Decoding Method, Device, Electronic Device, and Storage Medium

Abstract

The present application relates to a decoding method, apparatus, electronic device, and storage medium, which are applied in the field of computer technology. The method includes: obtaining initial data to be decoded; obtaining a target offset parameter corresponding to the current noise environment; performing offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded; and decoding the target data to be decoded to obtain a decoding result. This is to solve the problem in the prior art that the theoretical basis of the sum-product algorithm is BP, and when it is affected by noise, especially when the influence is large, incorrect decoding may also occur.

Description

Technical Field

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

[0002] At present, 5G (5th Generation Mobile Communication Technology) technology is constantly developing and has been deeply applied to various aspects of social production and management, becoming an important technology closely related to people's daily work and life. There are three application scenarios of 5G, namely eMBB (Enhanced Mobile Broadband), enhanced mobile Internet scenario; uRLLC (Ultra-Reliable and Low-Latency Communication), ultra-high reliability and low-latency communication scenario, used for some industrial automation services; mMTC (Massive Machine Type Communication), usually used for large-scale machine communication and large-scale Internet of Things services, so as to achieve the goal of connecting everything.

[0003] With the continuous development of wireless communication technology, digital signals have become the main signal processing method. Compared with analog signals, digital signals have higher anti-interference ability, it is easier to improve confidentiality, and can be used in combination with modern signal processing technology. Due to the complex nature of the channel, the modulated signal will be more or less affected by the channel when it is transmitted in the channel. Therefore, in the communication system, channel coding is often used as an effective method to correct errors, thereby reducing the system bit error rate. Channel coding is to add artificially controllable redundancy to the signal sending end, and these redundancies can be used for error detection and correction at the receiving end.

[0004] In the existing 5G UE (user equipment) hardware implementation, the commonly used decoding algorithm for low-density parity-check (LDPC) code decoders is the Sum-Product Algorithm (SPA). The Sum-Product Algorithm uses the Belief Propagation (BP) algorithm as the algorithm basis. Through iteration, it can better meet the decoding requirements within a limited number of iterations. The relationship between the decoded bit error rate (BER) and the speed and area is better than other algorithms. However, the theoretical basis of the Sum-Product Algorithm is BP. When affected by noise, especially when the influence is large, it may not be decoded correctly. Summary of the Invention

[0005] The present application provides a decoding method, apparatus, electronic device, and storage medium to solve the problem in the prior art that when the theoretical basis of the sum-product algorithm is BP and is affected by noise, especially when the influence is large, incorrect decoding may also occur.

[0006] In a first aspect, an embodiment of the present application provides a decoding method, including:

[0007] Obtain initial data to be decoded;

[0008] Obtain a target offset parameter corresponding to the current noise environment;

[0009] Perform offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded;

[0010] Decode the target data to be decoded to obtain a decoding result.

[0011] Optionally, the performing offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded includes:

[0012] Compensate the target offset parameter to obtain multiple branch offset parameters;

[0013] Add each branch offset parameter to the initial data to be decoded respectively to obtain the target data to be decoded.

[0014] Optionally, the compensating the target offset parameter to obtain multiple branch offset parameters includes:

[0015]

[0016] where param represents the target offset parameter, Ln represents the number of branches, and param i represents the i-th branch offset parameter, where 1 ≤ i ≤ Ln.

[0017] Optionally, the decoding the target data to be decoded to obtain a decoding result includes:

[0018] Input the target data to be decoded into an iterative operation logic;

[0019] When the number of iterations of the iterative operation logic reaches a preset number of times, obtain an iterative result;

[0020] Perform a hard decision on the iterative result to obtain a decision result;

[0021] Judge the decision result based on CRC to obtain a judgment result;

[0022] Determine that the judgment result of correct judgment is the decoding result.

[0023] Optionally, the inputting the target data to be decoded into the iterative operation logic includes:

[0024] Input the target data to be decoded into Ln decoding branches, and the iterative operation logic is configured in the decoding branches.

[0025] Optionally, the obtaining the target offset parameter corresponding to the current noise environment includes:

[0026] Obtain the sample encoded data and the sample data to be decoded of the sample encoded data in the current noise environment;

[0027] Obtain the noise influence coefficient in the current noise environment;

[0028] In each of the current noise environments, determine the target offset parameter based on at least one set of operation data, and each set of the operation data includes the sample encoded data, the sample data to be decoded, and the noise influence coefficient.

[0029] Optionally, the determining the target offset parameter based on at least one set of operation data includes:

[0030] Calculate an initial offset parameter based on each set of the operation data;

[0031] Determine the mean value of the initial offset parameter as the target offset parameter.

[0032] In a second aspect, an embodiment of the present application provides a decoding device, including:

[0033] A first obtaining module, configured to obtain initial data to be decoded;

[0034] A second obtaining module, configured to obtain a target offset parameter corresponding to the current noise environment;

[0035] An adjustment module, configured to perform offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded;

[0036] A decoding module, configured to decode the target data to be decoded to obtain a decoding result.

[0037] In a third aspect, an embodiment of the present application provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0038] The memory is configured to store a computer program;

[0039] The processor is configured to execute the program stored in the memory to implement the decoding method described in the first aspect.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the decoding method described in the first aspect.

[0041] The above technical solution provided by the embodiment of the present application has the following advantages compared with the prior art: In the method provided by the embodiment of the present application, initial data to be decoded is obtained; a target offset parameter corresponding to the current noise environment is obtained; the initial data to be decoded is offset and adjusted based on the target offset parameter to obtain target data to be decoded; and the target data to be decoded is decoded to obtain a decoding result. In this way, considering the influence of noise on the original data to be decoded, the initial data to be decoded is offset and adjusted by the target offset parameter in the obtained current noise environment, so that the obtained target data to be decoded is subject to a certain degree of noise correction, thereby improving the decoding accuracy after decoding the target data to be decoded. Description of the Drawings

[0042] The drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present invention and, together with the specification, are used to explain the principles of the present invention.

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 It is a diagram of an application scenario of the decoding method provided by an embodiment of the present application;

[0045] Figure 2 It is a flowchart of the decoding method provided by an embodiment of the present application;

[0046] Figure 3 It is a structural diagram of a branch improved decoder in the decoding method provided by an embodiment of the present application;

[0047] Figure 4 It is a structural diagram of a decoder in the decoding method provided by another embodiment of the present application;

[0048] Figure 5 It is a schematic diagram of the simulation effect provided by an embodiment of the present application;

[0049] Figure 6Schematic diagram of simulation effect provided by another embodiment of the present application;

[0050] Figure 7 Schematic diagram of simulation effect provided by another embodiment of the present application;

[0051] Figure 8 Structural diagram of a decoding device provided by an embodiment of the present application;

[0052] Figure 9 Structural diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0053] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0054] Before further elaborating on the embodiments of the present invention, the nouns and terms involved in the embodiments of the present invention are described. The nouns and terms involved in the embodiments of the present invention are subject to the following explanations.

[0055] eMBB (Enhanced Mobile Broadband): Enhanced Mobile Broadband, which refers to the further improvement of performance such as user experience based on the existing mobile broadband service scenario.

[0056] URLLC (Ultra-Reliable and Low-Latency Communication): Ultra-Reliable and Low-Latency Scenario.

[0057] mMTC (Massive Machine Type Communication): Massive Machine Type Communication (Large-Scale Internet of Things).

[0058] 3GPP (3rd Generation Partnership Project): 3rd Generation Partnership Project.

[0059] 5G (5th Generation Mobile Communication Technology): 5th Generation Mobile Communication Technology, which is a new generation of broadband mobile communication technology with the characteristics of high speed, low latency and large connection. 5G communication facilities are the network infrastructure for realizing the interconnection of humans, machines and things.

[0060] LDPC (low-density parity-check): Low-Density Parity-Check code.

[0061] Polar code: Polar code, a forward error correction coding method used for signal transmission.

[0062] BP: belief Propagation, the belief propagation algorithm.

[0063] UE: user equipment, user equipment.

[0064] SNR: Signal Noise Ratio, signal-to-noise ratio.

[0065] BER: Bit Error Rate, bit error rate.

[0066] Block Error Rate (BLER) refers to the ratio of the number of error blocks to the total number of received blocks in a digital circuit.

[0067] SPA: Sum-Product Algorithm, sum-product algorithm.

[0068] HARQ: Hybrid Automatic Repeat reQuest, hybrid automatic repeat request.

[0069] BF: Bit-Flipping, bit-flipping algorithm.

[0070] IQ modulation: The IQ signal is also called the in-phase quadrature signal. I is in-phase and Q is quadrature, with a 90° phase difference from I.

[0071] Es / N0: Ratio of symbol energy to noise power spectral density, the ratio of the energy per symbol to the noise power spectral density.

[0072] CRC (Cyclic Redundancy Check) is a fast algorithm that generates a short fixed-length check code based on data such as network data packets or computer files. It is mainly used to detect or verify possible errors in data transmission or storage.

[0073] Log-Likelihood Ratio (LLR) is a commonly used soft demodulation method for QAM.

[0074] According to an embodiment of the present application, a decoding method is provided. Optionally, in the embodiment of the present application, the above decoding method can be applied to, for exampleFigure 1 In the hardware environment composed of the terminal 101 and the server 102 as shown. As Figure 1 shown, the server 102 is connected to the terminal 101 through a network, and can be used to provide services (such as application services, etc.) for the terminal or the client installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for the server 102. The above network includes but is not limited to: wide area network, metropolitan area network or local area network. The terminal 101 is not limited to a PC, mobile phone, tablet computer, etc.

[0075] The decoding method of the embodiment of the present application can be executed by the server 102, or can be executed by the terminal 101, or can also be jointly executed by the server 102 and the terminal 101. Among them, when the terminal 101 executes the decoding method of the embodiment of the present application, it can also be executed by the client installed on it.

[0076] Taking the terminal executing the decoding method of the embodiment of the present application as an example, Figure 2 is a schematic flowchart of an optional decoding method according to an embodiment of the present application. As Figure 2 shown, the process of this method can include the following steps:

[0077] Step 201, obtain the initial data to be decoded.

[0078] In some embodiments, after the encoder encodes the original data to obtain encoded data, it is transmitted to the terminal where the decoder is located through a channel. After the terminal calculates the LLR of the transmitted data, the initial data to be decoded, that is, the LLR value, is obtained.

[0079] Since the data is transmitted through the channel, it will be more or less affected by the channel (such as noise). This will cause the direct decoding result of the initial data to be decoded obtained by the terminal to be different from the encoded value obtained after encoding.

[0080] Step 202, obtain the target offset parameter corresponding to the current noise environment.

[0081] In some embodiments, in the case of facing different noise environments, the noise will also have different degrees of influence on the transmitted data. Based on this, the target offset parameter corresponding to the current noise environment can be determined from multiple noise environments, and the initial data to be decoded is adjusted based on this target offset parameter.

[0082] In an optional embodiment, the obtaining the target offset parameter corresponding to the current noise environment includes:

[0083] Obtain the sample encoded data and the sample data to be decoded of the sample encoded data in the current noise environment;

[0084] Obtain the noise impact coefficient in the current noise environment;

[0085] In each of the current noise environments, determine the target offset parameter based on at least one set of operation data, where each set of operation data includes the sample coding data, the sample data to be decoded, and the noise impact coefficient.

[0086] In some embodiments, the target offset parameter can be derived from sample data in multiple noise environments. Among them, the sample data includes sample coding data and the sample data to be decoded of the sample coding data in the at least one noise environment.

[0087] Among them, the noise impact coefficient is a constant used to determine the target offset parameter in each noise environment.

[0088] Generally, the operation of LLR can be expressed as: Where s represents the coding data without noise interference, y represents the received data to be decoded after noise interference. p(s = 0|y) represents the probability that s is 0 when y data is received. p(s = 1|y) represents the probability that s is 1 when y data is received.

[0089] After constellation mapping, the data will pass through IQ modulation. For a BPSK channel, the data is represented by 1 and -1 on the x-axis and y-axis corresponding to IQ modulation respectively, and the corresponding mapped data obtained is: {0.7071 + 0.7071i, -0.7071 - 0.7071i}. When mapped to the representation of s, it corresponds to 0 and 1.

[0090] Considering that before the data enters the decoder in the UE, it will first undergo the operation of noise whitening, so that the influence of noise on the data conforms to the distribution characteristics of Gaussian noise. Therefore, it can be assumed that the mean value of the noise is 0 and the variance is σ 2 .

[0091] For the characteristics of BPSK, performing operation conversion on the above LLR, we can obtain:

[0092]

[0093] Also, because under Gaussian noise, the influence of noise can be expressed as additive noise, that is to say, assuming the noise is n at this time, the above y can be expressed as: y = s + n

[0094] Therefore, the above LLR can be expressed as:

[0095] Further transformation can obtain:

[0096] Based on the above formula, using the obtained sample coding data (s), the sample data to be decoded (LLR), and the noise influence coefficient (σ 2 ), the offset parameter (n) can be calculated.

[0097] Among them, it can be set that: Es / N0≈SNR, and using Es / N0, the following can be calculated: Therefore, by simulating SNR in different noise environments, different σ values can be obtained.

[0098] For different SNRs, under the characteristic of additive noise, y = s + n. It can be set that s = 0, and simulations of different SNRs in a Gaussian noise environment are carried out, and then the mean value is taken to obtain the additive noise reference value, that is, σ, for different SNRs.

[0099] In an alternative embodiment, determining the target offset parameter based on at least one set of operation data includes:

[0100] Calculating an initial offset parameter based on each set of the operation data;

[0101] Determining the mean value of the initial offset parameters as the target offset parameter.

[0102] In some embodiments, to improve the accuracy of the offset parameter, operations can be performed through multiple sets of operation data, and by calculating the mean value of the initial offset parameters, the target offset parameter can be obtained.

[0103] Step 203: Perform offset adjustment on the initial data to be decoded based on the target offset parameter to obtain the target data to be decoded.

[0104] In some embodiments, after obtaining the target offset parameter, the initial data to be decoded can be offset adjusted to achieve the effect of filtering the noise in the initial data to be encoded.

[0105] Among them, performing offset adjustment on the initial data to be decoded by the target offset parameter can be to perform an addition operation on the target offset parameter and each data in the initial data to be decoded.

[0106] In an alternative embodiment, performing offset adjustment on the initial data to be decoded based on the target offset parameter to obtain the target data to be decoded includes:

[0107] Compensating the target offset parameter to obtain multiple branch offset parameters;

[0108] Respectively adding each branch offset parameter to the initial data to be decoded to obtain the target data to be decoded.

[0109] In some embodiments, to improve the accuracy of offset adjustment, multiple compensation branches may be set based on the target offset parameter, and the target offset parameter may be segmented and compensated downward to obtain multiple branch offset parameters. Furthermore, the branch offset parameters are respectively added to the initial data to be decoded, so that within a certain compensation range, the target offset parameter is divided into multiple branch offset parameters, and the branch offset parameters are values that are not much different from the target offset parameter, thereby being able to improve the accuracy of the target data to be decoded to a certain extent.

[0110] In an alternative embodiment, compensating the target offset parameter to obtain multiple branch offset parameters includes:

[0111]

[0112] where param represents the target offset parameter, Ln represents the number of branches, and represents the i-th branch offset parameter, where 1 ≤ i ≤ Ln. i represents the i-th branch offset parameter, where 1 ≤ i ≤ Ln.

[0113] where i is usually set to an odd number. Thus, while compensating the target offset parameter, it can be ensured that the target offset parameter itself can participate in the offset adjustment process, thereby making the decoding result more accurate.

[0114] Correspondingly, in the above calculation method of the branch offset parameter, and represent branch coefficients when i takes different values.

[0115] In some embodiments, the number of branches can be set based on the actual situation. In practical applications, a number of branches can be set based on the relationship between the decoding improvement effect and the corresponding area and speed loss. The larger the number of branches, the stronger the decoding improvement effect, and the corresponding area or speed loss will be greater. Therefore, the setting of the number of branches should not be too large or too small.

[0116] where the number of branches can also be determined by the number of decoding branches that can be parallel in the terminal. For example, if 9 decoding branches are set in the terminal, the number of branches can be the same as the number of decoding branches, and accordingly set to 9.

[0117] Step 204, decode the target data to be decoded to obtain a decoding result.

[0118] In some embodiments, after obtaining the target data to be decoded in the current noise environment, it can be input into the corresponding decoding channel for decoding to obtain a decoding result.

[0119] It can be understood that for some situations where the current noise environment cannot be determined, all the pre-determined target offset parameters can be calculated through the above decoding process, and those for which a result can be calculated are used as the decoding result. Correspondingly, the noise environment in which the result is calculated is the current noise environment. By selecting the target offset parameters in multiple noise environments and performing offset adjustment on the initial data to be decoded, the accuracy of the decoding result is improved.

[0120] In an alternative embodiment, decoding the target data to be decoded to obtain a decoding result includes:

[0121] Inputting the target data to be decoded into an iterative operation logic;

[0122] When the number of iterations of the iterative operation logic reaches a preset number, obtaining an iterative result;

[0123] Performing a hard decision on the iterative result to obtain a decision result;

[0124] Judging the decision result based on CRC to obtain a judgment result;

[0125] Determining that the decision result with a correct judgment result is the decoding result.

[0126] In some embodiments, the iterative operation logic can be an iterative operation composed of C2V and V2C. After the target data to be decoded is input into the iterative operation logic, iterative operations are performed in C2V and V2C. Generally, an iteration threshold is set. When the number of iterations reaches the preset number, it is considered that the data has converged to a stable state based on the BP theory at this time. A hard decision (outputting 0 if greater than 0, otherwise 1) is performed on the iterative result to obtain a judgment result. Furthermore, based on the judgment of CRC or based on the LDPC matrix, when the correct decoding result is encountered, it can be output. If all judgments are incorrect, HARQ is performed according to the protocol.

[0127] In an alternative embodiment, the inputting the target data to be decoded into the iterative operation logic includes:

[0128] Inputting the target data to be decoded into Ln decoding branches with the number of branches, and the iterative operation logic is configured in the decoding branches.

[0129] In some embodiments, to improve the decoding efficiency, in the above related embodiments, in the target data to be decoded, the result of adding multiple branch offset parameters to the initial data to be decoded respectively is involved, so there is more than one target data to be decoded. Therefore, multiple iterative operation logics can be set, that is, multiple groups of C2V and V2C, and the target data to be decoded is respectively input into each iterative operation logic for parallel calculation.

[0130] Among them, since C2V and V2C are both parallel in the conventional implementation of the UE, an iterative operation logic can also be used to calculate the target data to be decoded in parallel in this group of C2V and V2C.

[0131] In a specific embodiment, the setting of the offset parameter is related to the SNR environment that needs to be improved. A more accurate method can calculate different parameters according to the change of SNR, but this also requires adding additional operation logic to perform real-time operations for different SNRs. Considering the cost of hardware implementation and the relationship between the performance improvement of the obtained decoder, a more reasonable implementation method is to consider the environmental characteristics required by the UE and the improvement effect required, set different working intervals (i.e., noise environments), and calculate the offset parameters according to the lowest SNR in each interval for improvement.

[0132] Taking the working interval SNR of 0 to 3 dB as an example, at this time, the lowest SNR, which is 0 dB, is selected for calculating the offset parameter. The obtained offset parameter is 4.206112617. For the convenience of calculation, its integer value is taken as 4.

[0133] After obtaining the offset parameter, a branch number is set for the relationship between the obtained decoding improvement effect and the corresponding area and speed loss. The larger the branch number, the stronger the decoding improvement effect, but the corresponding area or speed loss will be greater.

[0134] Assume that the currently determined branch number is Ln, then the parameter param for each branch calculated based on the offset parameter is:

[0135] Based on the above parameter definitions, for the hardware implementation structure of the decoder, refer to Figure 3 , which implements the structure of the branch-improved decoder.

[0136] Figure 3 In, after the left LLR is input, the calculated param (i.e., the above-mentioned target offset parameter) will be added to the input LLR (i.e., the above-mentioned initial data to be decoded) respectively according to i to obtain Ln different LLR' (i.e., the above-mentioned target data to be decoded), and then they are respectively input to C2V for operation. The operation results are respectively added in V2C. After completing the set number of iterations, they are input to the judgment module for judgment based on CRC or based on the LDPC matrix. The judgment order is from i = max to i = 1. When a correct decoding result is encountered, the output can be made. If all judgments are incorrect, HARQ is performed according to the protocol.

[0137] At the same time, since C2V and V2C are both parallel in the conventional implementation of the UE, the present invention can also use a C2V and V2C module with parallel operation units, as shown inFigure 4 As shown, in the implementation of the UE for the C2V and V2C modules, in order to improve performance, several data inputs are generally processed in parallel for simultaneous operations. Therefore, the present invention can also use parallel resources to replace different LLR inputs with LLR' inputs affected by the param, perform C2V operations using the parallel resources respectively, and then perform parallel operations and updates corresponding to V2C respectively. After completing the iterative operation of threshold setting, the output is judged, and the judgment method is the same as the above method.

[0138] To compare the BLER improvement effect of the present invention, considering that under PDSCH, the data transmission code length of NR is longer and the combination is more complex, different scenarios of NR's PDSCH are selected for simulation to compare their BLERs.

[0139] First, for the simulation test with a code rate of 0.5, the iteration number threshold set to 12 times, and EsN0 from 0 to 3 dB. Due to the code rate relationship, at this time, according to the protocol, BG1 is selected for encoding and decoding. The specific BLER is as Figure 5 shown.

[0140] The present invention is improved based on the original LSPA decoder, and the number of branches 3, 5, and 9 are respectively set for comparison. As can be seen from Figure 5, when the number of branches is 9, the improvement effect is obvious. Secondly, it weakens in turn, but compared with the original algorithm of LSPA, all have better improvement effects.

[0141] Similarly, in the case of Es / N0 from 0 to 3 dB, the code rate is 0.25. At this time, BG2 is selected for encoding and decoding to obtain the BLER. As Figure 6 shown, the improvement effect is obvious.

[0142] Change Es / N0 to -5 to -2 dB for testing, set the code rate to 0.25, and the number of iterations to 20 times for comparison. As Figure 7 can be seen, the obtained improvement effect is obvious.

[0143] In summary, the present invention can obtain a beneficial improvement effect on BLER.

[0144] Based on the same concept, an embodiment of the present application provides a decoding device. For the specific implementation of this device, reference can be made to the description in the method embodiment part, and the repeated parts will not be elaborated. As Figure 8 shown, the device mainly includes:

[0145] A first acquisition module 801, configured to acquire initial data to be decoded;

[0146] A second acquisition module 802, configured to acquire a target offset parameter corresponding to the current noise environment;

[0147] An adjustment module 803, configured to perform offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded;

[0148] A decoding module 804, configured to decode the target data to be decoded to obtain a decoding result.

[0149] Based on the same concept, an embodiment of the present application further provides an electronic device, as Figure 9 shown. The electronic device mainly includes: a processor 901, a memory 902, and a communication bus 903. Among them, the processor 901 and the memory 902 complete mutual communication through the communication bus 903. Among them, a program executable by the processor 901 is stored in the memory 902, and the processor 901 executes the program stored in the memory 902 to implement the following steps:

[0150] Obtain initial data to be decoded;

[0151] Obtain a target offset parameter corresponding to the current noise environment;

[0152] Perform offset adjustment on the initial data to be decoded based on the target offset parameter to obtain target data to be decoded;

[0153] Decode the target data to be decoded to obtain a decoding result.

[0154] The communication bus 903 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 903 may be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 9 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0155] The memory 902 may include a Random Access Memory (RAM), and may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor 901.

[0156] The above-mentioned processor 901 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc., or may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0157] The electronic device provided by the embodiments of the present application may specifically be a module capable of implementing a communication function or a terminal device including the module, etc. The terminal device may be a mobile terminal or an intelligent terminal. The mobile terminal may specifically be at least one of a mobile phone, a tablet computer, a laptop computer, etc.; the intelligent terminal may specifically be a terminal containing a wireless communication module such as an intelligent vehicle, an intelligent watch, a shared bicycle, an intelligent cabinet, etc.; the module may specifically be a wireless communication module, such as any one of a 2G communication module, a 3G communication module, a 4G communication module, a 5G communication module, an NB-IOT communication module, etc.

[0158] In another embodiment of the present application, a computer-readable storage medium is further provided. A computer program is stored in the computer-readable storage medium. When the computer program runs on a computer, the computer is caused to execute the decoding method described in the above embodiments.

[0159] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions are transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape, etc.), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state drive), etc.

[0160] It should be noted that in this document, 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 actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise", or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements that are inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article, or device that includes the element.

[0161] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the broadest scope consistent with the principles and novel features claimed herein.

Claims

1. A decoding method, characterized in that, it includes: Obtain the initial data to be decoded; Obtain the target offset parameter corresponding to the current noise environment; Compensate the target offset parameter to obtain multiple branch offset parameters, and add each branch offset parameter to the initial data to be decoded respectively to obtain the target data to be decoded; The compensating the target offset parameter to obtain multiple branch offset parameters includes: Among them, param represents the target offset parameter, Ln represents the number of branches, and param i represents the offset parameter of the i-th branch, where 1 ≤ i ≤ Ln; Decode the target data to be decoded to obtain a decoding result; Among them, decoding the target data to be decoded to obtain a decoding result includes: inputting the target data to be decoded into C2V for operation respectively, and the operation results are added in V2C respectively. After completing the set number of iterations, input them into the judgment module for judgment based on CRC or based on the LDPC matrix. The judgment order is from i = max to i = 1. When there is a correct decoding result, output the correct decoding result, where C2V and V2C form an iterative operation logic.

2. The decoding method according to claim 1, characterized in that, the decoding the target data to be decoded to obtain a decoding result includes: Input the target data to be decoded into the iterative operation logic; When the number of iterations of the iterative operation logic reaches the preset number, obtain the iterative result; Perform a hard decision on the iterative result to obtain a decision result; Judge the decision result based on CRC to obtain a judgment result; Determine that the judgment result being the correctly judged decision result is the decoding result.

3. The decoding method according to claim 2, characterized in that, the inputting the target data to be decoded into the iterative operation logic includes: Input the target data to be decoded into Ln decoding branches with the number of branches, and the iterative operation logic is configured in the decoding branches.

4. The decoding method according to claim 1, characterized in that, the obtaining the target offset parameter corresponding to the current noise environment includes: Obtain the sample encoded data and the sample data to be decoded of the sample encoded data in the current noise environment; Obtain the noise influence coefficient in the current noise environment; In each current noise environment, determine the target offset parameter based on at least one set of operation data, and each set of operation data includes the sample encoded data, the sample data to be decoded, and the noise influence coefficient.

5. The decoding method according to claim 4, characterized in that, the determining the target offset parameter based on at least one set of operation data includes: Calculate the initial offset parameter based on each set of operation data; Determine the mean value of the initial offset parameter as the target offset parameter.

6. A decoding device, characterized in that, it includes: A first acquisition module for acquiring the initial data to be decoded; A second acquisition module for acquiring the target offset parameter corresponding to the current noise environment; An adjustment module for compensating the target offset parameter to obtain multiple branch offset parameters, and adding each branch offset parameter to the initial data to be decoded respectively to obtain the target data to be decoded; Compensating the target offset parameter to obtain multiple branch offset parameters includes: Among them, param represents the target offset parameter, Ln represents the number of branches, and param i represents the offset parameter of the i-th branch, where 1 ≤ i ≤ Ln; A decoding module, configured to decode the target data to be decoded to obtain a decoding result; Among them, decoding the target data to be decoded to obtain a decoding result includes: respectively inputting the target data to be decoded into C2V for operation, performing addition operations on the operation results in V2C respectively, after completing a set number of iterations, inputting them into a judgment module for judgment based on CRC or an LDPC matrix, and the judgment order is from i = max to i = 1. When there is a correct decoding result, output the correct decoding result, where C2V and V2C constitute an iterative operation logic.

7. An electronic device Characterized in that It includes: A processor, a communication interface, a memory, and a communication bus. Among them, the processor, the communication interface, and the memory complete communication with each other through the communication bus; The memory is used to store a computer program; The processor is configured to execute the program stored in the memory to implement the decoding method according to any one of claims 1-5.

8. A computer-readable storage medium storing a computer program Characterized in that When the computer program is executed by a processor, it implements the decoding method according to any one of claims 1-5.

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