hdBit I ,hdBit Q ]

[0029] Among them, rI and r Q Respectively represent the real and imaginary parts of the constellation point, hdBit I and hdBit Q Respectively according to r I and r Q The hard decision bits obtained by the decision.

[0030] In a preferred example, the step of correcting the hard decision result using the trial sequence further includes:

[0031] An exclusive OR operation is performed on the trial sequence and the hard decision result.

[0032] In a preferred embodiment, the step of comparing the hard decision result with the candidate codeword set and selecting the best candidate codeword as the decoding result further includes:

[0033] Comparing the hard decision result with the candidate codeword set and finding the position where each candidate codeword in the candidate codeword set is different from the hard decision result; and

[0034] The log-likelihood ratios corresponding to the positions where the candidate codeword and the hard decision result are different are added, and the candidate codeword with the smallest added value is selected as the best candidate codeword, and the best candidate codeword is used as the decoding result.

[0035] The present application also discloses a Chase soft decoding device, comprising:

[0036] A trial sequence generation module is used to obtain a trial sequence according to a log-likelihood ratio obtained by soft demodulation of the constellation point cloud;

[0037] an adder, configured to modify a hard decision result obtained by hard decision making based on the constellation point cloud using the trial sequence;

[0038] a hard decoder, configured to hard decode the modified hard decision result and obtain a candidate codeword set; and

[0039] The best candidate codeword selection module is used to compare the hard decision result with the candidate codeword set and select the best candidate codeword as the decoding result.

[0040] In a preferred embodiment, the trial sequence generation module further comprises:

[0041] An absolute value calculation module, used for calculating the absolute value of the log-likelihood ratio;

[0042] A minimum value set selection module, used to select P absolute values ​​with the smallest absolute values ​​to form a minimum value set; and

[0043] The combining module is used to combine the minimum value sets into a binary trial sequence.

[0044] In a preferred example, a hard decision module is used to perform hard decision on the constellation point cloud, and the hard decision module includes: first to third comparators, first and second AND gates, and first to fourth multiplexers;

[0045] The first to third comparators receive the constellation point cloud respectively and compare the constellation points in the constellation point cloud with respective decision thresholds, the output end of the first comparator is coupled to the first multiplexer and coupled to one input end of the first AND gate through a NOT gate, the output end of the second comparator is coupled to the other input end of the first AND gate and coupled to one input end of the second AND gate through a NOT gate, the output end of the third comparator is coupled to the other input end of the second AND gate and coupled to the fourth multiplexer through a NOT gate;

[0046] The output end of the first AND gate is coupled to the second multiplexer, and the output end of the second AND gate is coupled to the third multiplexer;

[0047] One input terminal of the first multiplexer is coupled to 00, and the other input terminal is coupled to the output terminal of the second multiplexer; one input terminal of the second multiplexer is coupled to 01, and the other input terminal is coupled to the output terminal of the third multiplexer; one input terminal of the third multiplexer is coupled to 11, and the other input terminal is coupled to the output terminal of the fourth multiplexer; one input terminal of the fourth multiplexer is coupled to 10

[0048] The present application also discloses a computer-readable storage medium in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, the steps in the method described above are implemented.

[0049] Compared with the existing solutions, the implementation method of the present application incorporates soft demodulation into the category of Chase soft decoder, and the hard decision bit sequence is no longer obtained by the sign bit of LLR, but is directly obtained by hard decision from the constellation point cloud. This avoids the influence of LLR quantization error, makes the hard decision bit sequence more accurate, and thus improves the performance of the decoder.

[0050] The specification of the present application records a large number of technical features, which are distributed in various technical solutions. If all possible combinations of technical features of the present application (i.e., technical solutions) are to be listed, the specification will be too long. In order to avoid this problem, the various technical features disclosed in the above-mentioned invention content of the present application, the various technical features disclosed in the various embodiments and examples below, and the various technical features disclosed in the accompanying drawings can be freely combined with each other to form various new technical solutions (these technical solutions should all be regarded as having been recorded in this specification), unless the combination of such technical features is technically infeasible. For example, in one example, feature A+B+C is disclosed, and in another example, feature A+B+D+E is disclosed, and features C and D are equivalent technical means that play the same role. Technically, only one can be used, and it is impossible to use them at the same time. Feature E can be combined with feature C technically. Then, the solution of A+B+C+D should not be regarded as having been recorded because it is technically infeasible, and the solution of A+B+C+E should be regarded as having been recorded. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the structure of a Chase soft decoding device according to the second embodiment of the present application.

[0052] Figure 2 It is a flowchart of the Chase soft decoding method according to the first embodiment of the present application.

[0053] Figure 3 This is a schematic diagram of hard decision under PAM4 modulation in an embodiment of the present application.

[0054] Figure 4 It is a structural diagram of a hard decision module according to an embodiment of the present application.

[0055] Figure 5 This is a schematic diagram of hard decision under QAM16 modulation in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In the following description, many technical details are provided to help readers better understand the present application. However, those skilled in the art can understand that the technical solution claimed in the present application can be implemented even without these technical details and various changes and modifications based on the following embodiments.

[0057] In order to make the objectives, technical solutions and advantages of the present application more clear, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0058] An embodiment of the present application relates to a Chase soft decoding device, whose structure is as follows: Figure 1As shown, the Chase soft decoding device 200 includes: a trial sequence generation module 201, an adder 205, a hard decoder 206, and a best candidate codeword selection module 207. The trial sequence generation module 201 is used to obtain a trial sequence according to the log likelihood ratio (LLR) obtained by soft demodulation of the constellation point cloud. The soft demodulation module 101 is used to soft-demodulate the constellation point cloud. The constellation point cloud includes many constellation points. The adder 205 is used to use the trial sequence to correct the hard decision result obtained by hard decision based on the constellation point cloud. The hard decision module 102 is used to make a hard decision on the constellation point cloud. The hard decoder 206 is used to hard-decode the corrected hard decision result and obtain a candidate codeword set. It should be understood that the Chase soft decoding device includes a plurality of hard decoders. The best candidate codeword selection module 207 is used to compare the hard decision result with the candidate codeword set and select the best candidate codeword as the decoding result.

[0059] In one embodiment, the trial sequence generation module 201 further includes: an absolute value calculation module 202, a minimum value set selection module 203, and a combination module 204. The absolute value calculation module 202 is used to calculate the absolute value of the log-likelihood ratio. The minimum value set selection module 203 is used to select P absolute values ​​with the smallest absolute value to form a minimum value set. The combination module 204 is used to combine the minimum value set into a binary trial sequence.

[0060] Another embodiment of the present application relates to a Chase soft decoding method, the process of which is as follows: Figure 2 As shown, the method comprises the following steps:

[0061] Step 301: soft-demodulate the constellation point cloud and obtain a log-likelihood ratio (LLR).

[0062] Step 302: Obtain a trial sequence according to the log-likelihood ratio.

[0063] In one embodiment, the step of obtaining a trial sequence according to the log-likelihood ratio further includes: obtaining the absolute value of the log-likelihood ratio, selecting P absolute values ​​with the smallest absolute value to form a minimum value set, and combining the minimum value set into a binary trial sequence.

[0064] Step 303: perform hard decision on the constellation point cloud and obtain a hard decision result.

[0065] In one embodiment, the step of performing hard decision on the constellation point cloud and obtaining a hard decision result further includes: comparing the constellation points in the constellation point cloud with predefined decision thresholds to obtain hard decision results.

[0066] It should be noted that PAM4 and QAM16 are only used as examples. In fact, the Chase soft decoding method is applicable to any modulation mode, including but not limited to one-dimensional modulation (NRZ, PAM4, PAM8, etc.), two-dimensional modulation (QPSK, QAM8, QAM16, QAM32, etc.).

[0067] Step 304: Use a trial sequence to correct the hard decision result.

[0068] In one embodiment, the step of using a probe sequence to correct the hard decision result further includes: performing an XOR operation on the probe sequence and the hard decision result.

[0069] Step 305: hard-decode the corrected hard decision result and obtain a candidate codeword set.

[0070] Step 306: compare the hard decision result with the candidate codeword set and select the best candidate codeword as the decoding result.

[0071] In one embodiment, the step of comparing the hard decision result with the candidate codeword set and selecting the best candidate codeword as the decoding result further includes:

[0072] Comparing the hard decision result with the candidate codeword set and finding the position where each candidate codeword in the candidate codeword set is different from the hard decision result; and

[0073] The log-likelihood ratios corresponding to the positions where the candidate codeword and the hard decision result are different are added, and the candidate codeword with the smallest added value is selected as the best candidate codeword, and the best candidate codeword is used as the decoding result.

[0074] In order to better understand the technical solution of the present application, a specific example is provided below for illustration. The details listed in the example are mainly for ease of understanding and are not intended to limit the scope of protection of the present application.

[0075] refer to Figure 1 As shown, firstly, according to the log-likelihood ratio output by the soft demodulation module, the symbol position with a greater possibility of error is found. According to the P minimum values, a binary trial set is constructed to obtain a trial sequence.

[0076] The hard decision module performs hard decisions on the constellation point cloud and obtains a hard decision bit sequence. Among them, the rule for the hard decision module to make hard decisions on the received constellation points that are interfered by the channel and noise is: find the standard constellation point closest to the received constellation point, and then judge it as the binary bit corresponding to the constellation point. For example, for PAM4 modulation, at the transmitter, 2 bits will be mapped to one of the four constellation points, and their amplitude values ​​are ±1 and ±3 respectively. At the receiving end, the constellation points interfered by noise will deviate from the original constellation points, and find the original constellation point closest to the received constellation point. Therefore, the decision thresholds can be defined as -2, 0, and 2, respectively, such as Figure 3 As shown, Figure 3 The dots in the middle represent constellation points. The hard decision equation is shown in the following formula (1).

[0077]

[0078] Wherein, r represents a constellation point, and hdBit represents a hard decision bit obtained according to r.

[0079] Figure 4 The hard decision module 102 includes a first comparator 103, a second comparator 104, a third comparator 105, a first AND gate 106, a second AND gate 107, a first multiplexer 108, a second multiplexer 109, a third multiplexer 110, and a fourth multiplexer 111. The inputs of the first to third comparators receive the constellation point cloud output by the previous module respectively, the output of the first comparator is coupled to the first multiplexer 107 and coupled to one input end of the first AND gate 106 through a NOT gate, the output of the second comparator 104 is coupled to the other input end of the first AND gate 106 and coupled to one input end of the second AND gate 107 through a NOT gate, the output of the third comparator 105 is coupled to the other input end of the second AND gate 107 and coupled to the fourth multiplexer 111 through a NOT gate. The output of the first AND gate 106 is coupled to the second multiplexer 109, and the output of the second AND gate 107 is coupled to the third multiplexer 110. One input terminal of the first multiplexer 108 is coupled to 00, and the other input terminal is coupled to the output terminal of the second multiplexer 109. One input terminal of the second multiplexer 109 is coupled to 01, and the other input terminal is coupled to the output terminal of the third multiplexer 110. One input terminal of the third multiplexer 110 is coupled to 11, and the other input terminal is coupled to the output terminal of the fourth multiplexer 111. One input terminal of the fourth multiplexer 111 is coupled to 10, and the other input terminal is coupled to the floating value x.

[0080] The first comparator 103 is used to compare the constellation point with the decision threshold -2, the second comparator 104 is used to compare the constellation point with the decision threshold 0, and the third comparator 105 is used to compare the constellation point with the decision threshold 2. When the constellation point output by the previous module is less than -2, the first comparator 103 outputs 1, the second comparator 104 and the third comparator 105 output 0, the first AND gate 106 and the second AND gate 107 output 0, and the first multiplexer 108 selects 00 to output to the subsequent module. When the constellation point is greater than or equal to -2 and less than 0, the second comparator 103 outputs 1, the first comparator 103 and the third comparator 105 output 0, the first AND gate 106 outputs 1, the second AND gate 107 outputs 0, and the second multiplexer 109 selects 01 to output and outputs 01 to the subsequent module through the first multiplexer (for example, Figure 1 Adder in, optimal candidate codeword selection module). When the constellation point is greater than or equal to 0 and less than 2, the third comparator 103 outputs 1, the first comparator 103 and the third comparator 105 output 0, the first AND gate 106 outputs 0, the second AND gate 107 outputs 1, the third multiplexer 110 selects 11 to output and sequentially passes through the second multiplexer 109 and the first multiplexer 108 to output to the subsequent module. When the constellation point is greater than or equal to 2, the first comparator 103, the second comparator 104 and the third comparator 105 output 0, the first AND gate 106 and the second AND gate 107 output 0, the fourth multiplexer 111 selects 10 to output and sequentially passes through the third multiplexer 110, the second multiplexer 109 and the first multiplexer 108 to output to the subsequent module.

[0081] In another embodiment, for two-dimensional modulation, such as QAM16, it is equivalent to performing PAM4 modulation in two dimensions, and the decision thresholds -2, 0, and 2 can be defined in the two dimensions respectively. Figure 4 As shown, Figure 5 The dots in the middle represent constellation points. The hard decision equation is shown in the following formula (2).

[0082]

[0083] hdBit=[hdBit I ,hdBit Q ]

[0084] Among them, r I and r Q Respectively represent the real and imaginary parts of the constellation point, hdBit I and hdBit Q Respectively according to r I and r QThe hard decision bits obtained by the decision. It can be seen that by directly making hard decisions through constellation points, only a certain number of comparators need to be added, and the increase in resources is negligible.

[0085] It should be noted that when QAM16 modulation is used, two Figure 4 The hard decision modules shown in the figure are respectively I and r Q Make a judgment. The principle of the judgment is as described above and will not be repeated here.

[0086] Each trial sequence is used to modify the hard decision bit sequence, and the modified sequence is input to a number of hard decision decoders.

[0087] Figure 1 The adder in is a vector adder, where the length of the vector is the code length, and the addition of each element in the vector is based on the GF(2) field, that is, an XOR operation. The principle of the XOR operation is explained using y=a+b as an example, as shown in Table 1 below.

[0088] a b y 0 0 0 0 1 1 1 0 1 1 1 0

[0089] Table 1 XOR operation principle

[0090] One of the inputs of the vector adder is the hard decision module output hdBit, and the other input is the probe sequence. The length of the probe sequence is the code length, most of which are 0, with only ≤P 1s, and the 1 position represents the position that needs to be flipped.

[0091] The last module "best codeword selection" is to select a candidate codeword as the final decoding result according to a certain optimal criterion. The most commonly used one is the minimum Euclidean distance algorithm, that is, find the position where the hard decision hdBit is different from the candidate codeword, add up the absolute values ​​of the LLRs corresponding to these positions, as the Euclidean distance between the candidate codeword and the input codeword, and find the candidate codeword corresponding to the smallest Euclidean distance as the decoding output. For example, as shown in Table 2 below, taking two candidate codewords in the candidate codeword set as an example, an example of candidate codeword selection is shown. The different positions of candidate codeword 1 and the hard decision bit hdBit are 2 and 7, and the absolute values ​​of the log-likelihood ratios of the corresponding positions abs(LLR) add up to 7. The different positions of candidate codeword 2 and the hard decision bit hdBit are 2 and 8, and the absolute values ​​of the log-likelihood ratios of the corresponding positions abs(LLR) add up to 8, so candidate codeword 1 is selected as the best candidate codeword output.

[0092]

[0093] Table 2 Example of selection of candidate codewords

[0094] Based on a Hamming code with an overhead of 7.6%, the signal-to-noise ratio (SNR) and bit error rate simulation results of the first iteration are shown in the following Table 3. It can be seen that under all signal-to-noise ratio conditions, the bit error rate of the present invention is lower.

[0095]

[0096] Table 3 Bit error rate under different signal-to-noise ratios

[0097] In the traditional scheme, the log-likelihood ratio LLR after soft demodulation is used to obtain the trial sequence and the hard decision bit sequence respectively, and then the trial sequence is used to correct the hard decision bit sequence. Compared with the existing scheme, the implementation method of the present application incorporates soft demodulation into the category of Chase soft decoder, and the hard decision bit sequence is no longer obtained by the sign bit of LLR, but is directly obtained by hard decision from the constellation point cloud. In this way, the influence of LLR quantization error is avoided, making the hard decision bit sequence more accurate, thereby improving the performance of the decoder.

[0098] It should be noted that those skilled in the art should understand that the implementation functions of each module shown in the implementation of the above-mentioned Chase soft decoding device can be understood with reference to the relevant description of the above-mentioned Chase soft decoding method. The functions of each module shown in the implementation of the above-mentioned Chase soft decoding device can be implemented by a program (executable instruction) running on a processor, or can be implemented by a specific logic circuit. If the above-mentioned Chase soft decoding device in the embodiment of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM, Read Only Memory), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0099] Accordingly, the present application also provides a computer-readable storage medium in which computer executable instructions are stored, and when the computer executable instructions are executed by the processor, the various method embodiments of the present application are implemented. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be a computer-readable instruction, a data structure, a module of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable storage media do not include temporary computer-readable media (transitory media), such as modulated data signals and carriers.

[0100] It should be noted that in the application documents of this patent, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one" do not exclude the existence of other identical elements in the process, method, article or device including the elements. In the application documents of this patent, if it is mentioned that an action is performed according to an element, it means that the action is performed at least according to the element, which includes two situations: performing the action only according to the element, and performing the action according to the element and other elements. Expressions such as multiple, multiple, and multiple include 2, 2 times, 2 kinds, and more than 2, more than 2 times, and more than 2 kinds.

[0101] All documents mentioned in this specification are considered to be included in the disclosure of this application as a whole, so that they can be used as a basis for modification when necessary. In addition, it should be understood that the above is only a preferred embodiment of this specification and is not intended to limit the scope of protection of this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of this specification should be included in the scope of protection of one or more embodiments of this specification.

[0102] In some cases, the actions or steps described in the claims may be performed in a different order than in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A Chase soft decoding method, characterized in that: include: Soft demodulate the constellation point cloud and obtain the log-likelihood ratio; Obtaining a trial sequence according to the log-likelihood ratio; Performing hard decision on the constellation point cloud and obtaining a hard decision result; Using the trial sequence to modify the hard decision result; Hard decoding the modified hard decision result to obtain a candidate codeword set; Comparing the hard decision result with the candidate codeword set and selecting the best candidate codeword as the decoding result; Compare the hard decision result with the candidate codeword set and find out the position where each candidate codeword in the candidate codeword set is different from the hard decision result; as well as The log-likelihood ratios corresponding to the positions where the candidate codeword and the hard decision result are different are added, and the candidate codeword with the smallest added value is selected as the best candidate codeword, and the best candidate codeword is used as the decoding result.

2. The Chase soft decoding method according to claim 1, characterized in that: The step of obtaining a trial sequence according to the log-likelihood ratio further comprises: The absolute value of the log-likelihood ratio is calculated, P absolute values ​​with the smallest absolute values ​​are selected to form a minimum value set, and the minimum value set is combined into a binary trial sequence.

3. The Chase soft decoding method according to claim 1, characterized in that: The step of performing hard decision on the constellation point cloud and obtaining a hard decision result further includes: The constellation points in the constellation point cloud are respectively compared with predefined decision thresholds to obtain hard decision results.

4. The Chase soft decoding method according to claim 3, characterized in that: When PAM4 modulation is adopted, the predefined decision thresholds include -2, 0, and 2, and the following formula is adopted to perform hard decision on the constellation point; Wherein, r represents a constellation point, and hdBit represents a hard decision bit obtained according to r; When QAM16 modulation is adopted, the predefined decision thresholds include -2, 0, and 2, and the following formula is adopted to perform hard decision on the constellation point; Among them, r I and r Q Respectively represent the real and imaginary parts of the constellation point, hdBit I and hdBit Q Respectively according to r I and r Q The hard decision bits obtained by the decision.

5. The Chase soft decoding method according to claim 1, characterized in that: The step of using the trial sequence to correct the hard decision result further includes: An exclusive OR operation is performed on the trial sequence and the hard decision result.

6. A Chase soft decoding device, characterized in that: include: A trial sequence generation module is used to obtain a trial sequence according to a log-likelihood ratio obtained by soft demodulation of the constellation point cloud; an adder, configured to modify a hard decision result obtained by hard decision making based on the constellation point cloud using the trial sequence; A hard decoder, used for hard decoding the modified hard decision result and obtaining a candidate codeword set; as well as The best candidate codeword selection module is used to compare the hard decision result with the candidate codeword set and find out the position where each candidate codeword in the candidate codeword set is different from the hard decision result, add the log likelihood ratios corresponding to the positions where the candidate codeword is different from the hard decision result and select the candidate codeword with the smallest added value as the best candidate codeword, and use the best candidate codeword as the decoding result.

7. The Chase soft decoding device according to claim 6, characterized in that: The trial sequence generation module further includes: An absolute value calculation module, used for calculating the absolute value of the log-likelihood ratio; A minimum value set selection module, used to select P absolute values ​​with the smallest absolute values ​​to form a minimum value set; and The combining module is used to combine the minimum value sets into a binary trial sequence.

8. The Chase soft decoding device according to claim 6, characterized in that: A hard decision module is used to perform hard decision on the constellation point cloud, wherein the hard decision module includes: first to third comparators, first and second AND gates, and first to fourth multiplexers; The first to third comparators receive the constellation point cloud respectively and compare the constellation points in the constellation point cloud with respective decision thresholds, the output end of the first comparator is coupled to the first multiplexer and coupled to one input end of the first AND gate through a NOT gate, the output end of the second comparator is coupled to the other input end of the first AND gate and coupled to one input end of the second AND gate through a NOT gate, the output end of the third comparator is coupled to the other input end of the second AND gate and coupled to the fourth multiplexer through a NOT gate; The output end of the first AND gate is coupled to the second multiplexer, and the output end of the second AND gate is coupled to the third multiplexer; One input terminal of the first multiplexer is coupled to 00, and the other input terminal is coupled to the output terminal of the second multiplexer; one input terminal of the second multiplexer is coupled to 01, and the other input terminal is coupled to the output terminal of the third multiplexer; one input terminal of the third multiplexer is coupled to 11, and the other input terminal is coupled to the output terminal of the fourth multiplexer; one input terminal of the fourth multiplexer is coupled to 10.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, the steps in the method according to any one of claims 1 to 5 are implemented.

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