Joint coding method and device under relay channel model, equipment and medium

Abstract

The invention provides a joint coding method, device and equipment under a relay channel model and a storage medium, a sending scheme is adjusted at a sending node according to the characteristics of a joint coding matrix, original bit information is increased, compressed bit information is reduced at the same time, and the error leveling level of a whole system is reduced. And meanwhile, reduced compressed bit information is provided at the sending node by utilizing decoding and forwarding of the relay node, so that the destination node can have more information for decoding, and the waterfall zone performance of the system is improved. Under the condition that the total energy of a sending node and a relay node is fixed, the optimal self-adaptive joint coding sending strategy is selected by optimizing different energy distribution conditions. According to the scheme, the same joint coding matrix is used at the sending node, the relay node and the destination node, the coding and decoding complexity is not increased, and the method has the characteristic 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: 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. 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. 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. 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. 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. 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: 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 basic matrix for link verification. 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 The channel check matrix, The size is It is a connection check matrix. The size is It is an extended parity check matrix.

[0007] Preferably, the step of adaptively decomposing 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 constructing the transmitting sequence of the transmitting node, specifically involves: according 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 ; The corresponding quantity is 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 possible cases, and select the optimal decoding threshold.

[0008] Preferably, in the relay node corresponding to The initialization of the decoding information of the variable nodes is calculated as follows: , 0 ; in, It is the variance of the channel from the sending node to the relay node. For sending nodes to relay nodes Corresponding received signal, For sending nodes to relay nodes Corresponding received signal, a proportion of 0 in source bits, a proportion of 1 in source bits.

[0009] Preferably, at the destination node, The decoding information initialization of the variable nodes is respectively calculated 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 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, a proportion of 0 in source bits, a proportion of 1 in source bits.

[0010] Preferably, the same joint encoding check matrix is used at the relay node, the sending node and the destination node.

[0011] The second embodiment of the present application provides a joint encoding device under a relay channel model, comprising: 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; 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; A recovery unit is configured to receive a signal from a sending node at a relay node, perform log-likelihood ratio initialization based on a partial variable node known and equal-probability prior and belief propagation decoding, 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 to a destination node; A decoding unit is configured to jointly receive signals from a sending node and a relay node at a destination node, perform log-likelihood ratio initialization based on different channel observations and variable node sending states and belief propagation joint decoding, and output a final decoding result; The feedback unit is used to obtain the 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. 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.

[0012] 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.

[0013] 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, does not increase the complexity of encoding and decoding, and has the characteristics of low complexity. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is a flowchart of the joint encoding method under a relay channel model provided by the first embodiment of the present application; Figure 2 is an adaptive transmission scheme under a relay channel model based on a double LDPC code provided by the present application; Figure 3 is a module schematic diagram of the joint encoding device under a relay channel model provided by the second embodiment of the present application. DETAILED DESCRIPTION

[0015] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0016] To better understand the technical solution of the present invention, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0017] This invention discloses a joint coding method, apparatus, device, and storage medium under a relay channel model, aiming to achieve low-complexity, high-reliability transmission by using only a single joint coding matrix, through adaptive bit decomposition and energy allocation closed-loop optimization of the transmitting node and relay node, while reducing error planes and improving waterfall performance.

[0018] The first embodiment of the present invention provides a joint coding method under a relay channel model, which can be executed by an adaptive joint coding device (hereinafter referred to as coding device or system) under the relay channel model, specifically by one or more processors within the coding device or system, to at least implement the following steps: S101, Obtain the source sequence and source statistical characteristics, generate a joint coding check matrix based on the preset dual original mode graph LDPC joint coding base matrix through the edge expansion algorithm, and perform joint coding on the source sequence to obtain a system form coding sequence, wherein the coding sequence contains original information bits and check bits; In this embodiment, the encoding device or system may be a server, a desktop computer, a laptop computer, or other terminal with data processing capabilities. The encoding device may be equipped with a corresponding operating system and application software, and the functions required in this embodiment are realized through the combination of the operating system and application software. Specifically, let the source sequence to be transmitted be s, and its code length be . Bits. Source statistical characteristics are used. It means that, among them, The proportion representing bits "1" This represents the proportion of bits "0". Statistical properties reflect the non-uniform distribution characteristics of the information source.

[0019] The joint encoding process employs a dual-prototype LDPC code structure, whose fundamental matrix... It has a specific block structure. This fundamental matrix It consists of four sub-matrices: the source verification base matrix Channel verification fundamental matrix , Connect and verify the basic matrix and extended verification base matrix .

[0020] in, The size is Responsible for source compression coding; The size is , responsible for channel error correction coding; The size is Establish the link between source coding and channel coding; The size is It provides additional validation constraints to enhance error correction capabilities.

[0021] To adapt to the code length requirements of actual transmission, the fundamental matrix needs to be modified. Perform an edge expansion operation. Let the expansion factor be q, and use the edge expansion algorithm to expand the fundamental matrix... Each non-zero element in the matrix is ​​replaced with a q×q cyclic shift matrix, and zero elements are replaced with a q×q all-zero matrix. After expansion, the actual joint encoding check matrix is ​​obtained. Accordingly, It also contains four expanded submatrices: The size is The source verification matrix, The size is The channel check matrix, The size is It is a connection check matrix. The size is It is an extended parity check matrix.

[0022] To illustrate with a concrete example, firstly, given an initial joint encoding basis matrix... for: , , , as well as The variable nodes are divided into two parts by dashed lines: the source variable node set and the variable node set. , corresponding to Columns 1 to 8: Set of channel variable nodes , corresponding to Columns 9 to 16.

[0023] Source statistical characteristics are Assuming the transmitted information code length is 6400 seconds, it is necessary to... By expanding the edge with coefficient q=800, we obtain Therefore, the bit length corresponding to each variable node is 800. The sending node corresponds to the original source bits. Perform joint encoding, that is c is a checksum of length 3200 bits. yes Gaussian elimination yields a system form of the form .

[0024] S102, 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. according to The original information bits s are decomposed into two parts. ,in The length of the raw bit portion directly transmitted by the sending node is [length missing]. , The unsent portion of the original bits has a length of [length missing]. ; at the same time according to The parity bit c is decomposed into two parts. ,in The parity bits are sent directly by the sending node, and their length is... , The length of the directly transmitted check bits is [length missing]. Construct the sending sequence [ ]; To illustrate with an example, based on The characteristic of this is that it decomposes the original information bits s into two parts, namely Where s1 has a length of 1600, corresponding to and The length of s2 is 4800, corresponding to (i=3,4,5,6,7,8), according to The characteristic of this property is that it decomposes c into two parts, namely ,in The length is 1600, corresponding to and The length is , corresponding to (i=1,2,3,4,5,8), that is, [sc]=[ Here, the sending sequence is constructed. ]; It should be noted that, The selection needs to be optimized based on different code types, among which, Based on the density of the current information sources, the relative quality of the three links, and the total power distribution, targeted optimizations are made to maximize the performance of the waterfall area while ensuring that the error level is low enough.

[0025] S103, the relay node receives the signal from the sending node, performs log-likelihood ratio initialization and confidence 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 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. It should be noted that after receiving the noisy signal broadcast from the sending node, the relay node first accurately distinguishes the four types of variable nodes according to the known transmission strategy. And perform targeted log-likelihood ratio initialization for different categories: for the original information bits that have been directly transmitted by the sending node The initial LLR of the corresponding variable node is directly calculated as follows: ,in For the corresponding channel between the sending node and the relay node The actual received value, This represents the noise variance of the hopping channel; for bits that are not directly transmitted but belong to the original information bits... The corresponding variable nodes, because they follow known non-uniform source statistical characteristics, have their initial LLR uniformly initialized as follows: This allows for full utilization of prior redundancy in the information source; for the parity bits that the transmitting node has already directly transmitted... The initial LLR of the corresponding variable node is also calculated based on channel observations. For check bits that are not sent from the sending node and are only forwarded by the relay, For the corresponding variable nodes, since the relay has not yet transmitted and there is no direct observation, and the bits in this part are nearly uniformly distributed, their initial LLR is all initialized to 0. Subsequently, the relay node uses the standard confidence propagation algorithm to perform complete iterative decoding based on the joint coding parity matrix H initialized by the above four types of variable nodes, until convergence or the maximum number of iterations is reached, thereby recovering the entire information bit sequence and all parity bits. After successful decoding, the relay node no longer forwards any original information bits, but only re-modulates the decoded parity bits (i.e., the part of parity bits that the sending node deliberately reduced) into BPSK and forwards them to the destination node with the allocated transmission energy, thereby realizing a "parity bit-based relay forwarding sequence". Under the condition of limited total transmission energy, this effectively supplements the missing parity information of the destination node, significantly improves the performance of the waterfall area, and maintains the same coding matrix structure as the sending node and extremely low implementation complexity.

[0026] S104, at the destination node, signals from the transmitting node and the relay node are jointly received, and joint decoding based on log-likelihood ratio initialization and confidence propagation is performed based on different channel observations and variable node transmission states, and the final decoding result is output. Preferably, at the destination node, The initialization of the decoding information of the variable nodes is calculated as follows: , , , , It is the variance of the channel from the sending node to the destination node; It is the variance of the channel from the relay node to the destination node. For sending node to destination node Corresponding received signal, For sending node to destination node Corresponding received signal, The proportion of 0s in the source bits. The proportion of 1s in the source bits.

[0027] It should be noted that after the destination node simultaneously receives two noisy signals from the direct broadcast link of the sending node and the forwarding link of the relay node, it also accurately distinguishes the four types of variable nodes based on the known joint coding parity matrix H and the globally unified bit decomposition strategy. Differential log-likelihood ratio initialization and joint decoding are performed separately. Specifically: For the raw information bits directly sent by the sending node The corresponding variable node has an initial LLR calculated as follows: ,in For the corresponding channel on the sending node to the destination node The received value, This represents the noise variance of the direct link; For bits that are not directly sent by the sending node but belong to the original information bits The corresponding variable nodes, because they obey known priors of non-uniform information sources, have their initial LLR uniformly initialized as follows: This allows the gains from source redundancy to be retained. For the small number of parity bits directly sent by the sending node The corresponding variable node has an initial LLR calculated as follows: ,in For the corresponding direct link The received value, Direct link noise variance; For critical check bits that are entirely supplemented and forwarded by relay nodes The corresponding variable node has an initial LLR calculated as follows: ,in For the corresponding relay node to destination node channel The actual received value, This represents the noise variance of the relay-destination link.

[0028] After initialization, the destination node, based on the identical joint coding parity-check matrix H, uses the standard confidence propagation algorithm to perform global joint iterative decoding on all variable nodes. Since the sending node has already transmitted extra bits of the original information... (Significantly reduced error levels), while relay nodes precisely replenished the large number of parity bits that had been intentionally reduced. (Significantly improves waterfall area performance) With the combined effect of two-hop channel observations of different quality, source prior information and additional check information from relays, the destination node can achieve an extremely low bit error rate at a signal-to-noise ratio far lower than that of traditional schemes.

[0029] 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 sending node and the relay node through traversal or optimization algorithms. It should be noted that, with a fixed total transmit power, the system pre-evaluates or evaluates multiple possible combinations of schemes: each scheme includes how many original information bits the transmitting node sends, how many parity bits are reserved for relay supplementation, and how much transmit power is allocated to each of the transmitting and relay nodes. The system tests the decoding performance achievable at the destination node for each of these combinations through simulation or rapid theoretical analysis, specifically examining whether the bit error rate in the high SNR region has almost reached its limit (i.e., whether the error plane meets reliability requirements), and whether the earliest point of sharp decrease in bit error rate in the medium SNR region is as far to the left as possible (i.e., whether the waterfall region is steep enough). Among all combinations that guarantee a sufficiently low error plane, the system selects the one with the best performance in the waterfall region as the optimal strategy under the current conditions.

[0030] In actual communication, whenever the density of the information source or the quality of the three links changes, the transmitting end or control node will immediately look up or quickly calculate the optimal original information transmission ratio, parity bit retention ratio, and power allocation ratio between the two nodes from the prepared strategy table based on the latest information source statistical characteristics and channel status. Based on this, it will adjust which bits to transmit and how much power each node uses for transmission, thereby achieving fully adaptive closed-loop optimization. This ensures that the system can always push the waterfall area performance to the optimal level while meeting extremely low error levels, regardless of the information source and channel environment. The entire adjustment process is equivalent to changing the transmission subset and power ratio on the same coding table, without changing the codebook or increasing any coding and decoding complexity.

[0031] In one possible implementation of the invention, the exact same joint coding check matrix is ​​used in the relay node, the sending node, and the destination node.

[0032] It should be noted that the sending node, relay node, and destination node share and use only the same joint coding parity check matrix throughout the entire process. This matrix was constructed and fixed once during the initial design phase based on the statistical characteristics of the information source. The sending node uses only this matrix to perform joint coding of the original information source, obtaining a complete system-form coding sequence. After receiving some bits, the relay node directly loads the exact same parity check matrix for confidence propagation decoding, recovering all information bits and parity bits without any additional coding structure or re-coding operation. When forwarding, the relay node only selects the necessary supplementary parts from the parity bits recovered from this matrix and sends them directly. After receiving two signals, the destination node also loads the same matrix and performs a complete joint iterative decoding based on the observations of different links and the known transmission status to obtain the final result. Throughout the entire process, none of the three parties need to introduce a second code type, multi-layer coding, nested structure, or different parity check matrices. All coding, decoding, and forwarding operations strictly revolve around the same joint coding parity check matrix, thereby achieving dual optimization of error leveling and waterfall areas while minimizing the overall system storage requirements, implementation difficulty, and inter-node coordination overhead.

[0033] The second embodiment of the present invention provides a joint coding apparatus under a relay channel model, comprising: The encoding unit is used to acquire the source sequence and source statistical characteristics. Based on the preset dual-original-mode graph LDPC joint encoding base matrix, it generates a joint encoding check matrix through the edge expansion algorithm, and performs joint encoding on the source sequence to obtain a system form encoding sequence, wherein the encoding sequence contains 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, construct the transmitting node transmission sequence, and broadcast the transmitting node transmission sequence to the relay node and the destination node under the total transmission energy constraint. The recovery unit is used to receive signals from the transmitting node at the relay node, perform log-likelihood ratio initialization and confidence propagation decoding based on partial variable node knowns and equal probability priors, recover all information bits and check bits, and then construct a relay forwarding sequence mainly based on increasing check bits according to the degree distribution structure of the same joint coding check matrix, and send it to the destination node. The decoding unit is used to jointly receive signals from the transmitting node and the relay node at the destination node, perform joint decoding based on log-likelihood ratio initialization and confidence propagation based on different channel observations and variable node transmission states, and output the final decoding result. The feedback unit is used to obtain the decoding performance of the destination node under different energy allocation ratios, and dynamically adjusts the bit decomposition ratio and energy allocation ratio of the sending node and the relay node through traversal or optimization algorithms. The third embodiment of the present invention provides a joint coding device under a relay channel model, characterized in that it includes a memory and a processor, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement a joint coding method under a relay channel model as described in any of the above embodiments.

[0034] The fourth embodiment of the present invention provides a computer-readable storage medium storing a computer program, which can be executed by a processor of the device in which the computer-readable storage medium is located, to implement a joint coding method under a relay channel model as described in any of the above embodiments.

[0035] Based on the joint coding method, apparatus, device, and storage medium provided by this invention under a relay channel model, the transmission scheme at the transmitting node is adjusted according to the characteristics of the joint coding matrix, increasing the original bit information while reducing the compressed bit information, thereby reducing the overall system error level. Simultaneously, the decoding and forwarding of the relay node provides the compressed bit information reduced at the transmitting node, allowing the destination node to have more information for decoding, improving the system's waterfall performance. Given a fixed total energy for the transmitting and relay nodes, the optimal adaptive joint coding transmission strategy is selected by optimizing different energy allocation scenarios. This scheme uses the same joint coding matrix at the transmitting, relay, and destination nodes, without increasing the complexity of encoding and decoding, exhibiting low complexity.

[0036] Exemplary examples show that the computer program described in the third and fourth embodiments of the present invention can 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 can be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the joint coding device implementing a relay channel model. For example, the apparatus described in the second embodiment of the present invention.

[0037] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the joint coding method under the relay channel model, connecting the various parts of the joint coding method under the relay channel model through various interfaces and lines.

[0038] The memory can be used to store the computer program and / or modules. The processor, by running or executing the computer program and / or modules stored in the memory, and by calling the data stored in the memory, implements various functions of a joint coding method under a relay channel model. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, text conversion function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, text message data, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0039] If the implemented module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0040] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0041] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A joint coding method under a relay channel model, characterized in that, include: 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. 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. 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. 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. 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.

2. The joint coding method under a relay channel model according to claim 1, characterized in that, The joint encoding base matrix based on the preset dual-prototype graph LDPC is used to generate a joint encoding verification matrix through an edge expansion algorithm, specifically as follows: 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 basic matrix for link verification. 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 The channel check matrix, The size is It is a connection check matrix. The size is It is an extended parity check matrix.

3. The joint coding method under a relay channel model according to claim 2, characterized in that, The step of adaptively decomposing the original information bits and check bits into a transmitting part and a reserved part by the transmitting node based on the degree distribution structure of the joint coding check matrix, and constructing the transmitting sequence by the transmitting node, is as follows: according 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 ; The corresponding quantity is 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.

4. The joint coding method under a relay channel model according to claim 3, characterized in that, In the relay node corresponding to The initialization of the decoding information of the variable nodes is calculated as follows: , 0 ; in, It is the variance of the channel from the sending node to the relay node. For sending nodes to relay nodes Corresponding received signal, For sending nodes to relay nodes Corresponding received signal, The proportion of 0s in the source bits. The proportion of 1s in the source bits.

5. The joint coding method under a relay channel model according to claim 3, characterized in that, At the destination node, The initialization of the decoding information of the variable nodes is calculated as follows: , , , , It is the variance of the channel from the sending node to the destination node; It is the variance of the channel from the relay node to the destination node. For sending node to destination node Corresponding received signal, For sending node to destination node Corresponding received signal, The proportion of 0s in the source bits. The proportion of 1s in the source bits.

6. The joint coding method under a relay channel model according to claim 3, characterized in that, The same joint coding check matrix is ​​used in relay nodes, sending nodes and destination nodes.

7. A joint coding apparatus under a relay channel model, characterized in that, include: The encoding unit is used to acquire the source sequence and source statistical characteristics. Based on the preset dual-original-mode graph LDPC joint encoding base matrix, it generates a joint encoding check matrix through the edge expansion algorithm, and performs joint encoding on the source sequence to obtain a system form encoding sequence, wherein the encoding sequence contains 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, construct the transmitting node transmission sequence, and broadcast the transmitting node transmission sequence to the relay node and the destination node under the total transmission energy constraint. The recovery unit is used to receive signals from the transmitting node at the relay node, perform log-likelihood ratio initialization and confidence propagation decoding based on partial variable node knowns and equal probability priors, recover all information bits and check bits, and then construct a relay forwarding sequence mainly based on increasing check bits according to the degree distribution structure of the same joint coding check matrix, and send it to the destination node. The decoding unit is used to jointly receive signals from the transmitting node and the relay node at the destination node, perform joint decoding based on log-likelihood ratio initialization and confidence propagation based on different channel observations and variable node transmission states, and output the final decoding result. The feedback unit is used to obtain the decoding performance of the destination node under different energy allocation ratios, and dynamically adjusts the bit decomposition ratio and energy allocation ratio of the sending node and the relay node through traversal or optimization algorithms.

8. A joint coding device under a relay channel model, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program that can be executed by the processor to implement a joint coding method under a relay channel model as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The device contains a computer program that can be executed by a processor of the device in which the computer-readable storage medium is located, to implement the joint coding method under a relay channel model as described in any one of claims 1 to 6.

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