A joint coding method and device under a relay channel model, equipment and medium

Abstract

The application provides a joint coding method and device under a relay channel model, a storage medium, and an apparatus. The method adjusts a sending scheme according to the characteristics of a joint coding matrix, increases original bit information, reduces compressed bit information, and reduces the error floor level of the overall system. The decoding and forwarding of the relay node provides the compressed bit information reduced in the sending node, so that the destination node can have more information for decoding, and the performance of the waterfall region of the system is improved. In the case that the total energy of the sending node and the relay node is constant, the optimal adaptive joint coding sending strategy is selected by optimizing different energy allocation conditions. The scheme uses the same joint coding matrix in the sending node, the relay node, and the destination node, does not increase the complexity of coding and decoding, and has the characteristics of low complexity.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication coding, in particular to a joint coding method and device under a relay channel model, equipment and storage medium. BACKGROUND

[0002] In the Internet of Things communication system, in addition to the point-to-point communication between the sending node and the destination node, there are often many relay nodes, and the overall performance of the system can be significantly improved by using these relay nodes for cooperative communication. The most common relay cooperation scheme is the amplify-and-forward scheme and the decode-and-forward scheme. The amplify-and-forward scheme achieves performance gain through energy amplification of the relay node and diversity combining technology of the destination node, while the decode-and-forward scheme generates new check bit information by designing a new coding structure and performing decoding and re-encoding operations at the relay node to achieve coding gain. The optimization scheme of the traditional LDPC channel coding applied to the relay channel model is to construct a multi-layer coding structure to generate new check bit information. However, the traditional relay channel model does not consider the characteristics of the input source itself, so it is necessary to consider how to apply source coding and channel coding to the relay channel model.

[0003] The joint source channel coding (JSCC) scheme based on dual protograph LDPC code refers to using two protograph LDPC codes to realize source coding and channel coding at the sending node, and establishing the connection between the source protograph LDPC code and the channel protograph LDPC code at the target node by using a connection matrix to construct a new joint coding matrix, and realizing the overall performance gain by fully utilizing the characteristics of the source itself and the received information to perform joint iterative decoding. However, most of the above-mentioned joint source channel coding schemes based on dual protograph LDPC codes (hereinafter referred to as joint coding schemes) do not consider the relay channel model. Although the relay system of the joint coding does not protect the error mechanism, it considers the joint coding scheme in the relay system, but the mixed use of channel coding and joint coding scheme for source transmission cannot realize low complexity and efficient transmission.

[0004] In view of this, the present application is proposed. SUMMARY

[0005] The present application discloses a joint coding method, device, equipment and storage medium under a relay channel model, aiming to realize how to use only a single joint coding matrix, through bit adaptive decomposition and energy allocation closed-loop optimization of the sending node and the relay node, while reducing error flatness and improving waterfall area performance, realizing low complexity and high reliability transmission.

[0006] The first embodiment of the present application provides a joint coding method under a relay channel model, comprising:

[0007] The source sequence and source statistical characteristics are obtained. Based on the preset dual-original-mode graph LDPC joint coding base matrix, a joint coding check matrix is ​​generated through the edge expansion algorithm. The source sequence is then jointly coded to obtain a system form coding sequence, wherein the coding sequence contains original information bits and check bits.

[0008] Based on the degree distribution structure of the joint coding check matrix, the original information bits and check bits are adaptively decomposed into a transmitting part and a reserved part of the transmitting node, and a transmitting sequence of the transmitting node is constructed. Under the constraint of total transmission energy, the transmitting sequence of the transmitting node is broadcast to the relay node and the destination node.

[0009] The relay node receives signals from the sending node, performs log-likelihood ratio initialization and confidence propagation decoding based on partial variable node knowns and equal probability priors, recovers all information bits and check bits, and then constructs a relay forwarding sequence mainly based on increasing check bits according to the degree distribution structure of the same joint coding check matrix, and sends it to the destination node.

[0010] The destination node jointly receives signals from the transmitting node and the relay node, performs joint decoding based on log-likelihood ratio initialization and confidence propagation based on different channel observations and variable node transmission states, and outputs the final decoding result.

[0011] Obtain the decoding performance of the destination node under different energy allocation ratios, and dynamically adjust the bit decomposition ratio and energy allocation ratio of the sending node and relay node through traversal or optimization algorithms.

[0012] Preferably, the joint coding verification matrix is ​​generated based on the preset dual-prototype graph LDPC joint coding fundamental matrix through an edge expansion algorithm, specifically as follows:

[0013] The joint coding fundamental matrix based on dual-primal-graph LDPC codes can be represented as... , The size is The source verification basis matrix, The size is The channel verification fundamental matrix, The size is It is the connection verification base matrix. The size is It involves expanding the basic verification matrix by using an expansion factor to obtain a joint encoding matrix verification. , ,in, The size is The source verification matrix, The size is a channel check matrix, is a check matrix of size is a connection check matrix, is a check matrix of size is an extension check matrix.

[0014] Preferably, the degree distribution structure of the joint encoding check matrix is used to adaptively decompose the original information bits and check bits into a sending node sending part and a reserved part, and a sending node sending sequence is constructed, specifically:

[0015] According to the characteristics of the original information bits s are decomposed into two parts , wherein is the length of the original bit part sent , is the length of the original bit part not sent , according to the characteristics of the check bits c are decomposed into two parts , wherein is the length of the check bit part sent by the relay , is the length of the check bit part sent directly , and a sending sequence is constructed;

[0016] According to the degree distribution structure of and , the source variable node set and the channel variable node set are respectively divided;

[0017] Corresponding to the number of , the is allocated to , the number of is allocated to , corresponding to the number of , the is allocated to , and corresponding to the number of is allocated to , wherein q is the extension factor;

[0018] The decoding threshold corresponding to the relay node and the decoding threshold corresponding to the destination node are calculated, and all possible cases are traversed to select the optimal decoding threshold.

[0019] Preferably, the decoding information corresponding to the variable node of in the relay node is initialized to be calculated respectively , , 0, ;

[0020] wherein, is the variance of the channel from the sending node to the relay node, is the variance of the channel from the sending node to the relay node, corresponds to the received signal, is the variance of the channel from the sending node to the relay node, corresponds to the received signal, is the fraction of 0s in the source bits, is the fraction of 1s in the source bits.

[0021] Preferably, at the destination node, the variable node decoding information initialization is calculated as , , , , is the variance of the channel from the sending node to the destination node;

[0022] is the variance of the channel from the relay node to the destination node, is the variance of the channel from the sending node to the destination node, corresponds to the received signal, is the variance of the channel from the sending node to the destination node, corresponds to the received signal, is the fraction of 0s in the source bits, is the fraction of 1s in the source bits.

[0023] Preferably, the same joint encoding check matrix is used at the relay node, the sending node and the destination node.

[0024] The second embodiment of the present application provides a joint encoding device under a relay channel model, comprising:

[0025] An encoding unit is configured to acquire a source sequence and source statistical characteristics, generate a joint encoding check matrix through an edge expansion algorithm based on a preset dual original module diagram (LDPC) joint encoding base matrix, and perform joint encoding on the source sequence to obtain a system form encoding sequence, wherein the encoding sequence comprises original information bits and check bits.

[0026] A decomposition unit is configured to adaptively decompose the original information bits and the check bits into a sending node sending part and a reserved part according to a degree distribution structure of the joint encoding check matrix, construct a sending node sending sequence, and broadcast the sending node sending sequence to a relay node and a destination node under a total transmission energy constraint.

[0027] The recovery unit is used for receiving signals from the sending node at the relay node, performing log-likelihood ratio initialization and belief propagation decoding based on partial variable node known and equal-probability prior, recovering all information bits and check bits, and then constructing a relay forwarding sequence mainly with increased check bits according to a degree distribution structure of the same joint encoding check matrix, and sending to the destination node;

[0028] The decoding unit is used for jointly receiving signals from the sending node and the relay node at the destination node, performing log-likelihood ratio initialization and belief propagation joint decoding based on different channel observations and variable node sending states, and outputting a final decoding result.

[0029] The feedback unit is used for obtaining decoding performance of the destination node under different energy allocation ratios, and dynamically adjusting the bit decomposition ratio and the energy allocation ratio of the sending node and the relay node through an iteration or optimization algorithm.

[0030] The third embodiment of the present application provides a joint encoding device under a relay channel model, characterized by comprising a memory and a processor, the memory storing a computer program, and the computer program being executable by the processor to implement the joint encoding method under the relay channel model according to any one of the above.

[0031] The fourth embodiment of the present application provides a computer readable storage medium storing a computer program, and the computer program being executable by a processor of a device where the computer readable storage medium is located to implement the joint encoding method under the relay channel model according to any one of the above.

[0032] Based on the joint encoding method, device, equipment and storage medium under the relay channel model provided by the present application, the sending scheme is adjusted according to the characteristics of the joint encoding matrix at the sending node, the original bit information is increased and the compressed bit information is reduced, and the error floor level of the overall system is reduced. At the same time, the compressed bit information reduced at the sending node is provided by the decoding and forwarding of the relay node, so that the destination node can have more information for decoding, and the performance of the waterfall region of the system is improved. Under the condition that the total energy of the sending node and the relay node is constant, the optimal adaptive joint encoding sending strategy is selected by optimizing different energy allocation conditions. Such a scheme uses the same joint encoding matrix at the sending node, the relay node and the destination node, does not increase the complexity of encoding and decoding, and has the characteristics of low complexity. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 is a flowchart of the joint encoding method under the relay channel model provided by the first embodiment of the present application;

[0034] Figure 2The application provides an adaptive transmission scheme based on a dual LDPC code under a relay channel model.

[0035] Figure 3 The application provides a module schematic diagram of a joint coding device under a relay channel model. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the application will be apparently and completely described in connection with the drawings in the embodiments of the application, and obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative work belong to the protection scope of the application.

[0037] In order to better understand the technical solutions of the application, the embodiments of the application will be described in detail in connection with the drawings.

[0038] The application discloses a joint coding method and device under a relay channel model, equipment and a storage medium, aiming at realizing how to use only a single joint coding matrix, through bit adaptive decomposition and energy allocation closed-loop optimization of a sending node and a relay node, reducing error flatness and improving waterfall area performance, realizing low-complexity and high-reliability transmission.

[0039] The first embodiment of the application provides a joint coding method under a relay channel model, which can be executed by an adaptive joint coding device (hereinafter referred to as a coding device or system) under a relay channel model, in particular, by one or more processors in the coding device or system, to at least realize the following steps:

[0040] S101, acquiring a source sequence and a source statistical characteristic, generating a joint coding check matrix through an edge expansion algorithm based on a preset dual protograph LDPC joint coding basic matrix, and performing joint coding on the source sequence to obtain a system form coding sequence, wherein the coding sequence comprises original information bits and check bits;

[0041] In the embodiment, the coding device or system can be a server, a desktop computer, a notebook computer and the like having a data processing capability, and the coding device can be installed with a corresponding operating system and application software, and the functions required in the embodiment can be realized through the combination of the operating system and the application software.

[0042] Specifically, a source sequence to be transmitted is s, the code length of which is bits. The source statistical characteristic is represented by , wherein, represents the proportion of bits "1", The proportion of bits representing "0". The statistical property reflects the non-uniform distribution characteristics of the source.

[0043] The joint encoding process adopts a dual protograph LDPC code structure, and the base matrix has a specific block structure. The base matrix is composed of four sub-matrices: a source check base matrix , a channel check base matrix , a connection check base matrix , and an extension check base matrix .

[0044] wherein the size of is , responsible for source compression encoding; the size of is , responsible for channel error correction encoding; the size of is , establishing a connection between source encoding and channel encoding;

[0045] In order to adapt to the code length requirement of actual transmission, the base matrix needs to be edge-extended. Let the extension factor be q, and replace each non-zero element in the base matrix with a q×q cyclic shift matrix, and replace the zero element with a q×q all-zero matrix through the edge extension algorithm. After extension, the joint encoding check matrix actually used is obtained. Correspondingly, also contains four extended sub-matrices: is a source check matrix with a size of , is a channel check matrix with a size of , is a connection check matrix with a size of is a connection check matrix, is an extension check matrix with a size of .

[0046] To illustrate with a specific example, first, given an initial joint encoding base matrix :

[0047] ,

[0048] , , and . The variable nodes are divided into two parts by the dashed line, which are the source variable node set , the first column to the eighth column of , the channel variable node set , the ninth column to the sixteenth column of .

[0049] The source statistical characteristics are , assuming that the information code length of the transmission is 6400 s, so that the edge extension with a coefficient of q = 800 is required for , and is obtained, so that the bit length corresponding to each variable node is 800. The original source bits are jointly encoded at the sending node, that is, , c is the check bit information with a length of 3200, is Gaussian elimination can obtain a system in the form of

[0050] S102, according to the degree distribution structure of the joint encoding check matrix, adaptively decomposing the original information bits and the check bits into a sending node sending part and a reserved part, constructing a sending node sending sequence, and broadcasting the sending node sending sequence to the relay node and the destination node under the constraint of total transmission energy;

[0051] According to , the original information bits s are decomposed into two parts , wherein is the original bit part directly sent by the sending node, with a length of , is the original bit part not sent, with a length of ; and according to , the check bits c are decomposed into two parts , wherein is the check bit part directly sent by the sending node, with a length of , is the check bit part directly sent, with a length of , and a sending sequence is constructed;

[0052] An example is described, according to the characteristics of , the original information bits s are decomposed into two parts, that is, , wherein the length of s1 is 1600, corresponding to and , and the length of s2 is 4800, corresponding to (i = 3, 4, 5, 6, 7, 8), according to the characteristics of , c is decomposed into two parts, that is, , wherein of length 1600, corresponding to and of length , corresponding to (i = 1, 2, 3, 4, 5, 8), i.e., [s c]= [1 1 1 1 1 1 1 1] ], where the transmission sequence [s c] is constructed as ;

[0053] It should be noted that, the selection needs to be optimized according to different code types, wherein, according to the sparsity of the current source, the relative quality of the three links, and the total power allocation, targeted optimization is performed to ensure that the error flat layer is low enough, and the performance of the waterfall area is pushed to the optimum.

[0054] S103, the relay node receives the signal from the sending node, performs log-likelihood ratio initialization and belief propagation decoding based on partial variable node known and equal probability prior, recovers all information bits and check bits, and then constructs a relay forwarding sequence mainly with increased check bits according to the degree distribution structure of the same joint coding check matrix, and sends to the destination node;

[0055] It should be noted that after the relay node receives the noisy signal broadcast from the sending node, it first accurately distinguishes the four types of variable nodes corresponding to according to the known sending strategy, and performs targeted log-likelihood ratio initialization for different categories: for the original information bits that have been directly sent by the sending node, the initial LLR of the corresponding variable node is directly calculated as , where is the actual received value of on the channel from the sending node to the relay node, is the noise variance of the hop channel; for corresponding to the variable node that is not directly sent but belongs to the original information bit, its initial LLR is uniformly initialized as , so as to fully utilize the source prior redundancy; for the check bits corresponding to the variable node that has been directly sent by the sending node, its initial LLR is also calculated as according to the channel observation; for the check bits that are not sent from the sending node at all and are only responsible for subsequent forwarding by the relay,The corresponding variable node, which has not been sent by the relay at this moment and has no any direct observation, has its initial LLR all initialized to 0 due to the near uniform distribution of the part of bits. Then the relay node performs complete iterative decoding based on the joint encoding check matrix H of the above four types of variable nodes after initialization, using the standard belief propagation algorithm until convergence or the maximum number of iterations is reached, so as to recover the entire information bit sequence and all check bits. After successful decoding, the relay node no longer forwards any original information bits, but only re-modulates the decoded (i.e. the part of check bits intentionally reduced by the sending node) with BPSK and forwards it to the destination node with the allocated transmission energy, so as to realize the "check bit dominant relay forwarding sequence", effectively supplement the missing check information of the destination node under the condition of limited total transmission energy, significantly improve the performance of the waterfall region, and maintain the same encoding matrix structure and extremely low implementation complexity as the sending node.

[0056] S104, the destination node jointly receives signals from the sending node and the relay node, performs log-likelihood ratio initialization and belief propagation joint decoding based on different channel observations and variable node transmission states, and outputs a final decoding result;

[0057] Preferably, at the destination node, The decoding information initialization of the variable node is calculated as , , , , is the variance of the channel from the sending node to the destination node;

[0058] is the variance of the channel from the relay node to the destination node, is the variance of the channel from the sending node to the destination node corresponding to the received signal, is the variance of the channel from the sending node to the destination node corresponding to the received signal, is the proportion of 0 in the source bits, is the proportion of 1 in the source bits.

[0059] It should be noted that after the destination node receives two noisy signals from the sending node direct broadcast link and the relay node forwarding link, it can accurately distinguish four types of variable nodes according to the known joint encoding check matrix H and the globally unified bit decomposition strategy, and perform differential log-likelihood ratio initialization and joint decoding.

[0060] For the original information bits sent by the sending node, the initial LLR of the corresponding variable node is calculated as wherein the corresponding received value on the direct link from the transmitting node to the destination node, the noise variance of the direct link;

[0061] for the original information bits not directly transmitted by the transmitting node the corresponding variable node, whose initial LLR is uniformly initialized as so as to continue to retain the gain brought by source redundancy;

[0062] for the small number of check bits directly transmitted by the transmitting node the corresponding variable node, whose initial LLR is calculated as where the corresponding received value on the direct link from the transmitting node to the destination node, the noise variance of the direct link; for the key check bits completely responsible for supplementary forwarding by the relay node

[0063] the corresponding variable node, whose initial LLR is calculated as where the actual received value on the relay-destination link from the relay node to the destination node, the noise variance of the relay-destination link. After the initialization, the destination node performs global joint iterative decoding on all variable nodes based on the same joint encoding check matrix H by using the standard belief propagation algorithm. Since the transmitting node has transmitted the original information bits significantly reducing the error floor, and the relay node has accurately supplemented the large number of check bits intentionally reduced

[0064] significantly improving the performance of the waterfall region, the destination node can achieve an extremely low bit error rate at a much lower signal-to-noise ratio than the traditional scheme under the joint action of the two-hop channel observation, source prior and relay additional check information. S105, obtain the decoding performance of the destination node under different energy allocation ratios, and dynamically adjust the bit decomposition ratio and energy allocation ratio of the transmitting node and the relay node through an exhaustive or optimization algorithm.

[0065] S105, obtain the decoding performance of the destination node under different energy allocation ratios, and dynamically adjust the bit decomposition ratio and energy allocation ratio of the transmitting node and the relay node through an exhaustive or optimization algorithm.

[0066] ​​It should be noted that the system will evaluate a plurality of possible combination schemes in advance or in real time under the condition that the total transmission power is fixed: each scheme contains how many original information bits are sent by the sending node, how many check bits are reserved for the relay to supplement, and how much transmission power is allocated to the sending node and the relay node respectively. The system tests the decoding performance that can be finally achieved by these combinations at the destination node one by one through simulation or fast theoretical analysis, especially whether the error floor in the high signal-to-noise ratio region has been low enough to almost no longer decline (i.e. whether the error floor meets the reliability requirement) and whether the starting point of the sharp decline of the error rate in the medium signal-to-noise ratio region appears as left as possible (i.e. whether the waterfall region is steep enough). Among all the combinations that can guarantee a low enough error floor, the system selects the one with the best performance in the waterfall region as the best strategy under the current condition.

[0067] In actual communication, as long as the density of the source or the quality of the three links changes, the sending end or the control node will immediately find out or quickly calculate the current optimal original information transmission ratio, check bit reservation ratio and power allocation ratio of the two nodes from the prepared strategy table according to the latest source statistical characteristics and channel state, and accordingly adjust which bits are sent and how much power is used for transmission in this transmission, so as to realize completely adaptive closed-loop optimization, so that the system can always push the performance of the waterfall region to the best while meeting the extremely low error floor no matter what the source and channel environment is, and the entire adjustment process only amounts to changing a sending subset and power ratio on the same code table, without changing the codebook and without increasing any coding and decoding complexity.

[0068] In a possible implementation of the present application, the relay node, the sending node and the destination node all use the same joint encoding check matrix.

[0069] It should be noted that the three parties of the sending node, the relay node and the destination node share and only use the same joint encoding check matrix throughout the whole process, which is constructed and fixed once in the initial design stage according to the statistical characteristics of the source. The sending node only completes the joint encoding of the original source based on the matrix to obtain the complete system form coding sequence; the relay node still directly loads the same check matrix for belief propagation decoding after receiving part of the bits to recover all information bits and check bits without any additional encoding structure or re-encoding operation; the relay node also only selects the part of the check bits recovered from the matrix to send directly when forwarding; the destination node also loads the same matrix after receiving the signals from the sending node and the relay node, and performs a complete joint iterative decoding based on the observation of different channels and the known sending state to obtain the final result. In the whole process, none of the three parties needs to introduce a second code type, multi-layer encoding, nested structure or different check matrices, and all encoding, decoding and forwarding operations are strictly carried out around the same joint encoding check matrix, so as to realize the double optimization of error flat and waterfall area while reducing the storage demand, implementation difficulty and coordination cost between nodes to the minimum.

[0070] The second embodiment of the application provides a joint encoding device under a relay channel model, comprising:

[0071] An encoding unit is configured to obtain a source sequence and a statistical characteristic of the source, generate a joint encoding check matrix through an edge expansion algorithm based on a preset dual original module LDPC joint encoding base matrix, and perform joint encoding on the source sequence to obtain a system form coding sequence, wherein the coding sequence comprises original information bits and check bits.

[0072] A decomposition unit is configured to adaptively decompose the original information bits and the check bits into a sending node sending part and a reserved part according to a degree distribution structure of the joint encoding check matrix, construct a sending node sending sequence, and broadcast the sending node sending sequence to a relay node and a destination node under a total transmission energy constraint.

[0073] A recovery unit is configured to receive a signal from the sending node at the relay node, perform log-likelihood ratio initialization and belief propagation decoding based on a part of variable nodes known and equal-probability prior, recover all information bits and check bits, and then construct a relay forwarding sequence mainly with increased check bits according to a degree distribution structure of the same joint encoding check matrix and send the relay forwarding sequence to the destination node.

[0074] A decoding unit is configured to jointly receive signals from the sending node and the relay node at the destination node, perform log-likelihood ratio initialization and belief propagation joint decoding based on different channel observations and variable node sending states, and output a final decoding result.

[0075] The feedback unit is used to obtain decoding performance of the destination node under different energy distribution ratios, and dynamically adjusts the bit resolution ratio and the energy distribution ratio of the sending node and the relay node through an iteration or optimization algorithm.

[0076] The third embodiment of the present application provides a joint encoding device under a relay channel model, characterized by comprising a memory and a processor, the memory storing a computer program, the computer program being executable by the processor to implement the joint encoding method under a relay channel model according to any one of the preceding embodiments.

[0077] The fourth embodiment of the present application provides a computer readable storage medium storing a computer program, the computer program being executable by a processor of a device where the computer readable storage medium is located to implement the joint encoding method under a relay channel model according to any one of the preceding embodiments.

[0078] Based on the joint encoding method, device, equipment and storage medium under a relay channel model provided by the present application, the sending scheme is adjusted according to the characteristics of the joint encoding matrix at the sending node, the original bit information is increased and the compressed bit information is reduced, and the error floor level of the overall system is reduced. Meanwhile, the relay node uses the decoding forwarding to provide the compressed bit information reduced at the sending node, so that the destination node can have more information for decoding, and the performance of the waterfall region of the system is improved. In the case that the total energy of the sending node and the relay node is constant, the optimal adaptive joint encoding sending strategy is selected by optimizing different energy distribution conditions. Such a scheme uses the same joint encoding matrix at the sending node, the relay node and the destination node, and does not increase the complexity of encoding and decoding, and has the characteristics of low complexity.

[0079] Exemplarily, the computer program in the third embodiment and the fourth embodiment of the present application can be divided into one or more modules, the one or more modules being stored in the memory and executed by the processor to complete the present application. The one or more modules can be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the joint encoding device under a relay channel model. For example, the device in the second embodiment of the present application.

[0080] The processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic components, discrete hardware components, etc. The general-purpose processor can be a microprocessor or can also be any conventional processor. The processor is a control center of the joint coding method under a relay channel model, and is connected with various parts of the joint coding method under a relay channel model through various interfaces and lines.

[0081] The memory can be used to store the computer program and / or modules, and the processor realizes various functions of the joint coding method under a relay channel model by running or executing the computer program and / or modules stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area. The program storage area can store an operating system, at least one application program required by a function (such as a sound playing function, a text conversion function, etc.), etc.; and the data storage area can store data created according to the use of the mobile phone (such as audio data, text message data, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, for example, a hard disk, a memory, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, at least one disk storage device, a flash memory device, or other volatile solid-state memory devices.

[0082] The implemented modules, if implemented in the form of software function units and sold or used as independent products, can be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the above-mentioned embodiment methods of the present application can also be completed by a computer program instructing related hardware, and the computer program can be stored in a computer readable storage medium. The computer program can implement the steps of each method embodiment when executed by a processor. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms. The computer readable medium can include any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the contents included in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example, in some jurisdictions, according to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.

[0083] It should be noted that the above-described device embodiments are only schematic, and the units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. In addition, the connection relationship between the modules in the device embodiment provided by the present application indicates that there is a communication connection between them, which can be realized as one or more communication buses or signal lines. Those skilled in the art can understand and implement it without creative labor.

[0084] The above is only a preferred embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed by the present application can be easily thought of by those skilled in the art, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A joint encoding method under a relay channel model, characterized in that, The method comprises the following steps: obtaining a source sequence and a source statistical characteristic, generating a joint coding check matrix based on a preset dual protograph LDPC joint coding base matrix through an edge expansion algorithm, and performing joint coding on the source sequence to obtain a system form coding sequence, wherein the coding sequence comprises original information bits and check bits; Based on the degree distribution structure of the joint coding parity matrix, the original information bits and parity bits are adaptively decomposed into a transmitting part and a reserved part by the transmitting node, and the transmitting sequence of the transmitting node is constructed, specifically as follows: The characteristic is that it decomposes the original information bits s into two parts. ,in, The length of the original bit portion to be sent is , The length of the unsent raw bit portion is ,according to The feature is that the parity bit c is decomposed into two parts. ,in The length of the check bit portion transmitted by the relay is [length missing]. , The length of the directly transmitted check bits is [length missing]. Construct the sending sequence [ ];according to and Based on the structural characteristics of the degree distribution, they are divided into sets of source variable nodes. Channel variable node set ; will correspond to a quantity of of Assigned to For a quantity of Assigned to , corresponding to a quantity of of Assigned to , corresponding to a quantity of Assigned to , where q is the expansion factor; calculate the decoding threshold corresponding to the relay node and the decoding threshold corresponding to the destination node, traverse all cases, and select the optimal decoding threshold; broadcast the sending node's transmission sequence to the relay node and the destination node under the total transmission energy constraint; at a relay node, receiving a signal from a sending node, performing log-likelihood ratio initialization and belief propagation decoding based on partial variable node known and equal-probability prior, recovering all information bits and check bits, and then constructing a relay forwarding sequence mainly increasing check bits according to a degree distribution structure of the same joint coding check matrix and sending the relay forwarding sequence to a destination node; at the destination node, jointly receiving signals from the sending node and the relay node, performing log-likelihood ratio initialization and belief propagation joint decoding based on different channel observations and variable node sending states, and outputting a final decoding result; obtaining a decoding performance of the destination node under different energy allocation ratios, and dynamically adjusting a bit decomposition ratio and an energy allocation ratio of the sending node and the relay node through an iteration or optimization algorithm.

2. The joint encoding method under a relay channel model according to claim 1, characterized in that, The joint coding check matrix is generated based on the preset dual protograph LDPC joint coding base matrix through the edge expansion algorithm, and specifically comprises: The joint encoding base matrix based on the dual LDPC code can be expressed as , is a source check base matrix with a size of , is a channel check base matrix with a size of , is a connection check base matrix with a size of , is an extended check base matrix with a size of , and the base matrix is extended according to an extension factor to obtain a joint encoding matrix check , wherein is a source check matrix with a size of , is a channel check matrix with a size of , is a connection check matrix with a size of , is an extended check matrix with a size of .

3. The joint encoding method under a relay channel model according to claim 2, characterized in that, In case the relay node corresponds to the decoding information of the variable nodes is initialized to , 0, respectively. wherein is the variance of the channel from the transmitting node to the relay node, is the variance of the channel from the transmitting node to the relay node, corresponds to the received signal, is the variance of the channel from the transmitting node to the relay node, corresponds to the received signal, is the proportion of 0s in the source bits, is the proportion of Is in the source bits.

4. The joint encoding method under a relay channel model according to claim 2, characterized in that, At the destination node, The variable node's decoding information initialization is calculated respectively as , , , , is the variance of the channel from the sending node to the destination node; is the variance of the channel from the relay node to the destination node, is the variance of the channel from the transmitting node to the destination node is the corresponding received signal, is the variance of the channel from the transmitting node to the destination node is the corresponding received signal, is the proportion of 0s in the source bits, is the proportion of 1s in the source bits.

5. The joint encoding method under a relay channel model according to claim 2, wherein, the same joint coding check matrix is used at the relay node, the sending node and the destination node.

6. A joint encoding apparatus under a relay channel model, characterized in that, The method comprises the following steps: an encoding unit is configured to obtain a source sequence and a source statistical characteristic, generate a joint coding check matrix based on a preset dual protograph LDPC joint coding base matrix through an edge expansion algorithm, and perform joint coding on the source sequence to obtain a system form coding sequence, wherein the coding sequence comprises original information bits and check bits; The decomposition unit is used to adaptively decompose the original information bits and check bits into a transmitting part and a reserved part of the transmitting node according to the degree distribution structure of the joint coding check matrix, and to construct the transmitting sequence of the transmitting node. Specifically, it is used to: The characteristic is that it decomposes the original information bits s into two parts. ,in, The length of the original bit portion to be sent is , The length of the unsent raw bit portion is ,according to The feature is that the parity bit c is decomposed into two parts. ,in The length of the check bit portion transmitted by the relay is [length missing]. , The length of the directly transmitted check bits is [length missing]. Construct the sending sequence [ ];according to and Based on the structural characteristics of the degree distribution, they are divided into sets of source variable nodes. Channel variable node set ; will correspond to a quantity of of Assigned to For a quantity of Assigned to , corresponding to a quantity of of Assigned to , corresponding to a quantity of Assigned to , where q is the expansion factor; calculate the decoding threshold corresponding to the relay node and the decoding threshold corresponding to the destination node, traverse all cases, and select the optimal decoding threshold; broadcast the sending node's transmission sequence to the relay node and the destination node under the total transmission energy constraint; a recovery unit is configured to, at a relay node, receive a signal from a sending node, perform log-likelihood ratio initialization and belief propagation decoding based on partial variable node known and equal-probability prior, recover all information bits and check bits, and then construct a relay forwarding sequence mainly increasing check bits according to a degree distribution structure of the same joint coding check matrix and send the relay forwarding sequence to a destination node; a decoding unit is configured to, at the destination node, jointly receive signals from the sending node and the relay node, perform log-likelihood ratio initialization and belief propagation joint decoding based on different channel observations and variable node sending states, and output a final decoding result; a feedback unit is configured to obtain a decoding performance of the destination node under different energy allocation ratios, and dynamically adjust a bit decomposition ratio and an energy allocation ratio of the sending node and the relay node through an iteration or optimization algorithm.

7. A joint encoding device under a relay channel model, characterized in that, The computer program can be executed by the processor to implement the joint coding method under the relay channel model according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer program can be executed by the processor to implement the joint coding method under the relay channel model according to any one of claims 1 to 5.

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