CN115642918A

CN115642918A - Encoding optimization method, device and equipment of double-prototype-graph LDPC code and storage medium

Info

Publication number: CN115642918A
Application number: CN202210991594.1A
Authority: CN
Inventors: 陈启望; 肖宏玲
Original assignee: Huaqiao University
Current assignee: Huaqiao University
Priority date: 2022-08-18
Filing date: 2022-08-18
Publication date: 2023-01-24

Abstract

The invention provides a method, a device, equipment and a storage medium for encoding optimization of a double-protograph LDPC code, wherein the method comprises the following steps: constructing a multiple connection basis matrix and optimizing the multiple connection basis matrix; providing a group of joint coding basic matrixes based on double-prototype LDPC codes, replacing the single-side connection basic matrixes of the joint coding basic matrixes with the optimized multiple connection basic matrixes, and generating joint coding matrixes; expanding each part of the joint coding matrix to generate a channel coding matrix and a connection matrix with a preset size; carrying out source coding on a given original source bit to generate source compression information; and performing generalized coding on the joint coding matrix according to the source compression information, the channel coding matrix and a connection matrix with a preset size, and aiming at increasing the possibility that source redundant information and channel state information can be fully utilized.

Description

Encoding optimization method, device and equipment of double-prototype-graph LDPC code and storage medium

Technical Field

The invention relates to the field of computers, in particular to a method, a device, equipment and a storage medium for encoding optimization of double-prototype LDPC codes.

Background

The goal of the joint source-channel coding scheme is to exploit the source redundancy and channel state information to improve the overall system performance over the traditional separate source or channel coding scheme. A Joint coding system consisting of two LDPC codes, one for source compression and the other for channel error control, is proposed by m.fresia et al in "Joint source and channel coding" [ IEEE Signal Processing Magazine,2010,27 (6): 103-114 ], called a dual LDPC coding system. Compared with a separated LDPC coding system, the core of the double LDPC coding structure is to introduce a connection matrix so as to establish the relation between two LDPC codes. At a decoding end, a joint belief propagation decoding algorithm can iteratively exchange information source redundancy and channel state information through the connection matrix to improve the system performance.

The specific structure and coding algorithm are described as follows:

a joint source channel coding based on dual LDPC codes may be represented by a joint matrix,

wherein H _S Is of size M _s ×N _s Source coding matrix of H _C Is of size M _s ×N _s Of the channel coding matrix, H _L1 Is of size M _s ×N _C Is a connection matrix of the first type, H _L2 Is of size M _C ×N _S Is a second type of connection matrix. In addition H _L1 Composed of a zero matrix 0 and an identity matrix H _I Thereby forming the structure. This identity matrix means that the check nodes of the source are in one-to-one correspondence with the variable nodes.

Has a group of lengths N _s Statistical property of (p) ₀ ，p ₁ ) Original source bit s, (1) obtaining a group of compressed bit sequences c through calculation of a source coding matrix, namely

Wherein (·) ^T Transpose operations for matrices; (2) Splicing s and c to obtain a new bit sequence sc](ii) a (3) Splicing H _L2 And H _C To obtain [ H ] _L2 H _C ]After Gaussian elimination, a form of [ I ] can be obtained _C G _C ]A generator matrix in the form of a system of (1); (4) [ sc ] of]Is subjected to channel coding G _C To obtain a group of check bit sequences p, i.e. p = [ sc = [ c ]]·G _C . Therefore, the whole encoding process can be summarized as

Wherein u = [ scp ]]。

After deleting the original source bit s in the codeword u, [ cp ]]Modulated into the channel. At a receiving end, initializing a variable node corresponding to s by using the information source statistical characteristics, initializing variable nodes corresponding to c and p by using channel information, and then performing iterative decoding by using a Belief Propagation (BP) algorithm. After several iterations, if obtained

Satisfy the requirement of

Or stopping iteration when the iteration times reach the preset maximum value, and extracting

In (1)

As estimated raw bit information. Here H _L2 May be a zero matrix.

As mentioned above, the first type of connection matrix is used to connect the source coding matrix and the channel coding matrix, so as to exchange the source redundancy and channel state decoding information. Then through H _I The single connection relation of (2) may not make full use of the decoded information.

In view of this, the present application is proposed.

Disclosure of Invention

The invention discloses a coding optimization method, a coding optimization device, coding optimization equipment and a storage medium of a double-protograph LDPC code, and aims to increase the possibility that information source redundant information and channel state information can be fully utilized.

The first embodiment of the present invention provides a method for encoding and optimizing a double-primitive-pattern LDPC code, including:

constructing a multiple connection basis matrix and optimizing the multiple connection basis matrix;

providing a group of joint coding basic matrixes based on double-prototype LDPC codes, replacing the single-side connection basic matrixes of the joint coding basic matrixes with the optimized multiple connection basic matrixes, and generating joint coding matrixes;

expanding each part of the joint coding matrix to generate a channel coding matrix and a connection matrix with a preset size;

carrying out source coding on given original source bits to generate source compression information;

and carrying out generalized coding on the joint coding matrix according to the information source compression information, the channel coding matrix and the connection matrix with the preset size.

Preferably, each part of the joint coding matrix is expanded, and a source coding matrix and a multiple connection coding matrix are further generated;

wherein the source coding matrix, the multiple connection coding matrix, the channel coding matrix, and the connection matrix of a predetermined size are used to be spliced into a joint coding matrix at a receiving end.

Preferably, the constructing a multiple connection basis matrix and optimizing the multiple connection basis matrix specifically include:

s1, giving a unit matrix, carrying out elementary transformation operation on the unit matrix, and generating multiple connection basic matrixes with different structures according to the operation;

s2, initializing variance values of different variable nodes of the multiple connection basic matrix according to information source statistical characteristics and signal-to-noise ratios;

s3, calling a traditional combined external information transfer algorithm, and iteratively updating information transfer of the variable nodes and the check nodes until mutual information of the variable nodes is equal to 1 or the maximum iteration times is reached;

s4, changing an initial signal-to-noise ratio, and repeating S2 and S3 until a minimum signal-to-noise ratio is found, so that mutual information of variable nodes is equal to 1;

and S5, changing the multiple connection basis matrix, repeating the S2, the S3 and the S4, and finding the multiple connection basis matrix with the minimum signal-to-noise ratio.

Preferably, the generalized encoding of the joint coding matrix according to the source compression information, the channel coding matrix and the connection matrix with a predetermined size is specifically:

performing multiple connection coding on the information source compression information to generate multiple coding information;

splicing the multiple coding information and the original information source bit to generate a new bit sequence;

splicing the channel coding matrix and the connection matrix with the preset size to generate a splicing result, and performing Gaussian elimination on the splicing result to generate a system-form generation matrix;

and multiplying the generating matrix in the system form and the new bit sequence to generate a combination of channel coding source information and check information.

A second embodiment of the present invention provides an encoding optimization apparatus for a double-primitive-pattern LDPC code, including:

the optimization unit is used for constructing a multiple connection basic matrix and optimizing the multiple connection basic matrix;

a replacing unit, configured to provide a group of joint coding base matrices based on a dual-prototype LDPC code, replace a single-side connection base matrix of the joint coding base matrix with the optimized multiple connection base matrix, and generate a joint coding matrix;

the extension unit is used for extending each part of the joint coding matrix to generate a channel coding matrix and a connection matrix with a preset size;

the source compression information generating unit is used for carrying out source coding on given original source bits to generate source compression information;

and the coding unit is used for carrying out generalized coding on the joint coding matrix according to the information source compression information, the channel coding matrix and the connection matrix with the preset size.

Preferably, the extension unit further generates a source coding matrix and a multiple connection coding matrix;

Preferably, the optimization unit is specifically configured to:

Preferably, the encoding unit is specifically configured to:

and multiplying the systematic generation matrix and the new bit sequence to generate a combination of channel coding source information and check information.

A third embodiment of the present invention provides an encoding optimization apparatus for a dual-primitive-graph LDPC code, including a memory and a processor, where the memory stores a computer program, and the computer program can be executed by the processor to implement the encoding optimization method for the dual-primitive-graph LDPC code as described in any one of the above.

A fourth embodiment of the present invention provides a storage medium, which stores a computer program, where the computer program can be executed by a processor of a device in which the computer readable storage medium is located, so as to implement the method for encoding and optimizing a dual-primitive-pattern LDPC code as described in any one of the above.

Based on the coding optimization method, the device, the equipment and the storage medium of the double-original-pattern LDPC code provided by the invention, the optimized multiple connection basis matrix is replaced by a single-side connection basis matrix of a group of joint coding basis matrixes based on the double-original-pattern LDPC code to generate a joint coding matrix, each part of the joint coding matrix is expanded to generate a channel coding matrix and a connection matrix with a preset size, and the given original source bit is subjected to source coding to generate source compression information; and performing generalized coding on the joint coding matrix according to the source compression information, the channel coding matrix and the connection matrix with the preset size, so that the possibility that source redundant information and channel state information can be fully utilized is increased.

Drawings

Fig. 1 is a flowchart illustrating a method for encoding and optimizing a dual-primitive-pattern LDPC code according to a first embodiment of the present invention;

FIG. 2 is a diagram illustrating an exemplary method for constructing a multi-connection basis matrix using elementary transformations of the matrix according to an embodiment of the present invention;

FIG. 3 shows the statistical properties (0.96, 0.04) and (0.94, 0.06) provided by the embodiment of the present invention,

and

AWGN Performance simulation ofA true figure;

fig. 4 is a schematic block diagram of an encoding optimization apparatus for a dual-prototype LDPC code according to a first embodiment of the present invention;

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

For better understanding of the technical solutions of the present invention, the following detailed descriptions of the embodiments of the present invention are provided with reference to the accompanying drawings.

It should be understood that the described embodiments are only some embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the examples of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

It should be understood that the term "and/or" as used herein is merely one type of association that describes an associated object, meaning that three relationships may exist, e.g., a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The word "if," as used herein, may be interpreted as "at \8230; \8230when" or "when 8230; \823030when" or "in response to a determination" or "in response to a detection", depending on the context. Similarly, the phrase "if determined" or "if detected (a stated condition or event)" may be interpreted as "upon determining" or "in response to determining" or "upon detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)", depending on the context.

In the embodiments, the references to "first \ second" are merely to distinguish similar objects and do not represent a specific ordering for the objects, and it is to be understood that "first \ second" may be interchanged with a specific order or sequence, where permitted. It should be understood that "first \ second" distinguishing objects may be interchanged under appropriate circumstances such that the embodiments described herein may be implemented in sequences other than those illustrated or described herein.

The following detailed description of specific embodiments of the invention refers to the accompanying drawings.

The invention discloses a coding optimization method, a device, equipment and a storage medium of a double-prototype LDPC code, aiming at increasing the possibility that information source redundant information and channel state information can be fully utilized.

Referring to fig. 1, a first embodiment of the present invention provides a method for encoding and optimizing a dual-protogram LDPC code, which can be performed by an encoding and optimizing apparatus (hereinafter referred to as an optimizing apparatus) of the dual-protogram LDPC code, and in particular, by one or more processors in the optimizing apparatus, to implement at least the following steps:

s101, constructing a multiple connection basic matrix and optimizing the multiple connection basic matrix;

in this embodiment, the optimization device may be a terminal having a data processing and analyzing capability, such as a desktop computer, a notebook computer, a server, and a workstation, wherein the evaluation device may be installed with a corresponding operating system and application software, and the functions required by this embodiment are implemented by the combination of the operating system and the application software.

Specifically, in the present embodiment, a multiple connection edge relationship is introduced, and a multiple connection coding matrix H is used _P Show that the inventors found H _P Usually a very large matrix, directly optimizing H _P Will be very complex becauseThis introduces a prototype LDPC code with a special structure for optimization. A prototype LDPC code is an irregular code which can be represented by a very small-sized basic matrix B = [ B ] _ij ]The method is shown to be expanded into an LDPC matrix H with a large size through a PEG algorithm. Therefore, the performance of the proto-pattern LDPC code can be determined by the base matrix B. In this embodiment, from the perspective of the basic matrix B, the basic matrix B is encoded for different information sources according to the statistical characteristics of the information sources by using the structural characteristics of the basic matrix B _S A channel coding base matrix B _C And a second connection matrix B _L2 Design the multiple connection coding matrix H _P Corresponds to B _P . Obtained B _P And given B _S And B _C The encoding matrix H with a certain code length can be obtained by adopting the PEG algorithm for expansion _P ，H _S ，H _C And H _L2 A generalized encoding algorithm is performed.

S1, giving a unit matrix, performing elementary transformation operation on the unit matrix, and generating multiple connection basis matrixes with different structures according to the operation;

the elementary transformations include: a. for the unit matrix B _E Multiplied by an integer greater than 1;

b. the identity matrix B _E Multiplied by some integer greater than 1, added to the other columns;

c. change B _E Any two column positions;

in this embodiment:

first, different multiple connection matrixes are constructed by matrix operation, and an initial joint coding base matrix is given

The structure of the master pattern is shown in fig. 2 (a). If the matrix operation of c is passed, the result is

The results of the prototype graph are shown in FIG. 2 (b). If the matrix operation of a is passed, the result is

The results of the prototype graph are shown in FIG. 2 (c). If the matrix operation of a and b is performed, the method can obtain

The results of the master graph are shown in FIG. 2 (d).

S2, according to the information source statistical characteristics (p) ₀ ，p ₁ ) And the signal-to-noise ratio E _b /N ₀ Initializing variance values of different variable nodes of the multi-connection basic matrix, wherein the variance of the source variable nodes is ln (p) ₁ /p ₀ ) The variance of the channel variable node is

If the puncturing structure exists, the variance value of the corresponding variable node is 0;

s3, calling a traditional combined external information transfer algorithm, and iteratively updating information transfer of the variable nodes and the check nodes until mutual information of the variable nodes is equal to 1 or the maximum iteration times are reached;

s4, changing the initial signal-to-noise ratio E _b /N ₀ Repeating S2 and S3 until a minimum signal-to-noise ratio E is found _b /N ₀ Making the mutual information of the variable nodes equal to 1;

s5, changing the multiple connection basic matrix, repeating S2, S3 and S4, and finding out the minimum signal-to-noise ratio E _b /N ₀ Multiple connection basis matrices.

It should be noted that the complexity of optimizing the multiple connection basis matrix depends on the size of the matrix and the maximum value of the matrix elements, wherein the size of the matrix is determined by the source coding basis matrix and the channel coding basis matrix. Aiming at the optimization of the multiple connection matrix, the following examples are given by combining a joint external information transfer algorithm, and the traditional joint coding matrix is as follows:

the size of the multiple connection basis matrix is thus 4 x 4. The candidate element value is set to 0,1,2, the source statistics are (0.96, 0.04), and thus the decoding threshold is-1.666 dB. Through the optimization of the steps S2 to S5, the optimal multiple connection basis matrix can be obtained as

The corresponding joint basis matrix is represented as

Its decoding threshold is-2.605 dB.

If the statistical properties of the information source are set to (0.94, 0.06), the conventional method

The corresponding decoding threshold is-0.481 dB. Through the optimization of the steps S2 to S5, the optimal multiple connection basis matrix can be obtained as

The corresponding joint basis matrix is represented as

Its decoding threshold is-1.149 dB.

S102, providing a group of joint coding basic matrixes based on double-prototype LDPC codes, replacing the optimized multiple-connection basic matrixes with single-side connection basic matrixes of the joint coding basic matrixes, and generating joint coding matrixes;

it should be noted that, by introducing multiple connection matrices in the source coding matrix and the channel coding matrix. Multiple connection coding is introduced between the traditional source coding and channel coding, and the possibility of more fully utilizing source redundant information and channel state information is increased. In order to increase the coding gain of the multiple connection matrix. Although a multiple connection matrix is introduced, the decoding mode is not changed, and the complexity is not increased.

S103, expanding each part of the joint coding matrix to generate a channel coding matrix and a connection matrix with a preset size;

in one possible embodiment of the present invention, PEG algorithm (not limited thereto) may be used to expand each part of the joint coding matrix, and also generate a source coding matrix and a multiple connection coding matrix.

Wherein the source coding matrix H _S Multiple concatenated coding matrix H _P A channel coding matrix H _C And a connection matrix H of a predetermined size _L2 For being spliced into a joint coding matrix at a receiving end

Wherein, the receiving end can adopt the belief propagation algorithm to decode.

S104, carrying out source coding on a given original source bit to generate source compression information;

in this embodiment, the encoding may be performed according to the following model:

wherein s is original source bit, c source compression information, (-) ^T Is a transpose operation of the matrix.

And S105, carrying out generalized coding on the joint coding matrix according to the information source compression information, the channel coding matrix and the connection matrix with the preset size.

Specifically, in the present embodiment:

performing multiple connection coding on the source compression information c to generate multiple coding information d, wherein d = c · H _P ；

Splicing the multiple coding information d and an original source bit s to generate a new bit sequence [ sd ];

encoding the channel with a matrix H _C And said connection matrix H of predetermined size _L2 Splicing is carried out to generate a splicing result H _ L2H _ C]And carrying out Gaussian elimination on the splicing result to generate a generator matrix [ I ] in a system form _C G _C ]；

Generating a matrix [ I ] for the system form _C G _C ]And said new bit sequence [ sd ]]Multiplying to generate the combination of channel coding source information and check information u = [ s d =][I _C G _C ]Wherein u = [ s d p ]]；

According to a generalized coding algorithm, the above optimization results are compared by taking the source statistical characteristics (0.96, 0.04) as an example.

Step 1: according to

Introducing optimized multiple connection basis matrix

Replacing the existing single-edge connection base matrix B _I ；

And 2, step: each part of the combined coding matrix is expanded by an expansion factor 200 by adopting a PEG algorithm, and the coding matrix corresponding to the original source bit with the code length of 3200 can be obtained

H _S-0.04 And H _C-0.04 Here H _L2 ＝0；

And step 3: source coding for a given original source bit s, i.e. c = s · H _S-0.04 ；

And 4, step 4: subjecting the obtained c to multiple concatenated coding, i.e.

And 5: splicing s and d to obtain a new bit sequence [ sd]，H _C-0.04 Through Gaussian elimination, a form of [ I ] can be obtained _C-0.04 G _C-0.04 ]A generator matrix in the form of a system of (a);

step 6: to be spliced [ sd]And [ I ] obtained _C G _C ]Multiplication is carried out, and u = [ sd ] can be obtained][I _C- _0.04 G _C-0.04 ]Wherein u = [ sdp = [ ]]；

And 7: at the receiving end, H is converted into _P ，H _S ，H _C And H _L2 The two are spliced into a joint coding matrix,

decoding by using a belief propagation algorithm, wherein the maximum iteration number is 100.

For statistical properties of the source (0.94, 0.06)

Also adopts the same parameters for expansion to obtain

Then a coding algorithm is performed. For is to

The same parameters are also expanded to obtain

And

the corresponding results of the simulation with the conventional codec algorithm are shown in fig. 3, and the simulation channel is AWGN channel. When BER =1 × 10 ^-6 ，

Compared with

With a coding gain of 0.62dB,

compared with

There is a coding gain of 0.36 dB. The analysis of the gain and the decoding threshold value is in accordance with the method, and the effect of the multiple connection matrix is highlighted.

The generalized encoding optimization algorithm of the dual-primitive-pattern LDPC code based on multiple connection matrices proposed by the present invention is introduced and described in detail above, and the above specific implementation can be used to help understand the core idea of the present invention. The source information and the channel information in the traditional double-protogram LDPC coding system are interacted only through a single-side connection matrix. The invention introduces multiple connection matrixes, so that the information interaction can be more sufficient. And meanwhile, in order to improve the effect brought by information interaction, a multiple connection matrix is constructed by a matrix operation method, decoding threshold value calculation is carried out by utilizing an external joint information transfer algorithm, and finally a joint coding matrix with a low decoding threshold value is obtained. Finally, generalized coding algorithms can also be used for the optimized joint coding matrix.

Referring to fig. 4, a second embodiment of the present invention provides an encoding optimization apparatus for a dual-primitive-pattern LDPC code, including:

an optimizing unit 201, configured to construct a multiple connection basis matrix and optimize the multiple connection basis matrix;

a replacing unit 202, configured to provide a group of joint coding basis matrices based on a dual-primitive model LDPC code, replace a single-side connection basis matrix of the joint coding basis matrix with the optimized multiple-connection basis matrix, and generate a joint coding matrix;

an expanding unit 203, configured to expand each part of the joint coding matrix to generate a channel coding matrix and a connection matrix with a predetermined size;

a source compression information generating unit 204, configured to perform source coding on a given original source bit to generate source compression information;

and an encoding unit 205 for performing generalized encoding on the joint coding matrix according to the source compression information, the channel coding matrix and a connection matrix of a predetermined size.

Preferably, the optimization unit is specifically configured to:

s4, changing the initial signal-to-noise ratio, and repeating the S2 and the S3 until the minimum signal-to-noise ratio is found, so that the mutual information of the variable nodes is equal to 1;

Preferably, the encoding unit is specifically configured to:

splicing the multiple coding information and the original source bit to generate a new bit sequence;

Based on the coding optimization method, device, equipment and storage medium of the double-prototype LDPC code provided by the invention, the optimized multiple connection basis matrix replaces a group of unilateral connection basis matrixes of the joint coding basis matrix based on the double-prototype LDPC code to generate a joint coding matrix, each part of the joint coding matrix is expanded to generate a channel coding matrix and a connection matrix with a preset size, and the given original source bit is subjected to source coding to generate source compression information; and performing generalized coding on the joint coding matrix according to the source compression information, the channel coding matrix and the connection matrix with the preset size, so that the possibility that source redundant information and channel state information can be fully utilized is increased.

Illustratively, the computer programs described in the third and fourth embodiments of the present invention may be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the encoding optimization device for implementing a dual-prototype LDPC code. For example, the device described in the second embodiment of the present invention.

The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc., the processor is a control center of the encoding optimization method for the dual-protograph LDPC code, and various interfaces and lines are used to connect the various parts of the whole method for implementing the encoding optimization method for the dual-protograph LDPC code.

The memory may be used to store the computer program and/or module, and the processor may implement various functions of a coding optimization method based on a dual-protograph LDPC code by executing or executing the computer program and/or module stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, a text conversion function, etc.), and the like; the storage data area may store data (such as audio data, text message data, etc.) created according to the use of the cellular phone, etc. Further, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.

Wherein the implemented module, if implemented in the form of a software functional unit and sold or used as a stand-alone product, can be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.

It should be noted that the above-described embodiments of the apparatus are merely illustrative, where the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement without inventive effort.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A coding optimization method of a double-prototype LDPC code is characterized by comprising the following steps:

providing a group of joint coding base matrixes based on double-prototype graph LDPC codes, replacing the single-side connection base matrixes of the joint coding base matrixes with the optimized multiple connection base matrixes, and generating joint coding matrixes;

and carrying out generalized coding on the joint coding matrix according to the source compression information, the channel coding matrix and the connection matrix with the preset size.

2. The method for encoding and optimizing the double-primitive-pattern LDPC code according to claim 1, wherein each part of the joint coding matrix is extended, and a source coding matrix and a multiple connection coding matrix are further generated;

3. The method for encoding and optimizing the double-prototype LDPC code according to claim 1, wherein the constructing a multiple connection basis matrix and optimizing the multiple connection basis matrix specifically comprises:

4. The method for encoding and optimizing the double-primitive-pattern LDPC code according to claim 1, wherein the generalized encoding is performed on the joint coding matrix according to the source compression information, the channel coding matrix and the connection matrix with a predetermined size, specifically:

5. An encoding optimization apparatus for a dual-primitive-pattern LDPC code, comprising:

the replacing unit is used for providing a group of joint coding basic matrixes based on the double-prototype LDPC codes, replacing the optimized multiple-connection basic matrixes with the single-side connection basic matrixes of the joint coding basic matrixes and generating joint coding matrixes;

the information source compression information generating unit is used for carrying out information source coding on given original information source bits to generate information source compression information;

6. The encoding optimization apparatus of a dual-primitive-pattern LDPC code according to claim 5, wherein the extension unit further generates a source coding matrix and a multiple connection coding matrix;

7. The encoding optimization apparatus for double-protogram LDPC code according to claim 5, wherein the optimization unit is specifically configured to:

8. The encoding optimization apparatus for the dual-proto-graph LDPC code according to claim 5, wherein the encoding unit is specifically configured to:

9. An encoding optimization apparatus for a dual-primitive-graph LDPC code, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement the encoding optimization method for the dual-primitive-graph LDPC code according to any one of claims 1 to 4.

10. A storage medium storing a computer program executable by a processor of a device in which the computer-readable storage medium is located to implement a method for encoding optimization of a dual-proto-pattern LDPC code as claimed in any one of claims 1 to 4.