Embodiments herein relate to e.g., a method performed by a network node for handling a received signal in a communication network. The network node includes at least two processing cores connected via a bus system for handling the received signal. The network node receives input bits associated with the received signal and permutes the received input bits into input bits of permuted order taking at least number of processing cores into account. The network node further decodes the input bits of the permuted order and re-permutes the decoded input bits into original order.

Embodiments of the invention provide an elementary check node processing unit (300) implemented in a check node processing unit of a non-binary error correcting code decoder, the elementary check node processing unit (300) being linked to a variable node processing unit (305) and being configured to receive a first message and a second message, each message comprising at least two components. The elementary check node processing unit (300) comprises a calculation unit (301) which determines two or more auxiliary components from the components comprised in the first message and from the components comprised in the second message, an auxiliary component comprising an auxiliary reliability metrics. The calculation unit (301) also determines, in association with each of the two or more auxiliary components, decoding performance values. The elementary check node processing unit (300) also comprises a selection unit (303) which selects, among the two or more auxiliary components, the auxiliary component that is associated with the optimal decoding performance values and determines an offset value from the auxiliary reliability metrics comprised in the selected auxiliary component. The elementary check node processing unit (300) then transmits the offset value and a selected set of auxiliary components among the two or more auxiliary components to the variable node processing unit (305).

An error correction circuit includes a memory that stores at least one decoding parameter, a low density parity check (LDPC) decoder that includes a first variable node storing one bit of the data, receives the at least one decoding parameter from the memory, decides a degree of the first variable node based on the at least one decoding parameter, and decides a decoding rule necessary for decoding of the one bit based on the degree of the first variable node, and an adaptive decoding controller that outputs corrected data based on a decoding result of the LDPC decoder.

Provided are a decoding method, a decoding device and a decoder. The method includes: setting a decoder parallelism P, and splitting soft information of a block to be decoded according to the parallelism P; performing decoding calculation on the block to be decoded according to the split information, and outputting decoded hard bit information; and recombining the hard bit information according to the parallelism P.

Methods and apparatus for decoding LDPC code provide that an LDPC code may be represented as a Tanner graph comprising bit nodes and check nodes and connections between them. A configurable LDPC decoder supporting many different LDPC codes having any sub-matrix size includes several independently addressable memories which are used to store soft decision data for each bit node. The decoder further includes a number P of check node processing systems which generate updated soft decision data. The updated values are then passed back to the memories via a shuffling system. If the number of check nodes processed in parallel by the check node processing systems is P.sub.CNB (where P≥P.sub.CNB) and the soft decision data for a bit node is of word size q bits, the total width of the independently addressable memories is larger than P.sub.CNB*q bits.

The present disclosure includes apparatuses and methods related to stopping criteria for layered iterative error correction. A number of methods can include receiving a codeword with an error correction circuit, iteratively error correcting the codeword with the error correction circuit including parity checking the codeword on a layer-by-layer basis and updating the codeword after each layer. Methods can include stopping the iterative error correction in response to a parity check being correct for a particular layer.

Certain aspects of the present disclosure generally relate to methods and apparatus for decoding low-density parity check (LDPC) codes, for example, using a parity check matrix having full row-orthogonality. An exemplary method for performing low-density parity-check (LDPC) decoding includes receiving soft bits associated to an LDPC codeword and performing LDPC decoding of the soft bits using a parity check matrix, wherein each row of the parity check matrix corresponds to a lifted parity check of a lifted LDPC code, at least two columns of the parity check matrix correspond to punctured variable nodes of the lifted LDPC code, and the parity check matrix has row orthogonality between each pair of consecutive rows that are below a row to which the at least two punctured variable nodes are both connected.

This invention presents a method and apparatus for vertical layered finite alphabet iterative decoding of low-density parity-check codes (LDPC) which operate on parity check matrices that consist of blocks of sub-matrices. The iterative decoding involves passing messages between variable nodes and check nodes of the Tanner graph that associated with one or more sub-matrices constitute decoding blocks, and the messages belong to a finite alphabet. Various embodiments for the method and apparatus of the invention are presented that can achieve very high throughputs with low hardware resource usage and power.

A computer-implemented method includes: receiving a code word sequence whose digit quantity is n; determining a check matrix of an order m×n, where a base matrix of the check matrix is a matrix of an order m.sub.b×n.sub.b; setting L variable nodes based on the base matrix, where L is greater than or equal to a quantity of values not equal to 1 in a row with a maximum quantity of values not equal to −1 in the base matrix; separately mapping valid submatrices in each layer of a check node to the L variable nodes; sending, to each of the L variable nodes that were mapped, data corresponding to each valid submatrix in each layer of the check matrix; and performing a corresponding operation in a layered normalized min-sum decoding algorithm by the L variable nodes using the data that was sent.

This invention presents a method and the corresponding hardware apparatus for decoding LDPC codes using a vertical layered (VL) iterative message passing algorithm. The invention operates on quasi-cyclic LDPC (QC-LDPC) codes, for which the non-zero circulant permutation matrices (CPMs) are placed at specific locations in the parity-check matrix of the codes, forming concentrated clusters of CPMs. The purpose of the invention is to take advantage of the organization of CPMs in clusters in order to derive a specific hardware architecture, consuming less power than the classical VL decoders. This is achieved by minimizing the number of read and write accesses to the main memories of the design.