10 results about "Tanner graph" patented technology

The invention provides an LDPC (Low Density Parity Check) optimization method based on dynamic parameter adaptive coding and a Tanner graph neural network. The method comprises the following steps: acquiring a data set through a channel sensing module; the data set comprises channel state information, bit error rate statistics and QoS (Quality of Service) demand information; the collected data set is preprocessed; dividing the preprocessed data set according to a preset proportion; constructing an LSTM (Long Short Term Memory) prediction model; training and optimizing the LSTM prediction model by using the training set based on the loss function, and storing an optimal model; inputting the test set into the optimal model to predict the coding parameters of the channel transmission to obtain a prediction result of the adaptive coding parameters of the channel transmission; the method comprises the following steps: establishing an LDPC encoder and a Tanner-GNN decoder; building a joint optimization controller; the joint optimization controller is used for dynamically adjusting coding parameters through the LSTM prediction model and receiving the bit error rate BER counted by the Tanner-GNN decoder, the technical limitation of traditional coding and decoding separation optimization is broken through, and the performance of the LDPC code in a complex channel environment is remarkably improved.

A method for constructing a permutation matrix or a check matrix, a processing device, a storage medium and a coding method. The method for constructing the permutation matrix comprises: obtaining a base matrix for the permutation matrix; and performing lifting on the base matrix to obtain the permutation matrix. The lifting on the base matrix to obtain the permutation matrix comprises: obtaining a modulus graph of the base matrix, obtaining each macro ring in the modulus graph, and for each macro ring in the modulus graph, determining the size of a short ring corresponding to the macro ring in a Tanner graph of a check matrix corresponding to the permutation matrix from an equivalent cycle value ECS of the macro ring, and determining whether at least one cycle value in the macro ring needs to be set according to the size of the short ring. The method can more efficiently obtain a required permutation matrix.

The invention relates to a short code length QC-LDPC (Quasi-Cyclic Low-Density Parity-Check) code construction method based on a Stanley sequence and a genetic algorithm. According to the method, a Stanley sequence is used for forming first two rows of an index matrix meeting the condition that no four rings exist, then a genetic algorithm is used for searching a third row element which enables the index matrix to meet the requirements that the ring length is at least 8 and the number of trap sets is small, and therefore the index matrix with the girth length being at least 8 is obtained, the genetic algorithm can guarantee that the number of the trap sets is minimum, and the number of trap sets is small. And finally, the index matrix is expanded to obtain a parity check matrix of the index matrix, so that four rings and six rings do not exist in a Tanner graph of the check matrix, the number of trap sets is small, the storage space required by code words is small, and hardware implementation is easy. Simulation shows that compared with an HS-QC-LDPC code, an MT-QC-LDPC code and an SES-QC-LDPC code which have the same code rate and code length, the SS-QC-LDPC code constructed by the method has the advantages that the net coding gain is improved to a certain extent, and the constructed SS-QC-LDPC code has better waterfall region performance in a high signal-to-noise ratio region and has no obvious error leveling phenomenon.

The application discloses a method for constructing QC-LDPC code with low error floor. The method comprises the following steps: firstly, selecting random number filling matrix elements to generate an index matrix of QC-LDPC code according to an original graph, and performing girth optimization on the index matrix to minimize the number of loops with a specified degree in a Tanner graph corresponding to the matrix; and then, searching for harmful trap sets in the matrix by column through decoding simulation, and eliminating the harmful trap sets by changing the shift value of the matrix elements until all harmful trap sets with a specified size are eliminated. The method has the following advantages: firstly, the method has no special requirements on the parameters of the QC-LDPC code matrix, and supports the design of flexible code rate. Secondly, the method searches for and eliminates the harmful trap sets in the QC-LDPC code, and takes into account the optimization of the minimum girth of the code, so that the constructed QC-LDPC code has good error floor performance. The construction method disclosed by the application can generate QC-LDPC code with uncorrectable error rate lower than 10 ‑15 , and is suitable for occasions with high requirements on error correction performance, such as flash memories.

Various aspects of the present disclosure relate to enhanced encoder designs (and associated signaling), such as enhanced encoder structures for quasi-cyclic low-density parity-check (QC-LDPC) encoders. The new encoders can achieve a larger girth (e.g., length of the shortest cycle of a Tanner graph) by using permutation matrices without increasing the complexity of hardware implementations of the encoders. Thus, the enhanced encoders can facilitate use of short or limited length codes for wireless communication data channels, among other benefits.

The present application relates to a communication method and apparatus, and a readable storage medium. The method comprises: a sending end acquiring an information bit sequence, and using a generator matrix corresponding to a parity-check matrix of an LDPC code to encode the information bit sequence to obtain a codeword sequence, wherein the code length of the LDPC code is less than or equal to 36, and the girth of a Tanner graph corresponding to the parity-check matrix of the LDPC code is greater than or equal to 6; and sending the codeword sequence. By using the present application, the decoding success rate of the system can be improved, and thus the decoding performance and the transmission reliability are improved. The present application supports IEEE series protocols, such as IEEE 802.11bn / UHR protocol, IEEE 802.15 / UWB protocol, IEEE 802.11bf / sensing protocol or integrated millimeter wave / IMMW protocol. The present application can also support a spark link / nearlink standard protocol.

The invention belongs to the technical field of error correction coding and decoding, and discloses a large nuclear polarization code coding and decoding method, which comprises the following steps: generating a p-order polarization nuclear matrix candidate space set C with a polarization effect, p being greater than or equal to 3; obtaining a verification relation candidate space of each column of each polarized nuclear matrix in the C, establishing a relation among the nuclear matrixes, the verification relation and the Tanner graphs, and obtaining the Tanner graphs with the least XOR structures corresponding to each nuclear matrix in the candidate space as a candidate Tanner graph set according to the relation; a candidate Tanner graph set meeting the bit-by-bit decoding characteristic is screened out from the candidate Tanner graph set to cooperate as a finally selected Tanner graph set, and a correspondingly selected polarization nuclear matrix set is obtained; and at the sending end, performing large nuclear polarization code coding according to the polarization nuclear matrix. Correspondingly, the invention also provides a large nuclear polarization code decoding method. According to the invention, the coding and decoding complexity can be reduced on the premise of ensuring the error correction capability of the polarization code.

The application provides an LDPC optimization method based on dynamic parameter adaptive coding and a Tanner graph neural network. The method comprises the following steps: collecting a data set through a channel sensing module; the data set comprises channel state information, bit error rate statistics and service QoS requirement information; preprocessing the collected data set; dividing the preprocessed data set according to a preset ratio; constructing an LSTM prediction model; training and optimizing the LSTM prediction model based on a loss function and using a training set, and saving an optimal model; inputting a test set into the optimal model to predict the coding parameters of channel transmission, and obtaining a prediction result of the adaptive coding parameters of channel transmission; building an LDPC encoder and a Tanner-GNN decoder; building a joint optimization controller; the joint optimization controller is used for dynamically adjusting the coding parameters through the LSTM prediction model and receiving the bit error rate BER counted by the Tanner-GNN decoder. The application breaks through the technical limitation of traditional coding and decoding separation optimization, and significantly improves the performance of the LDPC code in a complex channel environment.

This invention relates to a Normalized Minimum Offset Sum (NOMS) decoding method for LDPC codes based on optimized grouped neural networks, belonging to the field of wireless communication channel coding technology. This method utilizes the topological relationship between the LDPC code base graph and the Tanner graph to transform the Tanner graph into a non-fully connected grouped neural network. It groups edges based on the base graph type and achieves parameter sharing using edge bundles. A greedy hierarchical training algorithm is used to optimize the normalization factor and offset factor round by round, obtaining dynamically adaptive parameters that adapt to each iteration stage. The optimized factors are substituted into the decoding update formula to replace the traditional fixed factors and complete the normalized minimum offset sum decoding. This invention can suppress error amplification during iteration, avoid error leveling and decoding deadlock, improve decoding accuracy while reducing computational complexity and parameter size, exhibit strong generalization ability, and can adapt to LDPC codes with different code lengths and rates under the same base graph. It also features low latency, high robustness, and engineering practicality.

The invention relates to a local decoding method of a coding modulation system adopting a constant weight former, and belongs to the technical field of information theory and coding. The method comprises the following steps: in a low density parity check (LDPC) coding modulation system adopting a constant weight shaper (CCDM), when decoding of an original minimum sum (MS) algorithm fails, performing double expansion on a connection relation of a Tanner graph based on an LDPC code on a check node UCNs which is not satisfied and a CNs connected with a variable node VNs corresponding to an unreliable bit in a CCDM code word; vNs connected with the CNs are selected through double expansion, values of corresponding positions in the original confidence vectors are locally corrected through candidate VNs, and a candidate input information vector list is generated; and re-decoding the vectors in the list one by one to obtain a decoding output result. According to the method disclosed by the invention, the error platform of the LDPC code in the coding modulation system can be reduced without remarkably increasing the calculation complexity, the error diffusion in the inverse forming process of the system is reduced, and the transmission reliability of the LDPC coding modulation system is improved.