CN114584259A

CN114584259A - Decoding method, device, equipment and storage medium

Info

Publication number: CN114584259A
Application number: CN202210153634.5A
Authority: CN
Inventors: 胡继文; 童胜; 徐达人; 王仲立; 欧兆熊; 郑慧娟; 白宝明
Original assignee: Alibaba China Co Ltd
Current assignee: Alibaba China Co Ltd
Priority date: 2022-02-18
Filing date: 2022-02-18
Publication date: 2022-06-03
Anticipated expiration: 2042-02-18
Also published as: CN114584259B

Abstract

The embodiment of the application discloses a decoding method, a device, equipment and a storage medium, wherein the method comprises the following steps: obtaining a first message comprising first probability distribution data of coded bits; according to the first message, performing table query on the check node to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data; transmitting a second message from the check node to the variable node; according to the second message, performing table query on the variable node to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data; and when the third message meets the preset target condition, decoding the coded bits according to the third message to obtain a decoding result. According to the embodiment of the application, the output information of each node can be determined through table query of the check nodes and the variable nodes, so that the updating of the nodes is completed, and compared with a traditional calculation method, the calculation complexity is reduced, and the decoding efficiency is improved.

Description

Decoding method, device, equipment and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a decoding method, device, and storage medium.

Background

Low-Density Parity-Check (LDPC) codes are a class of channel codes with excellent performance, and can be applied to multiple communication standards to achieve reliable transmission of data.

In the related art, the decoding algorithm of the LDPC code is usually a sum-product algorithm or a modified minimum sum algorithm, but the sum-product algorithm has high operation complexity and high hardware implementation difficulty; the modified min-sum algorithm, although having a low computational complexity, will bring about a loss of decoding performance.

Disclosure of Invention

The embodiment of the application provides a decoding method, a decoding device, decoding equipment and a storage medium, which can improve the information decoding efficiency.

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

obtaining a first message comprising first probability distribution data of coded bits;

according to the first message, performing table query on the check node to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data;

transmitting a second message from the check node to the variable node;

according to the second message, performing table query on the variable node to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data;

and when the third message meets the preset target condition, carrying out decoding calculation on the coded bits according to the third message to obtain a decoding result.

In a second aspect, an embodiment of the present application provides a decoding apparatus, including:

a first obtaining module for obtaining a first message, the first message comprising first probability distribution data of coded bits;

the second query module is used for performing table query on the check node according to the first message to obtain a second message, and the second message comprises second probability distribution data of the first probability distribution data;

a first transmission module for transmitting the second message from the check node to the variable node;

the second query module is used for performing table query on the variable node according to the second message to obtain a third message, and the third message comprises third probability distribution data of the second probability distribution data;

and the decoding module is used for performing decoding calculation on the coded bits according to the third message under the condition that the third message meets the preset target condition to obtain a decoding result.

In a third aspect, embodiments of the present application provide a method

A computer device, comprising: a memory and a processor, wherein the processor is capable of,

a memory for storing a computer program;

a processor for executing a computer program stored in the memory, the computer program when run causing the processor to perform the steps of the decoding method as described in the first aspect.

In a fourth aspect, embodiments of the present application provide a computer storage medium, on which a program or instructions are stored, which, when executed by a computer device, cause the computer device to perform the steps of the decoding method according to the first aspect.

In a fifth aspect, embodiments of the present application provide a computer program product, which includes a computer program, and in a case where the computer program is executed by a computer device, the computer device is caused to execute the steps of the decoding method according to the first aspect.

In the decoding method, the decoding device, the decoding equipment and the storage medium, in the method, a first message is obtained, wherein the first message comprises first probability distribution data of coded bits; the check nodes are subjected to table query according to the first message to obtain a second message, the second message comprises second probability distribution data of the first probability distribution data, the message output by the check nodes is obtained in a table lookup mode, the operation complexity of the check nodes can be reduced when the check nodes are updated, and therefore the decoding efficiency is improved. The obtained second message is transmitted to the variable node, and the variable node can be subjected to table query according to the second message to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data. Therefore, the operation complexity of updating the variable nodes is reduced based on a table look-up mode when the variable nodes are updated; if the obtained third message meets the preset target condition, the coding bit can be decoded and calculated according to the message, and a decoding result is obtained. Therefore, the embodiment of the application can determine the output information of each node through table query of the check nodes and the variable nodes so as to complete the update of the nodes, and compared with the traditional calculation method, the method has the advantages that the operation complexity is reduced, and the decoding efficiency is improved.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a block diagram of a decoding system according to an embodiment of the present application;

FIG. 2 is a flowchart illustrating a decoding method according to an embodiment of the present application;

FIG. 3 is a diagram illustrating the relationship of variables of the IB algorithm in an exemplary embodiment of the present application;

FIG. 4 is a diagram illustrating the quantitative calculation of a message by the IB algorithm in another embodiment of the present application;

figure 5 is a schematic diagram of a forward algorithmic table lookup of check nodes in yet another embodiment of the present application,

FIG. 6 is a diagram illustrating a backward algorithm table lookup of check nodes in a further embodiment of the present application;

FIG. 7 is a table lookup for intermediate check nodes in yet another embodiment of the present application;

FIG. 8 is a table look-up of a forward algorithm for variable nodes according to yet another embodiment of the present application;

FIG. 9 is a diagram illustrating backward algorithmic table lookup of variable nodes according to yet another embodiment of the present application;

FIG. 10 is a schematic structural diagram of a decoding apparatus according to another embodiment of the present application;

fig. 11 is a schematic structural diagram of a computer device according to still another embodiment of the present application.

Detailed Description

Features of various aspects and exemplary embodiments of the present application will be described in detail below, and in order to make objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of, and not restrictive on, the present application. It will be apparent to one skilled in the art that the present application may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present application by illustrating examples thereof.

It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The LDPC code may be applied to a plurality of Communication standards, such as Mobile multimedia broadcasting standard, WiMax (World Interoperability for Microwave Access), second Generation standard for Satellite Digital Video broadcasting (Digital Video Broadcast-Satellite2, DVB-S2), IEEE 1102.3, and the latest fifth Generation Mobile Communication Technology (5th Generation Mobile Communication Technology, 5G) new air interface, and so on. In a communication scenario, a decoder of the LDPC code quantizes local operations of variable nodes or check nodes by using a decoding algorithm, wherein the decoding algorithm commonly used in the related art includes a sum-product algorithm and a modified minimum sum algorithm.

The performance of the sum-product algorithm is superior to that of the modified minimum sum algorithm, but the operation complexity of the sum-product algorithm is high, and particularly, the check node operation related to the sum-product algorithm relates to complex transcendental function calculation and is not beneficial to hardware implementation. The modified min sum algorithm has low complexity, but has low decoding performance.

In order to solve the problem of the prior art, embodiments of the present application provide a decoding method, apparatus, device, and storage medium, which can obtain messages to be exchanged between check nodes and variable nodes in a table query manner, so that mutual iteration between the check nodes and the variable nodes can be realized, the computation complexity is low, and further, the decoding efficiency is favorably improved.

The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.

Fig. 1 is a schematic structural diagram of a decoding system according to an exemplary embodiment of the present application. As shown in fig. 1, the system 100 includes: channel 101 and decoder 102;

a channel 101 for acquiring a first message comprising first probability distribution data of coded bits;

the decoder 102 is configured to perform table lookup on the check node according to the first message to obtain a second message, where the second message includes second probability distribution data of the first probability distribution data;

transmitting a second message from the check node to the variable node;

and when the third message meets the preset target condition, carrying out decoding calculation according to the third message coding bit to obtain a decoding result.

In the embodiment of the present application, the system 100 further comprises a modulator 103, and the channel 101 is communicatively connected to the modulator 103 to receive the signal of the coded bits modulated by the modulator 101 and convert the original discrete coded bit sequence into a transmission signal suitable for transmission in the channel. For example, the modulator 101 may use Binary Phase Shift Keying (BPSK) modulation, where the coded bits b ∈ {0,1}, and after BPSK modulation, the coded bits are mapped to the transmission signal x, x ═ 2b + 1. The channel 101 may be an Additive White Gaussian Noise (AWGN) channel, and after the transmitted signal x is transmitted through the AWGN channel, the output signal may be received by the decoder, that is, the received signal received by the decoder is y, y is x + N, and N is e N (0, σ N)²)，N(0,σ²) Is a Gaussian distribution of noise, where 0 is the mean of the Gaussian distribution of noise, σ²Is the variance of the gaussian distribution.

The channel 101 performs compression quantization processing on the received signal corresponding to the coded bits to obtain valid messages (i.e., quantized values) in the signal, wherein the compression quantization is a process of representing sampled values of the analog signal by using a predetermined finite number of levels to obtain finite discrete values. According to the probability distribution data of the original transmission signal of the quantization value and the coding bit, a first message is obtained through calculation and output to the decoder 102, the decoder controls the check node and the variable node to transmit messages to each other according to the first message, and table query is carried out according to the transmitted messages, so that mutual iteration of the check node and the variable node is achieved. And under the condition that the third message obtained by the variable node meets the preset target condition, decoding according to the third message to obtain the original discrete coding bit sequence through interpretation. For example, the decoder 102, as an LDPC decoder, may employ a plurality of bit nodes, the plurality of bit nodes including Variable Nodes (VN) and Check nodes (Check nodes, CN), the Variable nodes and Check nodes constructing a Check equation, wherein the bit nodes may be used to generate and/or store potential code bits, and the Check nodes may perform parity checking on different combinations of content on the bit nodes using the Check equation to complete the decoding. It should be understood that parity checking by check equations is well known in the art and will not be described in detail herein.

The decoding system provided by the embodiment can be applied to a decoding algorithm optimization scene of the solid-state storage device. For example, an Error Correction Code (ECC) engine is usually used by a solid-state hard disk storage chip (e.g., a Flash memory chip) to implement LDPC Code operation, so that the ECC engine can decode LDPC codes of received information based on the decoding system provided in the above embodiments of the present application, and is high in decoding efficiency and beneficial to improving decoding performance of a solid-state hard disk.

It should be understood that the solid-state storage device provided in the embodiment of the present application may be applied to a server, and the server provides storage services such as cloud storage and a data center, and accordingly, the decoding system provided in the embodiment may improve the quality of service in these application scenarios by improving the performance of the solid-state storage device.

Fig. 2 shows a flowchart of a decoding method provided in an embodiment of the present application. As shown in fig. 2, the decoding method includes steps S21 to S25:

s21 obtaining a first message, the first message including first probability distribution data of the coded bits;

s22, according to the first message, performing table query on the check node to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data;

s23 transmitting a second message from the check node to the variable node;

s24, according to the second message, performing table query on the variable node to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data;

and S25, when the third message meets the preset target condition, carrying out decoding calculation on the coded bits according to the third message to obtain a decoding result.

In the decoding method provided by the embodiment of the application, a first message is acquired, and the first message comprises first probability distribution data of coded bits; and performing table query on the check node according to the first message to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data, and the message output by the check node is obtained in a table lookup manner, so that the operation complexity of the check node can be reduced when the check node is updated, and the decoding efficiency is improved. And transmitting the obtained second message to the variable node, and performing table query on the variable node according to the second message to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data. Therefore, the operation complexity of updating the variable nodes is reduced when the variable nodes are updated based on a table look-up mode; if the obtained third message meets the preset target condition, the coded bits can be decoded according to the message, and a decoding result is obtained. Therefore, the embodiment of the application can determine the output information of each node through table query of the check nodes and the variable nodes so as to complete the update of the nodes, and compared with the traditional calculation method, the method has the advantages that the operation complexity is reduced, and the decoding efficiency is improved.

In the embodiment of the present application, the received signal received in the decoder is obtained by modulating discrete coded bits sent by the source and transmitting the modulated discrete coded bits through an AWGN channel. For example, the codeword sequence of the coded bits is { x }₁，x₂，x₃，x₄，x₅，x₆And decoding the check matrix constructed by the channel code word sequence to obtain the correct sequence of the discrete coding bits. And in the process of decoding the received signal, messages are transmitted back and forth between the variable nodes and the check nodes, and the updating iteration of the variable nodes and the check nodes is completed. The iterative process of the variable nodes and the check nodes can be a process of probability density evolution of the transmitted message, and the judgment of the code words corresponding to the received information is realized through the probability density evolution of the transmitted message, so that the decoding of the signal is completed.

To improve decoding performance, the probability density of messages transmitted between variable nodes and check nodes can be determined by finding the maximum mutual message, wherein the mutual message is the information amount of one variable containing the other variable, such as the information amount of the quantized value of the received signal containing the coded bits.

In this embodiment, in the process of updating and iterating the variable nodes and the check nodes, the variable nodes acquire the encoded bit-related initial probability density data output by the channel, form corresponding quantization messages, and transmit the quantization messages to the check nodes for iterating. Specifically, the step of acquiring the first message by the step S21 may specifically include the steps S211 to S213:

s211, setting first joint probability distribution data of coded bits and quantization bases of the coded bits, wherein the first joint probability distribution data are used for setting probability distribution obeyed after the coded bits are output through a channel;

s212, according to a preset algorithm, the first joint probability distribution data and the quantization base number are operated to obtain first probability distribution data corresponding to the coding bits;

s213 determines the first probability distribution data as the first message.

As a specific example, S21 may employ an information-bottleneck method (IB), which is hereinafter referred to as "IB algorithm," to perform compression quantization processing and node update on a signal received by the decoder by using mutual information as a metric, where the IB algorithm is used to perform node update, which is to perform quantization processing on a message transmitted in an iterative process of check node or variable node update.

The IB algorithm is a general information theory framework, and data are compressed and quantized by taking mutual information as a measure. For example, if the transmitted signal X of the coded bits is taken as the relevant variable X, X ∈ X, the IB algorithm performs data compression quantization on the received signal y, and extracts valid information in y. In this embodiment, a received signal Y is taken as an example of an observation variable Y, and Y ∈ Y is compressed to obtain a quantized value T. The IB algorithm can achieve two goals, one is to minimize the mutual message I (T; Y) and the other is to maximize the mutual message I (T, X), i.e. to make the quantization value T retain as much information about the transmitted signal X as possible.

The transmitted signal X and the received signal Y are correlated, so the joint probability density of the two can be denoted as p (X, Y), and the variable T is compressed from the variable Y, i.e. the Markov chain of X → Y → T as shown in fig. 3 is formed. In some examples, the joint probability density p (x, y) of the transmit signal x and the receive signal y may be expressed as the following equation (1):

referring to FIG. 3, the compressive relationship between variable Y and variable T can be described as a deterministic mapping of Y to T and can be expressed as a conditional probability distribution p (T | Y) between Y and T, T ∈ T. Then for the convenience of solution, the base | T | of the T-valued space may be fixed, for example, when quantizing a 4-bit received signal, the base | T | ═ 2⁴16, so that the mutual information I (T, X) is optimized, i.e. a deterministic mapping p (T | y) is found that maximizes the mutual information I (T, X) given the cardinality | T |.

Therefore, in order to facilitate quantization, it is necessary to find a unique compression variable t corresponding to an observed variable y. Referring to the IB algorithm quantization process shown in fig. 4, in S211, first joint probability distribution data p (x, y) of the received signal and the transmitted signal is constructed and a quantization base | T | of the received signal is set. In S212, based on the requirement of maximizing the mutual information I (T, X), the first joint probability distribution data p (X, y) is integrated by the IB algorithm to obtain the corresponding discretized joint distribution

With a fixed base | T | and

the IB algorithm operation is performed as data, and the corresponding conditional probability distribution data p (t | y) and the first probability distribution p (x, t) can be output.

In this embodiment, the conditional probability distribution data p (t | y) is used as a channel quantization constraint condition to represent the mapping relationship between the received signal and the quantization value when the mutual information is maximized, where the mutual information is the information amount of the transmission signal containing the coded bits in the quantization value. In this embodiment, the first probability distribution p (x, t) is used as initial channel probability density data acquired by the variable node to participate in iteration of the variable node and the check node. The first probability distribution p (x, t) is a joint probability distribution to which the transmitted signal x of the coded bits before transmission over the channel and the quantized values t after transmission over the channel and compression follow.

For the sake of the uniformity of the following notation, the above-described conditional probability distribution data p (t | y) output based on a channel (channel) can be denoted as p (t |)^chY), the first probability distribution p (x, t) based on the channel output can be denoted as p (x, t)^ch). And for convenience of description hereinafter, p (x, t) may be referred to^ch) Rephrased as p (x, y)^ch) It is to be understood that y^chThe representation is the quantized value of the coded bits corresponding to the received signal, i.e. the first probability distribution data.

In this embodiment, in S213, the variable node acquires the first probability distribution data and can transmit the first probability distribution data to the check node, so that the plurality of first probability distribution data transmitted from the plurality of variable nodes adjacent to the check node are determined as the first message.

In the mutual iteration process of the variable nodes and the check nodes, messages of a plurality of variable nodes are sent to corresponding check nodes, or messages of a plurality of check nodes are sent to corresponding variable nodes, the messages received by the check nodes or the variable nodes are determined according to the degree of the messages, such as the check nodes with one degree of 7, the received first message comprises first probability distribution data transmitted by a plurality of adjacent variable nodes, and the first probability distribution data, namely the quantized messages output by the variable nodes, can be expressed as

In this embodiment, the value of the check node degree or the variable node degree may be determined according to the regular LDPC code.

In this embodiment, the number of the first probability distribution data included in the first message transmitted from the variable node to the check node is determined according to the degree of the check node. After receiving the first message, the check node may iterate through step S22 in a table lookup manner according to the first message to obtain a corresponding second message. In the table query process, firstly, a table is preset, and corresponding output data is searched in the preset table according to input data of variable nodes or check nodes. In the embodiment of the application, the input data and the output data of the variable nodes and the check nodes are subjected to the joint probability distribution determined by the IB algorithm, so that the decoding performance is guaranteed, and meanwhile, the operation complexity of updating and iterating the variable nodes and the check nodes is reduced.

In a specific example, the decoder is in an initialization state, and has a preset signal-to-noise ratio, and the initial iteration number iter is 0; the value d of check node degree can be determined by the regular LDPC code_cAnd the value d of the degree of the variable node_v. Check node degree is the number of edges associated with check node CN and variable node degree is the number of edges associated with variable node VN.

It should be understood that, in the decoder, the check nodes and the variable nodes may construct a check matrix, which is a matrix including "0" and "1" elements and can be represented by a Tanner graph, in the check matrix, check nodes and variable nodes corresponding to elements other than "0" in rows and columns may be interconnected through edges, and there may not be a direct edge connection between the same kind of nodes. The check matrix and the interconnection relationship that the check nodes and the variable nodes can construct are well-known in the art and will not be described herein.

In order to reduce the operation complexity of the iteration of the check nodes and ensure the reliability of the iteration of the check nodes in a table query mode, in the embodiment of the application, a link formed by connecting target degree check nodes in series can be formed according to the degree distribution of the check nodes, based on the link, the check nodes are subjected to at least one forward algorithm table query and at least one backward algorithm table query according to a first preset table to obtain intermediate data and output data of each target degree check node, wherein the data transmitted to the variable nodes can be obtained according to the output data.

In a specific embodiment, the second message may include a plurality of second quantized messages, and S22 may specifically include S221 to S224:

s221, inquiring the first probability distribution data forward algorithm table at the check node according to the first preset table to obtain first forward probability distribution data of the first probability distribution data;

s222, according to the first preset table, carrying out backward algorithm table query on the first probability distribution data at the check node to obtain first backward probability distribution data of the first probability distribution data;

s223, determining second probability distribution data according to the first forward probability distribution data and the first backward probability distribution data;

s224 forms a second message according to the second probability distribution data.

In this embodiment, the manner of querying the check node Forward algorithm table and the check node Backward algorithm table according to the first preset table is a manner of querying the first preset table based on a Forward-Backward (FB) algorithm. The first preset table is a two-input lookup table, one output data is determined through two input data, and in the same table, the two input data and the corresponding output data obey the same joint probability distribution

In this embodiment, the variable node receives the initial probability density data of the channel output, i.e., the first probability distribution data, completes the initialization update, and sends the first probability distribution data as a first message to the check node associated therewith. The check node receives the first message transmitted from the neighboring variable node, which may be represented as

i＝0,1,…，d_c1, i represents the edges of the check nodes. First message

Obeying a joint probability distribution p (x, y)^v2c) X is the above-mentioned transmission signal, y^v2cIs a message that represents a message sent from a variable node to a check node. For the sake of convenience of illustration,

the joint probability distribution can be uniformly expressed as

Is composed of

Corresponding to the coded bits.

When the check node is updated, S221 is executed, according to the received first message, the first message is used as input data, and according to a mapping relationship between the input data and the output data configured in the first preset table, a forward algorithm table query is performed to obtain the external output data of the check node, that is, the first forward probability distribution data. Through S222, according to the first message and the first preset table, backward algorithm table query is performed on the check node, and first backward probability distribution data are obtained. In this embodiment, the message transmitted by each edge of the check node may generate an external output data by looking up a table, where the forward algorithm table query and the backward algorithm table query may generate the external output data corresponding to at least two edges. In S223-S224, the outgoing data of the check node may be used to form a second message, which is sent to the variable node. Because the same table is based on, one forward table look-up and one backward table look-up are carried out, and redundant table look-up operation is not needed in the middle, repeated table look-up on any edge can be avoided, and the calculation complexity of the check node is effectively reduced.

In a specific embodiment, the first probability distribution data in the first message is multiple, and the first forward probability distribution data obtained in S221 may include first intermediate data and first outgoing data. S221 may specifically include S2211 to S2213:

s2211 forms a first link in which a plurality of target-scale check nodes are connected in series according to the degree distribution of the check nodes.

According to the degree of the check node, the check node with a high degree can be split into a plurality of links in which the check nodes with a target degree are connected in series.

With d_cFor example, a check node of 7 degrees may be split into a first link of a series of 5 check nodes of 3 degrees, as shown in fig. 5. The target degree check node is a check node of a target degree obtained after a certain high-degree check node is split.

The plurality of destination-scale check nodes in the first link includes a head-end check node, an intermediate check node, and an end check node. As shown in fig. 5, the head check node, the intermediate check nodes, and the end check node are sequentially connected in series from left to right, and there may be a plurality of intermediate check nodes, that is, nodes located between the head check node and the end check node.

S2212 correspondingly inputs the plurality of first probability distribution data to the plurality of target degree check nodes, respectively.

In the first message, a plurality of first probability distribution data are transmitted from variable nodes adjacent to the check node, and the plurality of first probability distribution data are correspondingly input to the plurality of target scale check nodes on the first link according to the corresponding relation of the edges.

S2213 performs a forward algorithm table query on the first link according to the first preset table to obtain first intermediate data and first output data corresponding to the plurality of target degree check nodes.

Referring to FIG. 5, the first message received by the check node from 7 edges includes

Each message obeys the same probability density distribution. According to the forward algorithm table query mode, the input data of each intermediate check node in the first link includes the corresponding first probability distribution data, and also includes the forward message (i.e. the first intermediate data) of the previous node

F isAnd identifying the forward operation. Then forward message can be obtained after forward algorithm table query is performed sequentially from left to right

The first probability distribution data corresponding to the intermediate check node is

And the input data of the head end check node of the first link is first probability distribution data

The input data of the end target scale check node is first probability distribution data

The output data of the end target degree check node is first output data

Where "c 2 v" is used to indicate the identity sent from the check node to the variable node.

Specifically, S2213 may include:

according to first probability distribution data corresponding to the head end check node, performing forward algorithm table query according to a first preset table to obtain first intermediate data of the head end check node;

according to the first intermediate data of the head end check node and the first probability distribution data corresponding to the intermediate check nodes adjacent to the head end check node, carrying out forward algorithm table query according to a first preset table to obtain first intermediate data corresponding to the intermediate check nodes;

and carrying out forward algorithm table query according to a first preset table according to first intermediate data of intermediate check nodes adjacent to the tail end check node and first probability distribution data corresponding to the tail end check node to obtain first output data corresponding to the tail end check node.

Referring to FIG. 5, first

And

as the first probability distribution data corresponding to the head end check node in the link, the corresponding output value, that is, the first intermediate data of the head end check node, may be found based on the first preset table

Then from left to right, the head end checks the first intermediate data of the node

And first probability distribution data corresponding to intermediate check nodes adjacent to the head-end check node

Performing forward table query to obtain first intermediate data of intermediate check node adjacent to the head end check node

Sequentially looking up the table to the right to find out the first intermediate data corresponding to each intermediate check node

i is 1,2, 3. Finally, first intermediate data of intermediate check nodes adjacent to the end check node

And first probability distribution data corresponding to the end check node

Forward table look-up is carried out to obtain first output data corresponding to the end check node

In the first chain of the series, the relation between the two input data and the output data in the first preset table can be a function

Is represented by, i is 1,2,3 … d_c-3. Function(s)

In the first predetermined table, the function is a joint probability distribution function determined by IB algorithm

Where u and v refer to two input variables of the function, respectively, e.g.

Illustratively, the first probability distribution data is generated during configuration of the first predetermined table

Corresponding coded bit

Is a joint probability distribution of

i＝0,1,…，d_cObey the same joint probability distribution-1. If the function in the first preset table

Of an input message

Corresponding coded bits are

Function(s)

Output value of

Corresponding coded bits are

Then for a check node of degree 3, the coded bits corresponding to its input data and output message must satisfy the check relation, i.e. for the function

Satisfy the requirement of

From this, input messages

The joint probability distribution of (c) is:

in formula (2), a message is input

For combining messages, with quantization base | T-²The value of > T |. In order to make the event space size of the message generated based on the forward and backward table query and the IB algorithm (hereinafter, abbreviated as "FB-IB" algorithm) constant, the message may be combined using the IB algorithm

Compressed into a compressed form

In the process of constructing the first preset table, the joint probability distribution

And the quantization base | T | is input data of IB algorithm, and the output data of IB algorithm is deterministic mapping

Referring to the link in FIG. 5, the second degree of 3 objective degree check nodes function in the first predetermined table

Is configured in a manner similar to the first degree 3 target degree check node,

inputting messages

Corresponding joint probability distribution of

And

the specific calculation formula is similar to formula (2).

By analogy, relevant data of other target degree check nodes in the first preset table are configured, so that forward table query of the check nodes can be performed based on the first preset table, the operation complexity is low, and the method is suitable for deployment in hardware.

Correspondingly, the first backward probability distribution data obtained in S222 includes second intermediate data and second external output data, and S222 may specifically include S2221 to S2222:

s2221 correspondingly inputs the first probability distribution data into the target degree check nodes;

s2222 performs a backward algorithm table query on the first link according to the first preset table, to obtain second intermediate data and second external output data corresponding to the plurality of target degree check nodes.

And based on the same first link, carrying out backward algorithm table query on a plurality of target degree check nodes on the first link to obtain second intermediate data and second external output data.

Referring to FIG. 6, the first message received by the check node from 7 edges includes

Each message obeys the same probability density distribution. According to the table query mode of backward algorithm, the input of each intermediate check node in the first link comprises the corresponding first probability distribution data and also comprises the backward message of the next node

B is a backward operation identifier. Then after sequentially carrying out backward algorithm table query from right to left, obtaining backward messages

The input data of the end check node is a first probabilityDistributing data

And

the second external output data of the head end check node is

Referring to FIG. 6, it can be derived that the end check node (i.e. the target check node of the first lookup table in the backward algorithm table query) in the link inputs the message

Corresponding joint probability distribution of

And

first message

The joint probability distribution with the corresponding coded bits is

i＝0,1,…，d_c-1, obeying the same distribution.

And

as input to the IB algorithm, a deterministic mapping is obtained as

Therefore, for the tables used in the forward table lookup and backward table lookup of check nodes,

is a function of

Through the analysis, the intermediate results generated by the forward algorithm table query and the backward algorithm table query of the check node with the degree of 3 both satisfy probability symmetry, namely

i is 1,2,3, the joint probability distribution is the same. Therefore, the forward lookup table and the backward lookup table of the check node can multiplex the same first preset table.

In the backward table look-up decoding process of the check node, the second intermediate data obtained from right to left are

The second external output data obtained is

Firstly, the method

Then, the table is sequentially looked up from right to left, and the output value corresponding to each target degree check node can be sequentially looked up

i is 1,2, 3. Finally, the second external output data

In this embodiment, after S222, the method may further include:

according to a second preset table, performing table query on first intermediate data and/or second intermediate data of an intermediate check node in a first link to obtain first intermediate probability distribution data corresponding to the intermediate check node;

correspondingly, S223 may include:

the first extrinsic output data, the second extrinsic output data, and the first intermediate probability distribution data are used as second probability distribution data to form a second message.

Referring to fig. 7, still taking the serially connected first link constructed by the target degree check node of the above degree 3 as an example, the 0 th and 6 th edges have generated extrinsic information

And

only the outer information needs to be generated for the remaining edges. The specific calculation is as follows:

wherein,

and

some second preset tables may be used

Look-up tables to obtain, as foreign, information

The calculation of (2) requires other second preset tables to be found. It should be understood that the second preset table is one or more preset tables different from the first preset table, and the preset tables may be different.

Function for other second preset table

Having a joint probability distribution of

And

and symmetry of the message probability distribution, combining the messages

And

functions capable of reusing the same preset table

In the present embodiment, the degree d_cWhen the first intermediate probability distribution data of the intermediate check node is generated, the number of the additionally required second preset tables is

(d_cNot less than 3), wherein

Indicating rounding up.

Determining a function of the second preset table by means of the FB-IB algorithm

Then, the corresponding joint probability distribution is output

The p (x, y)^c2v) Input messages for iterations of the variable nodes may also be formed.

It can be understood that the external message obtained in the first link may be first external output data, second external output data, and first intermediate probability distribution data, each of which is taken as second probability distribution data, and as shown in fig. 5, 6, and 7, 7 corresponding second probability distribution data may be obtained and sent to the adjacent variable node.

From the above, the number of table lookup times required for the check nodes based on the forward and backward algorithm table query is 3 (d)_c-2), and if the IB algorithm operation is performed based on a conventional check matrix (non-serial link structure), one degree d_cCheck node of (2) requires d_c(d_c-2) a table look-up operation. Therefore, by the method of the embodiment of the application, the number of times of table lookup during updating of the check node can be reduced from the square magnitude of degrees to the linear magnitude. Obviously, the larger the number of check nodes is, the more considerable the number of reduced table lookup times is, so that the decoding efficiency can be greatly improved for a high-code-rate LDPC code decoding scene.

In some embodiments, the iterated output message is updated for the check node, that is, the second message includes second probability distribution data corresponding to a plurality of target degree variable nodes, that is, the variable node receives the second probability distribution data sent by the adjacent check node, and according to the iteration of the second message, the variable node may perform a forward algorithm table query and a backward algorithm table query, thereby obtaining a third message.

In this embodiment, S24 may specifically include S241 to S244:

s241, forward algorithm table query is carried out on the second probability distribution data at the variable nodes according to a third preset table to obtain second forward probability distribution data of the second probability distribution data;

s242, according to a third preset table, carrying out backward algorithm table query on the second probability distribution data at the variable nodes to obtain second backward probability distribution data of the second probability distribution data;

s243 determining third probability distribution data according to the second forward probability distribution data and the second backward probability distribution data;

s244 forms a third message based on the third probability distribution data.

In this embodiment, the variable node Forward algorithm table query and the variable node Backward algorithm table query are performed according to the third preset table, and the table query is performed on the third preset table based on a Forward-Backward (FB) algorithm. The third preset table is also a two-input lookup table, one output data is determined through two input data, and in the same table, the two input data and the corresponding output data obey the same joint probability distribution.

When the variable node is updated, S241 is executed, according to the received second message, the second message is used as input data, and according to the mapping relationship between the input data and the output data configured in the third preset table, a forward algorithm table query is performed to obtain the output data of the variable node, that is, the second forward probability distribution data. And through S242, carrying out backward algorithm table query on the variable nodes according to the second message and the third preset table to obtain second backward probability distribution data. In this embodiment, each edge of the variable node generates an outgoing data, the forward lookup table and the backward lookup table may generate outgoing data corresponding to at least two edges, and in S243 to S244, the outgoing data of the variable node is used as third probability distribution data, may form a third message, and is sent to the check node or used for decoding calculation. Because the same table is used for carrying out forward table look-up and backward table look-up once, and redundant table look-up operation is not needed in the middle, repeated table look-up on any edge can be avoided, and the calculation complexity of the variable node is effectively reduced.

In a specific embodiment, the second message includes second probability distribution data corresponding to a plurality of target degree variable nodes, the data being a plurality of, and the second forward probability distribution data includes third intermediate data and third outgoing data. S241 may specifically include S2411 to S2413:

s2411 forming a second link formed by connecting a plurality of target-scale variable nodes in series according to the degree distribution of the variable nodes.

S2412, correspondingly inputting the plurality of second probability distribution data into a plurality of target degree variable nodes respectively;

s2413 performs forward algorithm table query on the second link according to the third preset table to obtain third intermediate data and third output data corresponding to the multiple target degree variable nodes.

Referring to fig. 8, a variable node of one degree 5 is split into 4 second links of 3 degrees, where a plurality of target degree variable nodes in the links include a head variable node, an intermediate variable node, and a variable check node. The second message received by the variable node from the check node is

Each message is a joint probability distribution p (x, y) obtained at the check nodes^c2v) The quantized value of (a). The variable node also includes the first probability distribution data corresponding to the received signal of the channel output, i.e. the message of the channel output

Has a probability distribution of p (x, y)^ch). Referring to the second link shown in fig. 8, the input data of each target degree variable node includes the second probability distribution data and may include the forward message of the previous node in addition to the second probability distribution data according to the forward algorithm table query manner

F is the forward operation identification. Then forward messages are obtained after forward algorithm table query from left to right in sequence

The second probability distribution data corresponding to the intermediate variable nodes is

And the input data of the intermediate variable node closest to the middle part of the link in the second link is the message output by the channel

The input data of the head end variable node of the second link comprises

And

the input data of the end variable node comprises

And the output data is the fourth external output data

Where "v 2 c" is used to indicate the identity sent from the variable node to the check node.

Specifically, S2413 may include:

according to second probability distribution data corresponding to the head end variable node, forward algorithm table query is carried out according to a third preset table, and third intermediate data of the head end variable node are obtained;

performing forward algorithm table query according to a third preset table according to third intermediate data of the head end variable node and second probability distribution data and/or first probability distribution data corresponding to intermediate variable nodes adjacent to the head end variable node to obtain third intermediate data corresponding to the intermediate variable nodes;

and carrying out forward algorithm table query according to a third preset table according to third intermediate data of intermediate variable nodes adjacent to the tail end variable node and second probability distribution data corresponding to the tail end variable node to obtain third output data corresponding to the tail end variable node.

Referring to FIG. 8, first

And

as the second probability distribution data corresponding to the head end variable node in the second link, the corresponding output value, that is, the second intermediate data of the head end variable node may be found based on the third preset table

Then from left to right, second intermediate data of the head end variable node

And messages corresponding to intermediate variable nodes adjacent to the head variable node

Performing forward table query to obtain second intermediate data of intermediate variable node adjacent to the head variable node

Sequentially looking up the table to the right to find out the first intermediate data corresponding to each intermediate variable node

i is 1,2, 3. Finally, second intermediate data of intermediate variable nodes adjacent to the end variable node

And second probability distribution data corresponding to the end variable node

Forward looking up table to obtain the third output data corresponding to the end variable node

Wherein, due to

With second probability distribution data from check nodes

Are not the same, so if

If the placement position is not reasonable, the forward and backward operations of the variable nodes cannot reuse the same table. Therefore, in the embodiment of the present application, the

As an external input to a node in the second link closest to the middle position, so that the probability distribution of the quantized message generated in the forward-backward process is symmetrical. For even degree variable nodes, only the node is required to be connected

As the edge at the very middle, i.e. (d) th_vAnd/2) input data of edges.

For the odd-degree variable node,

the setting method comprises the following steps: look-up of a table in a forward algorithmIn the process of the inquiry, the user can inquire the information,

as the second ((d)_v-1)/2) inputs on the edges; and in the backward algorithmic table look-up process,

as the second ((d)_v+1)/2) edges. Fig. 8 shows a schematic diagram of performing forward algorithm table query on the second link corresponding to the variable node with the degree of 5, and fig. 9 shows a schematic diagram of performing backward algorithm table query on the second link corresponding to the variable node with the degree of 5.

It should be understood that the principle of the variable node performing the forward algorithm table query based on the third preset table is similar to the principle of the check node performing the forward algorithm table query, and the details are not repeated here.

In this embodiment of the application, the second backward probability distribution data obtained in S242 includes fourth intermediate data and fourth external output data, and based on a principle similar to backward algorithm table query performed on check nodes, S242 may specifically include S2421 to S2422:

s2421, correspondingly inputting the second probability distribution data into a plurality of objective variable nodes respectively;

s2422, according to the third preset table, backward algorithm table query is conducted on the second link, and fourth intermediate data and fourth external output data corresponding to the multiple target degree variable nodes are obtained.

In the embodiment of the application, when the variable nodes are subjected to backward algorithm table query, the variable nodes receive the messages from the check nodes as

Quantized messages from the channel on the variable nodes are

Referring to the example shown in fig. 9, the variable node performs backward algorithm table query according to a third preset table to obtain the output data

Specifically, S2422 may include:

according to second probability distribution data corresponding to the terminal variable nodes, carrying out backward algorithm table query according to a third preset table to obtain four intermediate data of the terminal variable nodes;

according to the fourth intermediate data of the tail end variable node and the second probability distribution data and/or the first probability distribution data corresponding to the intermediate variable nodes adjacent to the tail end variable node, carrying out backward algorithm table query according to a third preset table to obtain fourth intermediate data corresponding to the intermediate variable nodes;

and according to fourth intermediate data of the intermediate variable nodes adjacent to the head end variable node and second probability distribution data corresponding to the head end variable node, carrying out backward algorithm table query according to a third preset table to obtain fourth external output data corresponding to the head end variable node.

It should be understood that the principle of the variable node performing the backward algorithm table query based on the third preset table is similar to the principle of the check node performing the backward algorithm table query, and the details are not repeated here. And the principle that the variable node performs table lookup calculation on the outbound data of the intermediate variable node in the second link based on the fourth preset table is similar to the principle that the check node performs table lookup calculation on the outbound data of the intermediate check node based on the second preset table, and details are not repeated here.

And after the third external output data, the fourth external output data and the external output data of the intermediate variable node are obtained, the third external output data, the fourth external output data and the external output data of the intermediate variable node are used as third probability distribution data to form a third message.

In the embodiment of the application, the degree d is calculated based on the forward and backward table lookup_vVariable node, the number of table lookup required is 3 (d)_v-1), the number of look-up tables required for additional intermediate variable nodes is [ (d)_v-4)/2]. Thus making it easy to useBy the method, the number of table lookup times during variable node updating can be reduced from the square magnitude of degree to the linear magnitude. Obviously, the larger the degree of the variable node is, the more considerable the reduced table look-up times are, so that the decoding efficiency can be greatly improved for the decoding scene of the high-code-rate LDPC code.

In this embodiment of the application, after the variable node obtains the third message, in S25, a hard decision may be made based on the third message according to whether the third message satisfies a preset target condition. In a specific embodiment, S25 may include:

if the iteration times corresponding to the third message exceed the preset maximum iteration times, the iteration is finished;

and performing decoding calculation by using the third probability distribution data included in the third message, and determining a decoding result according to the calculation result if the obtained calculation result is 0 or 1.

A specific example is that the highest bit of the third probability distribution data in the third message is taken to perform an exclusive or operation with the check matrix, and the obtained result is used to determine whether decoding is finished or whether original data is obtained. For example, if the result of the xor operation is all 0 s, the coded bits are correct original data, if the result is not 0 s, the coded bits are incorrect original data, and if the coded bits are incorrect original data, the iterative operation may be selected to continue, or the termination operation may be selected to end.

In this embodiment, if the third message does not satisfy the preset target condition, the method may further include:

s26, when the third message does not meet the preset target condition, the third message is used as input data of a check node, and table query is carried out on the check node to obtain an updated second message;

s27, transmitting the updated second message from the check node to the variable node;

s28, according to the updated second message, performing table query on the variable node to obtain an updated third message;

and S29, when the updated third message meets the preset target condition, decoding the received signal according to the updated third message to obtain a decoding result.

And when the third message does not meet the preset target condition, the third message is used as input data of the check node, and the check node is iterated to obtain an updated second message. And sending the second message to a variable node iteration to obtain an updated third message, and judging the third message again until the message obtained by the variable node iteration meets a preset target condition to obtain a decoding result.

In this embodiment of the application, the preset target condition may be greater than or equal to a preset maximum number of iterations, that is, iter is greater than or equal to max _ iter, but is not limited to this, and the preset target condition may also be a threshold value of an external output message (e.g., a third message) of the variable node.

In the embodiment of the application, table query based on the forward and backward algorithm and table configuration based on the IB algorithm enable the operation complexity of variable nodes and check nodes to be greatly reduced in the decoding process, repeated table lookup times are avoided, and the decoding efficiency can be improved while the decoding performance is guaranteed.

The decoding method according to the embodiment of the present application is described in detail above with reference to fig. 2 to 9, and the decoding apparatus according to the embodiment of the present application is described in detail below with reference to fig. 7.

As shown in fig. 10, the decoding apparatus 1000 includes:

a first obtaining module 1001 configured to obtain a first message, where the first message includes first probability distribution data of coded bits;

a second query module 1002, configured to perform table query on the check node according to the first message to obtain a second message, where the second message includes second probability distribution data of the first probability distribution data;

a first transmission module 1003 for transmitting the second message from the check node to the variable node;

a second query module 1004, configured to perform table query on the variable node according to the second message to obtain a third message, where the third message includes third probability distribution data of the second probability distribution data;

the decoding module 1005 is configured to perform decoding calculation on the coded bits according to the third message when the third message meets the preset target condition, so as to obtain a decoding result.

The apparatus in this embodiment of the present application obtains a first message, where the first message includes first probability distribution data of coded bits; and performing table query on the check node according to the first message to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data, and the message output by the check node is obtained in a table lookup manner, so that the operation complexity of the check node can be reduced when the check node is updated, and the decoding efficiency is improved. And transmitting the obtained second message to the variable node, and performing table query on the variable node according to the second message to obtain a third message, wherein the third message comprises third probability distribution data of the second probability distribution data. Therefore, the operation complexity of updating the variable nodes is reduced based on a table look-up mode when the variable nodes are updated; if the obtained third message meets the preset target condition, the coded bits can be decoded according to the message, and a decoding result is obtained. Therefore, the embodiment of the application can determine the output information of each node through table query of the check nodes and the variable nodes so as to complete the update of the nodes, and compared with the traditional calculation method, the method has the advantages that the operation complexity is reduced, and the decoding efficiency is improved.

In one embodiment, the first message includes a plurality of first quantization messages, and the first obtaining module specifically includes:

the setting submodule is used for setting first joint probability distribution data of the coded bits and the quantization base numbers of the coded bits, and the first joint probability distribution data are used for setting probability distribution obeyed by the coded bits after being output through a channel;

the first operation submodule is used for operating the first joint probability distribution data and the quantization base number according to a preset algorithm to obtain first probability distribution data of the coded bits;

a first determining submodule, configured to determine the first probability distribution data as a first message.

In this embodiment, the first probability distribution data is a quantized value of the coded bit satisfying a predetermined conditional probability distribution,

the preset conditional probability distribution is used for representing the mapping relation between the coded bits and the quantized values of the coded bits when mutual information is maximized, and the mutual information is the information content of the coded bits contained in the quantized values.

In one embodiment, the first query module may include:

the first query submodule is used for performing table query of a forward algorithm on the first probability distribution data at the check node according to a first preset table to obtain first forward probability distribution data of the first probability distribution data;

the second query submodule is used for carrying out backward algorithm table query on the first probability distribution data at the check node according to the first preset table to obtain first backward probability distribution data of the first probability distribution data;

a second determining submodule, configured to determine second probability distribution data according to the first forward probability distribution data and the first backward probability distribution data;

and the first forming submodule is used for forming a second message according to the second probability distribution data.

In one embodiment, the first probability distribution data is a plurality of, the first forward probability distribution data includes first intermediate data and first output data, and the first query submodule includes:

a first forming unit configured to form a first link in which a plurality of target-scale check nodes are connected in series according to degree distribution of the check nodes;

the first input unit is used for correspondingly inputting the first probability distribution data into the target degree check nodes;

and the first query unit is used for performing table query of a forward algorithm on the first link according to the first preset table to obtain first intermediate data and first output data corresponding to the plurality of target degree check nodes.

In one embodiment, the plurality of destination-scale check nodes in the first link include a head-end check node, an intermediate check node, and an end check node, and the first query unit may include:

the first query subunit is configured to perform forward algorithm table query according to a first preset table according to first probability distribution data corresponding to the head end check node, so as to obtain first intermediate data of the head end check node;

the second query subunit is configured to perform table query of a forward algorithm according to the first intermediate data of the head-end check node and the first probability distribution data corresponding to the intermediate check node adjacent to the head-end check node, and obtain first intermediate data corresponding to the intermediate check node;

and the third query subunit is used for performing forward algorithm table query according to the first intermediate data of the intermediate check node adjacent to the tail end check node and the first probability distribution data corresponding to the tail end check node and the first preset table to obtain first output data corresponding to the tail end check node.

In one embodiment, the first backward probability distribution data includes second intermediate data and second external output data, and the second query submodule may specifically include:

the second input unit is used for correspondingly inputting the first probability distribution data values into a plurality of target scale check nodes respectively;

and the second query unit is used for performing backward algorithm table query on the first link according to the first preset table to obtain second intermediate data and second external output data corresponding to the plurality of target degree check nodes.

In one embodiment, the second query unit may include:

the fourth query subunit is used for performing backward algorithm table query according to the first probability distribution data corresponding to the terminal check node and the first preset table to obtain second intermediate data of the terminal check node;

the fifth query subunit is configured to perform backward algorithm table query according to the first preset table and the second intermediate data of the end check node and the first probability distribution data corresponding to the intermediate check node adjacent to the end check node, so as to obtain second intermediate data corresponding to the intermediate check node;

and the sixth query subunit is configured to perform backward algorithm table query according to the first preset table according to the second intermediate data of the intermediate check node adjacent to the head end check node and the first probability distribution data corresponding to the head end check node, so as to obtain second external output data corresponding to the head end check node.

In one embodiment, the first query module may further include:

the third query submodule is used for performing table query on the first intermediate data and/or the second intermediate data of the intermediate check node in the first link according to a second preset table to obtain first intermediate probability distribution data corresponding to the intermediate check node;

the second determination submodule may be specifically configured to:

and determining the first external output data, the second external output data and the first intermediate probability distribution data as third probability distribution data.

In one embodiment, the second query module may include:

the fourth query submodule is used for performing forward algorithm table query on the second probability distribution data at the variable node according to the third preset table to obtain second forward probability distribution data of the second probability distribution data;

the fifth query submodule is used for performing backward algorithm table query on the second probability distribution data at the variable nodes according to a third preset table to obtain second backward probability distribution data of the second probability distribution data;

a third determining submodule, configured to determine third probability distribution data according to the second forward probability distribution data and the second backward probability distribution data;

and the second forming submodule is used for forming a third message according to the third probability distribution data.

In one embodiment, the second message includes second probability distribution data corresponding to a plurality of target degree variable nodes, the plurality of values being a plurality, the second forward probability distribution data includes third intermediate data and third output data, and the fourth query submodule may include:

a second forming unit for forming a second link in series of a plurality of target-scale variable nodes according to the degree distribution of the variable nodes;

a third input unit, configured to correspondingly input the plurality of second probability distribution data into a plurality of target degree variable nodes, respectively;

and the third query unit is used for performing forward algorithm table query on the second link according to a third preset table to obtain third intermediate data and third output data corresponding to the multiple target degree variable nodes.

In one embodiment, the plurality of objective degree variable nodes in the second link include a head end variable node, an intermediate variable node, and an end variable node, and the third query unit may include:

the seventh query subunit is configured to perform forward algorithm table query according to the third preset table and the second probability distribution data corresponding to the head end variable node, so as to obtain third intermediate data of the head end variable node;

the eighth query subunit is configured to perform forward algorithm table query according to a third preset table according to the third intermediate data of the head-end variable node and the second probability distribution data and/or the first probability distribution data corresponding to the intermediate variable node adjacent to the head-end variable node, so as to obtain third intermediate data corresponding to the intermediate variable node;

and the ninth query subunit is configured to perform forward algorithm table query according to a third preset table and according to third intermediate data of an intermediate variable node adjacent to the end variable node and second probability distribution data corresponding to the end variable node, to obtain third output data corresponding to the end variable node.

In one embodiment, the second backward probability distribution data includes fourth intermediate data and fourth outer output data, and the fifth query submodule may include:

a fourth input unit, configured to correspondingly input the plurality of second probability distribution data into the plurality of target degree variable nodes, respectively;

and the fourth query unit is used for performing backward algorithm table query on the second link according to the third preset table to obtain fourth intermediate data and fourth external output data corresponding to the multiple target degree variable nodes.

In one embodiment, the fourth query unit may include:

the tenth query subunit is configured to perform backward algorithm table query according to the third preset table and the second probability distribution data corresponding to the terminal variable node, so as to obtain fourth intermediate data of the terminal variable node;

the eleventh query subunit is configured to perform backward algorithm table query according to a third preset table according to fourth intermediate data of the end variable node and second probability distribution data and/or first probability distribution data corresponding to intermediate variable nodes adjacent to the end variable node, so as to obtain fourth intermediate data corresponding to the intermediate variable node;

and the twelfth query subunit is configured to perform backward algorithm table query according to the third preset table according to the fourth intermediate data of the intermediate variable node adjacent to the head-end variable node and the second probability distribution data corresponding to the head-end variable node, so as to obtain fourth external output data corresponding to the head-end variable node.

In some embodiments, the second query module may further include:

the sixth query submodule is configured to perform table query on third intermediate data and/or fourth intermediate data of an intermediate variable node in the second link according to a fourth preset table to obtain second intermediate probability distribution data corresponding to the intermediate variable node;

the fourth determination submodule may be specifically configured to:

and determining the third and fourth outer output data and the second intermediate probability distribution data as third probability distribution data to form a third message.

In the embodiment of the application, the first preset table and the third preset table are both two input lookup tables, and one output data is determined through the two input data;

wherein the two input data and the one output data satisfy the same joint probability distribution condition as the first message.

It should be noted that all relevant contents of each step related to the above method embodiment may be referred to the functional description of the corresponding functional module, and the corresponding technical effect can be achieved, and for brevity, no further description is provided herein.

Fig. 11 is a diagram showing a hardware configuration of a computer apparatus according to an embodiment.

As shown in fig. 11, the computer device 1100 includes an input device 1101, an input interface 1102, a processor 1103, a memory 1104, an output interface 1105, and an output device 1106.

The input interface 1102, the processor 1103, the memory 1104, and the output interface 1105 are connected to each other via a bus 1110, and the input device 1101 and the output device 1106 are connected to the bus 1110 via the input interface 1102 and the output interface 1105, respectively, and further connected to other components of the computer device 1100. Specifically, the input device 1101 receives input information from the outside and transmits the input information to the processor 1103 through the input interface 1102; the processor 1103 processes the input information based on the computer-executable instructions stored in the memory 1104 to generate output information, stores the output information temporarily or permanently in the memory 1104, and then transmits the output information to the output device 1106 through the output interface 1105; the output device 1106 outputs output information to the exterior of the computer device 1100 for use by a user.

In one embodiment, the computer device 1100 shown in FIG. 11 may be implemented as a transcoding device that may include: a memory configured to store a program; a processor configured to execute the program stored in the memory to perform the decoding method described in the above embodiments.

In one embodiment, the memory may be further configured to store target task results of the task stream and processing results of each step in the decoding process described in conjunction with fig. 1-9 above. As an example, the processing result includes at least: executing a logical operation instruction on the task flow, and executing scheduling information of at least two operator nodes of the logical operation instruction.

According to an embodiment of the present application, the process described above with reference to the flowchart may be implemented as a computer-readable storage medium. For example, embodiments of the present application include a computer-readable storage medium comprising a program or instructions stored thereon, which, if executed by a computer device, cause the computer device to perform the steps of the above-described method.

According to an embodiment of the application, the process described above with reference to the flow chart may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network, and/or installed from a removable storage medium.

In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions which, when run on a computer, cause the computer to perform the methods described in the various embodiments above. The procedures or functions according to the embodiments of the present application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wirelessly (e.g., infrared, wireless, microwave, etc.). Computer-readable storage media can be any available media that can be accessed by a computer or a data storage device, such as a server, data center, etc., that includes one or more available media. The available media may be magnetic media (e.g., floppy disk, hard disk, magnetic tape), optical media (e.g., DVD), or semiconductor media (e.g., solid state disk), among others. .

Moreover, an embodiment of the present application further provides a chip, where the chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is configured to execute a program or an instruction to implement each process of the decoding method embodiment, and the same technical effect can be achieved.

It should be understood that the chips mentioned in the embodiments of the present application may also be referred to as system-on-chip, system-on-chip or system-on-chip, etc.

It is to be understood that the present application is not limited to the particular arrangements and instrumentality described above and shown in the attached drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions, or change the order between the steps, after comprehending the spirit of the present application.

The functional blocks shown in the above structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the present application are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.

It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.

Aspects of the present application are described above with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions/acts specified in the flowchart and/or block diagram block or blocks. Such a processor may be, but is not limited to, a general purpose processor, a special purpose processor, an application specific processor, or a field programmable logic circuit. It will also be understood that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware for performing the specified functions or acts, or combinations of special purpose hardware and computer instructions.

As described above, only the specific embodiments of the present application are provided, and it can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present application, and these modifications or substitutions should be covered within the scope of the present application.

Claims

1. A method of decoding, comprising:

according to the first message, performing table query on a check node to obtain a second message, wherein the second message comprises second probability distribution data of the first probability distribution data;

transmitting the second message from the check node to a variable node;

and when the third message meets a preset target condition, carrying out decoding calculation on the coded bits according to the third message to obtain a decoding result.

2. The method of claim 1, wherein after the obtaining the third message, the method further comprises:

when the third message does not meet the preset target condition, the third message is used as input data of the check node, and table query is performed on the check node to obtain an updated second message;

transmitting the updated second message from the check node to the variable node;

according to the updated second message, performing table query on the variable node to obtain an updated third message;

and when the updated third message meets the preset target condition, performing decoding calculation on the coded bits according to the updated third message to obtain a decoding result.

3. The method of claim 1, wherein the obtaining the first message comprises:

setting first joint probability distribution data of the coded bits and a quantization base number of the coded bits, wherein the first joint probability distribution data are used for setting probability distribution obeyed by the coded bits after being output through a channel;

according to a preset algorithm, calculating the first joint probability distribution data and the quantization base number to obtain the first probability distribution data corresponding to the coding bits;

determining the first probability distribution data as the first message.

4. The method of claim 3, wherein the first probability distribution data is a quantized value of the coded bit when a preset conditional probability distribution is satisfied;

the preset conditional probability distribution is used for representing a mapping relation between the coded bits and quantized values of the coded bits when mutual information is maximized, and the mutual information is information quantity of the coded bits contained in the quantized values.

5. The method of claim 1, wherein the performing a table lookup at a check node according to the first message to obtain a second message comprises:

according to a first preset table, performing forward algorithm table query on the first probability distribution data at the check node to obtain first forward probability distribution data of the first probability distribution data;

according to the first preset table, carrying out backward algorithm table query on the first probability distribution data at the check node to obtain first backward probability distribution data of the first probability distribution data;

determining the second probability distribution data according to the first forward probability distribution data and the first backward probability distribution data;

and forming a second message according to the second probability distribution data.

6. The method of claim 5, wherein the first probability distribution data is plural, the first forward probability distribution data including first intermediate data and first outer output data; the method for performing table query of a forward algorithm on the first probability distribution data at the check node according to a first preset table to obtain first forward probability distribution data of the first probability distribution data includes:

forming a first link formed by connecting the plurality of target scale check nodes in series according to the degree distribution of the check nodes;

correspondingly inputting the first probability distribution data into the target scale check nodes respectively;

and performing table query of a forward algorithm on the first link according to a first preset table to obtain first intermediate data and first output data corresponding to the plurality of target degree check nodes.

7. The method of claim 6, wherein the first backward probability distribution data comprises second intermediate data and second extrinsic output data; the performing, at the check node according to the first preset table, a backward algorithm table query on the first probability distribution data to obtain first vector probability distribution data of the first probability distribution data includes:

and according to a first preset table, carrying out backward algorithm table query on the first link to obtain second intermediate data and second external output data corresponding to the plurality of target degree check nodes.

8. The method of claim 1, wherein performing a table lookup at the variable node according to the second message to obtain a third message comprises:

according to a third preset table, performing forward algorithm table query on the second probability distribution data at the variable nodes to obtain second forward probability distribution data of the second probability distribution data;

according to the third preset table, performing backward algorithm table query on the second probability distribution data at the variable nodes to obtain second backward probability distribution data of the second probability distribution data;

determining the third probability distribution data according to the second forward probability distribution data and the second backward probability distribution data;

and forming the third message according to the third probability distribution data.

9. The method of claim 8, wherein there are a plurality of said second probability distribution data, said second forward probability distribution data including third intermediate data and third outgoing data; performing forward algorithm table query on the second probability distribution data at the variable node according to a third preset table to obtain second forward probability distribution data of the second probability distribution data, including:

forming a second link formed by connecting the plurality of target-scale variable nodes in series according to the degree distribution of the variable nodes;

correspondingly inputting a plurality of second probability distribution data into the plurality of target scale variable nodes respectively;

and performing table query of a forward algorithm on the second link according to a third preset table to obtain third intermediate data and third output data corresponding to the multiple target degree variable nodes.

10. The method of claim 9, wherein the second backward probability distribution data comprises fourth intermediate data and fourth outer output data; the performing, at the variable node, a backward algorithm table query on the second probability distribution data according to the third preset table to obtain second backward probability distribution data of the second probability distribution data includes:

and according to a third preset table, carrying out backward algorithm table query on the second link to obtain fourth intermediate data and fourth external output data corresponding to the multiple target degree variable nodes.

11. A coding device, the device comprising:

a first obtaining module to obtain a first message comprising first probability distribution data of coded bits;

a second query module, configured to perform table query on a check node according to the first message to obtain a second message, where the second message includes second probability distribution data of the first probability distribution data;

a first transmission module for transmitting the second message from the check node to a variable node;

a second query module, configured to perform table query on the variable node according to the second message to obtain a third message, where the third message includes third probability distribution data of the second probability distribution data;

and the decoding module is used for performing decoding calculation on the coded bits according to the third message under the condition that the third message meets a preset target condition to obtain a decoding result.

12. A computer device, comprising: a memory and a processor, wherein the processor is capable of,

the memory for storing a computer program;

the processor is configured to execute a computer program stored in the memory, the computer program when executed causes the processor to perform the steps of the decoding method according to any one of claims 1 to 10.

13. A computer readable storage medium having stored thereon a program or instructions which, when executed by a computer device, causes the computer device to perform the steps of the decoding method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program which, if executed by a computer device, causes the computer device to carry out the steps of the transcoding method as claimed in any of claims 1 to 10.