A coding parameter identification method, device, apparatus and storage medium

Abstract

The application discloses a kind of coding parameter identification method, device, equipment and storage medium.Therein, the method includes: a set of coding parameters is taken from pre-set closed set, as target coding parameter;Wherein, the closed set is formed by several sets of coding parameters corresponding to the coding type of receiving code word sequence;The receiving code word sequence is decoded based on the target coding parameter, and decoding result is obtained;The decoding result is encoded, and self-encoding code word sequence is obtained;If the self-encoding code word sequence matches the receiving code word sequence, the target coding parameter is used as the coding parameter of the receiving code word sequence;If they do not match, the next set of coding parameters is taken from the closed set, as target coding parameter, and the operation of decoding the receiving code word sequence based on the target coding parameter is returned.It can be simple in non-cooperative communication environment by executing this technical solution, and coding parameter can be identified simply and quickly.

Description

Technical Field

[0001] This invention relates to the field of blind identification technology, and in particular to a method, apparatus, device and storage medium for identifying encoded parameters. Background Technology

[0002] Low-density parity-check (LDPC) codes are block error-correcting codes with sparse parity-check matrices, applicable to almost all channels, and have therefore become a research hotspot in the coding community in recent years. Their performance approaches the Shannon limit, and they are simple to describe and implement, easy to theoretically analyze and study, simple to decode, and can be parallelized, making them suitable for hardware implementation.

[0003] In cooperative communication environments, the receiver knows the frame length N, code rate R, and parity check matrix H of the received LDPC encoded codeword sequence, making decoding easy. However, in non-cooperative communication environments, the receiver lacks knowledge of the LDPC encoding parameters, making decoding difficult. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for identifying encoded parameters, which enables simple and rapid identification of encoded parameters and allows for blind identification even in harsh communication environments, thereby improving work efficiency.

[0005] In a first aspect, embodiments of this application provide a method for identifying encoding parameters, the method comprising:

[0006] A set of encoding parameters is taken from a preset closed set as the target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence;

[0007] The received codeword sequence is decoded based on the target encoding parameters to obtain the decoding result;

[0008] The decoding result is then encoded to obtain a self-encoded codeword sequence;

[0009] If the self-encoded codeword sequence matches the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence;

[0010] If the self-encoded codeword sequence does not match the received codeword sequence, the next set of encoding parameters is taken from the closed set as the target encoding parameters, and the operation of decoding the received codeword sequence based on the target encoding parameters is returned.

[0011] Secondly, embodiments of this application provide a device for identifying encoded parameters, the device comprising:

[0012] A selection module is used to extract a set of encoding parameters from a preset closed set as target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence;

[0013] The decoding module is used to decode the received codeword sequence based on the target encoding parameters to obtain a decoding result;

[0014] The autoencoder module is used to encode the decoding result to obtain an autoencoder codeword sequence;

[0015] The determining module is used to, if the self-encoded codeword sequence matches the received codeword sequence, use the target encoding parameter as the encoding parameter of the received codeword sequence;

[0016] The return module is used to, if the self-encoded codeword sequence does not match the received codeword sequence, extract the next set of encoding parameters from the closed set as the target encoding parameters, and return the operation of decoding the received codeword sequence based on the target encoding parameters.

[0017] Thirdly, embodiments of this application provide an electronic device, the electronic device comprising:

[0018] At least one processor; and

[0019] A memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the encoded parameter identification method according to any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the encoded parameter identification method according to any embodiment of the present invention.

[0022] The technical solution of this invention provides a new method for identifying encoding parameters. This method can decode and re-encode the received codeword sequence based on the encoding parameters extracted from a preset closed set as the target encoding parameters. Then, it determines whether the encoding parameters of the received codeword sequence are the target encoding parameters based on the matching results of the self-encoded codeword sequence and the received codeword sequence. This achieves the effect of blind identification and blind decoding in non-cooperative communication environments or when the receiving end lacks knowledge of the encoding parameters of the received codeword sequence, greatly reducing the difficulty of encoding parameter identification.

[0023] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of an encoding parameter identification method provided in Embodiment 1 of the present invention;

[0026] Figure 2 This is a flowchart of a coding parameter identification method applicable to Embodiment 2 of the present invention;

[0027] Figure 3A This is a flowchart of an encoding parameter identification method provided in Embodiment 3 of the present invention;

[0028] Figure 3B This is a schematic diagram of a specific application scenario obtained by the method provided in Embodiment 3 of the present invention;

[0029] Figure 3C This is a schematic diagram of a specific application scenario obtained by the method provided in Embodiment 3 of the present invention;

[0030] Figure 4 This is a schematic diagram of the structure of an encoding parameter identification device provided in Embodiment 4 of the present invention;

[0031] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] Example 1

[0035] Figure 1 The flowchart of an encoding parameter identification method provided in Embodiment 1 of the present invention is applicable to blind identification of encoding parameters in a non-cooperative communication environment. The method can be executed by the encoding parameter identification device provided in this embodiment, which can be implemented in hardware and / or software and can be configured in an electronic device that executes the method.

[0036] See Figure 1 The method in this embodiment includes, but is not limited to, the following steps:

[0037] S110. Take a set of encoding parameters from the preset closed set as the target encoding parameters;

[0038] The closed set is formed by several sets of coding parameters corresponding to the coding type of the received codeword sequence.

[0039] Among them, there are two or more different sets of encoding parameters in the preset closed set;

[0040] The encoding type of the encoding parameters is the same as the encoding type of the received codeword sequence;

[0041] In this embodiment of the invention, a preset closed set can be constructed before S110. Optionally, the encoding type of the received codeword sequence can be LDPC encoding, BCH encoding, or other encoding types. In this embodiment of the invention, LDPC encoding is selected as the preferred encoding type. LDPC encoding has a better signal-to-noise ratio boundary, and this method can be applied to identification even in harsh environments.

[0042] Specifically, all possible encoding parameters corresponding to the encoding type of the received codeword sequence form a closed set. For example, if the received codeword sequence is LDPC encoded, then the possible encoding parameters may include 20 groups.

[0043] In an embodiment of the present invention, optionally, after forming a closed set, encoding parameters can be selected sequentially from the closed set as target encoding parameters, thereby performing decoding based on the target encoding parameters and then making a judgment.

[0044] S120. Decode the received codeword sequence based on the target encoding parameters to obtain the decoding result.

[0045] In this embodiment of the invention, different encoding parameters correspond to different decoding methods. Decoding based on different encoding parameters yields different decoding results. The encoding parameters include N and K, where N is the frame length of the received codeword sequence and K is the information length. Therefore, in this embodiment, a decoding and re-encoding method based on the target encoding parameters is selected and compared with the received codeword sequence to determine whether the target encoding parameters are correct.

[0046] For example, if the received codeword sequence is X of length N, a set of encoding parameters from a closed set C is selected, and the received codeword sequence X is decoded based on these encoding parameters to obtain a hypothetical sequence U of length K. Here, U is the decoding result.

[0047] S130. Encode the decoding result to obtain the self-encoded codeword sequence.

[0048] In this embodiment of the invention, the decoding result is encoded using a fixed function to obtain a self-encoded codeword sequence, which is then matched with the received codeword sequence. The self-encoded codeword sequence and the received codeword sequence may differ, and the process of decoding and then encoding the received codeword sequence is not reversible. Therefore, by matching the self-encoded codeword sequence obtained in this way with the received codeword sequence, it is determined whether the selected target encoding parameter is the encoding parameter of the received codeword sequence.

[0049] Referring to the above, the decoding result U can be encoded to obtain a self-encoded codeword sequence X2 of length N.

[0050] S140. Determine whether the self-encoded codeword sequence matches the received codeword sequence.

[0051] In this embodiment of the invention, determining whether the self-encoded codeword sequence matches the received codeword sequence can specifically involve determining whether the parity bit portion of the self-encoded codeword sequence matches the portion of the received codeword. Specifically, it can be determined whether the proportion of differences between the parity bit portions of the self-encoded codeword sequence and the received codeword is less than a decision threshold. For example, the parity bit portions of the received codeword sequence X and the self-encoded codeword sequence X2 can be compared to see if they match.

[0052] S150. Use the target encoding parameters as the encoding parameters for the received codeword sequence.

[0053] In this embodiment of the invention, if the self-encoded codeword sequence matches the received codeword sequence, then the target encoding parameter is precisely the encoding parameter of the received codeword sequence, and therefore the target encoding parameter is used as the encoding parameter of the received codeword sequence.

[0054] S160. Take the next set of encoding parameters from the closed set as the target encoding parameters.

[0055] In this embodiment of the invention, if the self-encoded codeword sequence does not match the received codeword sequence, the next set of encoding parameters is taken from the closed set as the target encoding parameters, and the process returns to S120, until the self-encoded codeword sequence matches the received codeword sequence. The next set of encoding parameters is a different set of encoding parameters than those selected in the above steps.

[0056] In this embodiment of the invention, the technical solution provided may further include: if the encoding parameters in the preset closed set are traversed and neither the self-encoded codeword sequence nor the received codeword sequence match, then the recognition is determined to have failed. Optionally, after recognition failure, the traversal can be repeated for recognition, or other methods can be used for recognition.

[0057] The technical solution provided in this embodiment offers a novel method for identifying encoding parameters. This method can decode and re-encode the received codeword sequence based on the encoding parameters extracted from a preset closed set as the target encoding parameters. Then, it determines whether the encoding parameters of the received codeword sequence are the target encoding parameters based on the matching results of the self-encoded codeword sequence and the received codeword sequence. This achieves the effect of blind identification and blind decoding in non-cooperative communication environments or when the receiving end lacks knowledge of the encoding parameters of the received codeword sequence, greatly reducing the difficulty of encoding parameter identification.

[0058] Example 2

[0059] Figure 2 This is a flowchart of an encoding parameter identification method provided in Embodiment 2 of the present invention. This embodiment is based on Embodiment 1 above and specifically describes the matching of the self-encoded codeword sequence and the received codeword sequence. The specific content of steps S210 to S240 is largely the same as steps S110 to S140 in Embodiment 1, therefore, it will not be described again in this embodiment. Figure 2 As shown, the method includes: Figure 2 As shown, the technical solution provided by the embodiments of the present invention includes:

[0060] like Figure 2 As shown, the technical solution provided by the embodiments of the present invention includes:

[0061] S210: Take a set of encoding parameters from the preset closed set as the target encoding parameters;

[0062] The closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence;

[0063] S220: Decode the received codeword sequence based on the target encoding parameters to obtain the decoding result;

[0064] S230: Encode the decoding result to obtain a self-encoded codeword sequence;

[0065] S240: Determine whether the self-encoded codeword sequence matches the check bit portion of the received codeword sequence.

[0066] In this embodiment of the invention, the check bit portion is the self-encoded codeword that needs to be compared with the last (NK) bits of the received codeword sequence.

[0067] If yes, execute S250; otherwise, execute S260.

[0068] S250: Use the target encoding parameters as the encoding parameters of the received codeword sequence.

[0069] In an embodiment of the present invention, optionally, the step of using the target encoding parameter as the encoding parameter of the received codeword sequence if the self-encoded codeword sequence matches the check bit portion of the received codeword sequence includes: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is less than a decision threshold, the target encoding parameter is used as the encoding parameter of the received codeword sequence; wherein, M = NK, where N is the frame length of the received codeword sequence, K is the information length, and the last M bits of the received codeword sequence are the check bit portion of the received codeword sequence.

[0070] In this embodiment of the invention, the decision threshold can be set as needed. Optionally, if the last M bits of the self-encoded sequence are the same as the last M bits of the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence.

[0071] S260: Take the next set of encoding parameters from the closed set as the target encoding parameters, and return to S220.

[0072] In an embodiment of the invention, optionally, if the check bit portion of the self-encoded codeword sequence does not match the received codeword sequence, the next set of encoding parameters is extracted from the closed set as the target encoding parameter. This includes: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is greater than a decision threshold, the next set of encoding parameters is extracted from the closed set as the target encoding parameter. Wherein, if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is greater than the decision threshold, it indicates that the target encoding parameter used during the decoding and encoding process of the received codeword sequence is inaccurate, resulting in a significant difference between the self-encoded codeword sequence and the received codeword sequence. Therefore, it is necessary to extract the next set of encoding parameters from the closed set as the target encoding parameter, and return to S220 until the self-encoded codeword sequence matches the received codeword sequence.

[0073] Therefore, by matching the last M bits of the received codeword sequence and the self-encoded codeword sequence, the correct target encoding parameters can be obtained, which can quickly identify the encoding parameters and improve the recognition efficiency.

[0074] In this embodiment of the invention, optionally, the technical solution provided by this embodiment may further include: querying a check matrix based on the encoding parameters of the received codeword sequence, and verifying the decoding result based on the check matrix. Specifically, after obtaining the encoding parameters of the received codeword sequence, the check matrix corresponding to the encoding parameters can be queried from existing data to verify the decoding result.

[0075] In related technologies, existing techniques utilize Gaussian elimination of error-free codewords to obtain a non-sparse parity-check matrix, which is then sparsified to achieve LDPC encoding recognition. The core idea of ​​matrix sparsification is as follows: During one iteration, the non-sparse parity-check matrix H is fixed. d The algorithm iterates through all other rows, taking the sum of the modulo of the fixed row and the other traversed row, and then replacing the fixed row with the result that has the smallest Hamming weight. This process is repeated until no more row swaps are performed in a given iteration, at which point the iteration ends. The resulting sparse parity-check matrix H is then obtained. s The computational complexity of this algorithm is lR. 2 N, where l is the number of iterations, R = NK, N is the frame length, and K is the information length. The above method has a large computational load, low real-time performance, and a relatively complex process. In addition, it requires that the received codewords be completely error-free, which greatly narrows the application scope of the existing technology.

[0076] In related technologies, an iterative filtering algorithm is used to filter out effective check vectors for LDPC encoding, thereby achieving sparsity of the LDPC encoding check matrix. Specifically, the algorithm first constructs an error-containing matrix based on the intercepted data, and obtains its dual vector through elimination operations. Then, it uses check vector judgment criteria to filter out effective check vectors for the LDPC code from the dual vector. Next, it identifies and removes error-containing code groups in the intercepted data, iterating the above operations to increase the proportion of error-free code groups in the resulting data, until the original problem is reduced to a simpler scenario with error-free code groups. Finally, an asymptotic transformation algorithm is used to achieve sparsity of the LDPC code check matrix. Although this method allows for errors in the received encoded codewords, the error rate is approximately 10. -4 At the scale of [unclear], it is no longer possible to guarantee correct recognition, and this method requires receiving a large number of codewords to perform blind recognition.

[0077] The method provided in this embodiment is applied to LDPC encoding, which can easily and quickly identify encoding parameters, improve recognition efficiency, and does not require a large number of encoded codewords, only one frame is needed. It has a higher accuracy and better practicality.

[0078] The technical solution provided in this embodiment offers a novel method for identifying encoding parameters. This method can decode and re-encode the received codeword sequence based on the encoding parameters extracted from a preset closed set as the target encoding parameters. Then, it determines whether the encoding parameter is the target encoding parameter based on whether the check parts of the self-encoded codeword sequence and the received codeword sequence match. This achieves the effect of blind identification and blind decoding when only a small number of codewords, or even just one frame, are received, greatly reducing the difficulty of identifying encoding parameters.

[0079] Example 3

[0080] Figure 3A This is a flowchart of an encoding parameter identification method provided by an embodiment of the present invention. In this embodiment, optionally, the method is applied to LDPC encoding in the DVB-S2 communication standard. Optionally, the encoding parameter is the LDPC encoding parameter, the received codeword sequence is the received LDPC encoded codeword sequence, and the self-encoded codeword sequence is a self-compiled LDPC encoded codeword sequence. Optionally, the received codeword sequence can be an LDPC encoded codeword sequence transmitted in the DVB-S2 communication standard.

[0081] The technical solutions provided by the embodiments of the present invention include:

[0082] S310: Take a set of LDPC encoding parameters from a preset closed set as target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received LDPC encoded codeword sequence.

[0083] S320: Decode the received LDPC encoded codeword sequence based on the target encoding parameters to obtain the decoding result.

[0084] S330: Encode the decoding result to obtain a self-compiled LDPC codeword sequence.

[0085] S340: Determine whether the self-compiled LDPC codeword sequence matches the check bit portion of the received LDPC codeword sequence.

[0086] If yes, execute S350; otherwise, execute S360.

[0087] One method for determining whether the self-encoded codeword sequence matches the received codeword sequence is to use a comparison and verification method.

[0088] The verification part consists of the (NK) bits of the received codeword sequence and the self-encoded codeword sequence; where N is the length of the received codeword sequence and the self-encoded codeword sequence, and K is the length of the source sequence obtained in the above steps.

[0089] Furthermore, the verification parts of the received codeword sequence and the self-encoded codeword sequence are compared. If all the verification parts are consistent, the encoding and decoding parameters at this time are returned as the blind recognition result.

[0090] S350: Use the target encoding parameters as the encoding parameters of the received LDPC encoded codeword sequence.

[0091] S360: Take the next set of encoding parameters from the closed set and return it as the target encoding parameters to S320.

[0092] Therefore, the method provided in this embodiment of the invention is applied to LDPC encoded codeword sequences in the DVB-S2 communication standard. In this application scenario, all possible encoding parameters of the received codeword sequence are discrete and finite, which facilitates the construction of closed sets. This reduces the number of repetitions and the amount of computation in the subsequent identification process. Furthermore, the method provided in this embodiment of the invention can easily and quickly identify LDPC encoding parameters. It does not require receiving a large number of encoded codewords, only one frame is needed, and blind identification can be achieved even in harsh communication environments. Specific Implementation

[0094] To more clearly illustrate the technical solutions provided in the embodiments of the present invention, Figure 3B , 3C This is a schematic diagram of a specific application scenario applicable to Embodiment 3 of the present invention.

[0095] like Figure 3BAs shown, taking the closed set C = {(N,K)|(16200,5400), (16200,7200)} as an example, when identifying the LDPC encoded codeword sequence with parameters (16200,7200) of a frame X1 under noise-free conditions, the parameter (16200,5400) in the set is selected. The received encoded X1 is first decoded and then encoded using this parameter to obtain the source sequence U1 and the self-encoded codeword sequence X2. Since the encoding parameters of the actual received encoded codeword sequence are (16200,7200), the last (NK) bits of the received codeword sequence X1 and the self-encoded codeword sequence X2 are compared in this round of traversal. The ratio of different bits between the two sequences is about 0.5, that is, the two are mismatched. It can be confirmed that the encoding parameters of the received codeword sequence are not (16200,5400).

[0096] Continue iterating through the parameters in the closed set, such as... Figure 3C As shown, the parameters to be traversed next are (16200, 7200), resulting in the source sequence U2 and the self-encoded codeword sequence X3. Since the encoding parameter X1 of the actual received codeword sequence is (16200, 7200), the last (NK) bits of the received codeword sequence X1 and the self-encoded codeword sequence X3 are compared in this round of traversal. The two sequences are completely identical, that is, they are matched, and the parameters (16200, 7200) of the LDPC encoded codeword sequence are correctly identified.

[0097] With the above settings, LDPC encoding parameters can be easily and quickly identified in a zero-noise, non-cooperative communication environment.

[0098] The above embodiments represent matching results under ideal noise-free environments. In actual communication, the received sequences are all contaminated by noise. In this embodiment of the invention, the method can be applied to harsh environments and can still be used for identification.

[0099] For example, taking BPSK (Binary Phase Shift Keying) as an example, Table 1 gives the LDPC encoding parameters as (16200, 7200) in different... Under signal-to-noise ratio conditions, compare the different proportions of the last 9000 bits of the self-encoded codeword sequence and the received code sequence:

[0100]

[0101] As shown in the table above, when channel conditions are very poor, the different proportions are approximately 0.5; as channel conditions improve, the different proportions gradually decrease and approach 0. When setting different decision thresholds, a balance needs to be struck between recognition rate and accuracy: if the decision threshold is set relatively high (e.g., <0.4), the invention can identify coding parameters in harsh environments, but the accuracy is low; if the decision threshold is set relatively low (e.g., <0.1), the invention can identify coding parameters in normal environments, and the accuracy can reach 100%. Therefore, the decision threshold can be flexibly selected according to the actual situation to meet practical needs.

[0102] Define the present invention The boundary is as follows: When the modulation method is BPSK, the threshold for different proportions is set to 0.1. If in It can continuously and correctly identify 10,000 frames under channel conditions, but compared to... In harsher environments, it becomes impossible to continuously and correctly identify 10,000 frames, so it is recorded... To identify boundaries.

[0103] The following presents several information lengths K under BPSK modulation with a frame length N of 16200. The boundaries are shown in Table 2:

[0104] As shown in Table 2, with the increase in bit rate Increase, The boundary first decreases and then increases. Overall... The relatively low boundary means that the present invention can achieve blind identification and blind decoding in harsh communication environments, and has considerable practicality.

[0105] Table 2

[0106]

[0107] Example 4

[0108] Figure 4 This is a schematic diagram of the structure of an encoding parameter recognition device provided in Embodiment 4 of the present invention. Figure 4 As shown, the device includes:

[0109] The selection module 410 is used to extract a set of encoding parameters from a preset closed set as target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence.

[0110] The decoding module 420 is used to decode the received codeword sequence based on the target encoding parameters to obtain a decoding result.

[0111] The self-encoding module 430 is used to encode the decoding result to obtain a self-encoded codeword sequence.

[0112] The determining module 440 is used to use the target encoding parameter as the encoding parameter of the received codeword sequence if the self-encoded codeword sequence matches the received codeword sequence.

[0113] The return module 450 is used to extract the next set of encoding parameters from the closed set as the target encoding parameters if the self-encoded codeword sequence does not match the received codeword sequence, and return the operation of decoding the received codeword sequence based on the target encoding parameters.

[0114] Furthermore, the selection module 410 described above can be specifically used to extract a set of encoding parameters from a preset closed set as target encoding parameters; wherein, the encoding parameters are LDPC encoding parameters, the received codeword sequence is a received LDPC encoded codeword sequence, and the self-encoded codeword sequence is a self-compiled LDPC encoded codeword sequence; wherein, the LDPC encoded codeword sequence includes an LDPC encoded codeword sequence based on the DVB-S2 communication standard.

[0115] Furthermore, the aforementioned decoding module 420 is used to decode the received codeword sequence based on the target encoding parameters to obtain a decoding result; wherein, the encoding parameters are LDPC encoding parameters, and the received codeword sequence is a received LDPC encoded codeword sequence, including an LDPC encoded codeword sequence based on the DVB-S2 communication standard.

[0116] Furthermore, the aforementioned encoding module 430 can be specifically used to encode the decoding result to obtain a self-encoded codeword sequence; wherein, the self-encoded codeword sequence is a self-compiled LDPC encoded codeword sequence.

[0117] Furthermore, the aforementioned determining module 440 can be specifically used to determine whether the self-encoded codeword sequence matches the received codeword sequence. If the self-encoded codeword sequence matches the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence. If the self-encoded codeword sequence does not match the received codeword sequence, the encoding is submitted to the return module 450 for the next step.

[0118] Furthermore, the aforementioned determining module 440 can be specifically used to determine whether the check bit portion of the self-encoded codeword sequence matches the portion of the received codeword sequence. If the difference ratio of the last M bits of the self-encoded codeword sequence and the received codeword sequence is less than the decision threshold, the target encoding parameter is used as the encoding parameter of the received codeword sequence. Correspondingly, if the check bit portion of the self-encoded codeword sequence does not match the portion of the received codeword sequence, the encoding is submitted to the return module 350 for the next step.

[0119] Optionally, the decoding module 420 may further include a verification module 421, which may be specifically used to query the verification matrix based on the encoding parameters of the received codeword sequence, and to verify the decoding result based on the verification matrix.

[0120] The encoding parameter identification device provided in the embodiments of the present invention can execute the encoding parameter identification method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0121] Example 5

[0122] Figure 5 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is provided. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0123] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0124] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0125] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the encoded parameter identification method.

[0126] In some embodiments, method-encoded parameter identification may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method-encoded parameter identification method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method-encoded parameter identification method by any other suitable means (e.g., by means of firmware).

[0127] The memory 18 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device controlled by the smart terminal. Furthermore, the memory 18 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 520 may optionally include memory remotely located relative to the processor 11, and these remote memories can be connected to the electronic device controlled by the smart terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0128] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0129] These computational programs (also referred to as programs, software, software applications, or code) include machine instructions for a programmable processor and can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. As used herein, the terms “machine-readable medium” and “computer-readable medium” refer to any computer program product, device, and / or apparatus (e.g., disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor, including machine-readable media that receive machine instructions as machine-readable signals. The term “machine-readable signal” refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0130] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0131] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0132] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0133] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0134] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0135] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0136] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for identifying encoded parameters, characterized in that, include: A set of encoding parameters is taken from a preset closed set as the target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence; The received codeword sequence is decoded based on the target encoding parameters to obtain the decoding result; The decoding result is then encoded to obtain a self-encoded codeword sequence; If the self-encoded codeword sequence matches the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence; If the self-encoded codeword sequence does not match the received codeword sequence, the next set of encoding parameters is taken from the closed set as the target encoding parameters, and the operation of decoding the received codeword sequence based on the target encoding parameters is returned. Wherein, if the self-encoded codeword sequence matches the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence, including: if the self-encoded codeword sequence matches the parity bit portion of the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence; correspondingly, if the self-encoded codeword sequence does not match the received codeword sequence, the next set of encoding parameters is taken from the closed set and used as the target encoding parameter, including: if the self-encoded codeword sequence does not match the parity bit portion of the received codeword sequence, the next set of encoding parameters is taken from the closed set and used as the target encoding parameter; Wherein, if the self-encoded codeword sequence matches the parity bit portion of the received codeword sequence, the target encoding parameter is used as the encoding parameter of the received codeword sequence, including: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is less than a decision threshold, the target encoding parameter is used as the encoding parameter of the received codeword sequence; correspondingly, if the self-encoded codeword sequence does not match the parity bit portion of the received codeword sequence, the next set of encoding parameters is taken from the closed set as the target encoding parameter, including: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is greater than a decision threshold, the next set of encoding parameters is taken from the closed set as the target encoding parameter; where M=NK, where N is the frame length of the received codeword sequence, and K is the information length.

2. The method according to claim 1, characterized in that, The encoding parameters are LDPC encoding parameters, the received codeword sequence is the received LDPC encoded codeword sequence, and the self-encoded codeword sequence is a self-compiled LDPC encoded codeword sequence.

3. The method according to claim 2, characterized in that, The LDPC encoded codeword sequence includes an LDPC encoded codeword sequence based on the DVB-S2 communication standard.

4. The method according to claim 3, characterized in that, Also includes: The verification matrix is ​​queried based on the encoding parameters of the received codeword sequence, and the decoding result is verified based on the verification matrix.

5. The method according to claim 1, characterized in that, Also includes: If the encoding parameters in the preset closed set are traversed and neither the self-encoded codeword sequence nor the received codeword sequence match, then the recognition is deemed to have failed.

6. A device for identifying encoded parameters, characterized in that, include: A selection module is used to extract a set of encoding parameters from a preset closed set as target encoding parameters; wherein, the closed set is formed by several sets of encoding parameters corresponding to the encoding type of the received codeword sequence; The decoding module is used to decode the received codeword sequence based on the target encoding parameters to obtain a decoding result; The autoencoder module is used to encode the decoding result to obtain an autoencoder codeword sequence; The determining module is used to, if the self-encoded codeword sequence matches the received codeword sequence, use the target encoding parameter as the encoding parameter of the received codeword sequence; The return module is used to, if the self-encoded codeword sequence does not match the received codeword sequence, extract the next set of encoding parameters from the closed set as the target encoding parameters, and return the operation of decoding the received codeword sequence based on the target encoding parameters; Specifically, the determining module is used to: if the self-encoded codeword sequence matches the check bit portion of the received codeword sequence, use the target encoding parameter as the encoding parameter of the received codeword sequence; correspondingly, if the self-encoded codeword sequence does not match the received codeword sequence, extract the next set of encoding parameters from the closed set as the target encoding parameter, including: if the self-encoded codeword sequence does not match the check bit portion of the received codeword sequence, extract the next set of encoding parameters from the closed set as the target encoding parameter; Specifically, the determining module is used to: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is less than a decision threshold, use the target encoding parameter as the encoding parameter of the received codeword sequence; correspondingly, if the check bit portion of the self-encoded codeword sequence and the received codeword sequence does not match, extract the next set of encoding parameters from the closed set as the target encoding parameter, including: if the difference ratio between the last M bits of the self-encoded codeword sequence and the received codeword sequence is greater than a decision threshold, extract the next set of encoding parameters from the closed set as the target encoding parameter; where M=NK, where N is the frame length of the received codeword sequence, and K is the information length.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method of any one of claims 1-7.

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