A memory system includes an encoder and a decoder. The encoder is configured to generate multi-dimensionally-coded data to be written into the non-volatile memory. Data bits of the multi-dimensionally-coded data are grouped into first and second dimensional codes with respect to first and second dimensions, respectively. The decoder is configured to, with respect to each of the first and second dimensional codes included in read multi-dimensionally-coded data, generate a syndrome value of the dimensional code, generate low-reliability location information, generate a soft-input value based on the syndrome value and the low-reliability location information, decode the dimensional code through correction of the dimensional code using the soft-input value, and store modification information indicating a bit of the dimensional code corrected through the correction and reliability information indicating reliability of the correction. The decoder generates the soft-input value also based on the modification information and the reliability information in the memory.

Exemplary methods, apparatuses, and systems include receiving a request for a segment of data. The requested segment data is one of a plurality of segments of data in a stripe of data. A failure to decode the requested segment is detected. Each of the plurality of segments in the stripe other than the requested segment are read. Reading each segment includes reading raw encoded data and attempting to decode the raw encoded data, the result of reading each segment including decoded data when decoding is successful and the raw encoded data when decoding fails. A combined result of each read is generated. The combining includes combining decoded data for segments that were successfully decoded and the raw encoded data for segments for which decoding failed. A statistical model for the requested segment is updated using the combined result. The requested segment is decoded using the updated statistical model.

A memory system includes an encoder and a decoder. The encoder is configured to generate multi-dimensionally-coded data to be written into the non-volatile memory. Data bits of the multi-dimensionally-coded data are grouped into first and second dimensional codes with respect to first and second dimensions, respectively. The decoder is configured to, with respect to each of the first and second dimensional codes included in read multi-dimensionally-coded data, generate a syndrome value of the dimensional code, generate low-reliability location information, generate a soft-input value based on the syndrome value and the low-reliability location information, decode the dimensional code through correction of the dimensional code using the soft-input value, and store modification information indicating a bit of the dimensional code corrected through the correction and reliability information indicating reliability of the correction. The decoder generates the soft-input value also based on the modification information and the reliability information in the memory.

A channel decoding method is provided. The method includes storing, in a memory, a set of first log likelihood ratio (LLR) values corresponding to bits of a codeword generated by modulation of a channel-encoded signal; changing, into a preset value, at least one LLR value corresponding to previously defined bits of the codeword from among the set of the first LLR values, to generate a set of second LLR values; and performing forward error correction (FEC) based on the set of the second LLR values and an FEC code, to estimate the bits of the codeword, in which the FEC code comprises a constraint code for constricting a previously defined structural correlation between the bits of the codeword.

For low complexity error correction, a decoder modifies each reliability metric of an input data stream with a random perturbation value. The reliability metric comprises a weighted sum of a channel measurement for the input data stream and parity check results for the input data stream. In addition, the decoder may generate an output data stream as a function of the reliability metrics.

A decoding method includes: receiving a plurality of subcarrier signals each including encoded data; acquiring a predetermined amount of data from each of the plurality of subcarrier signals; correcting errors in the plurality of subcarrier signals by performing decoding arithmetic processing on the respective predetermined amounts of data acquired from the plurality of subcarrier signals in a time-division manner; and causing the decoding arithmetic processing to be consecutively performed on each of the predetermined amounts of data a predetermined number of times.

A decoding method for low density parity check (LDPC) code, used to decode an input signal into a correct codeword according to a predetermined LDPC matrix, is provided. The method includes performing a plurality of decoding attempts according to the LDPC matrix within a predetermined number of decoding attempts, the plurality of decoding attempts at least including a first decoding attempt with use of a first decoding schedule and a second decoding attempt with use of a second decoding schedule. The second decoding attempt is adjacently subsequent to the first decoding attempt. The first decoding schedule as a group is not included in the second decoding schedule.

A method and apparatus for decoding quasi-cyclic LDPC codes using a vertical layered iterative message passing algorithm. The algorithm of the method improves the efficiency of the check node update by using one or more additional magnitudes, predicted with predictive magnitude maps, for the computation of messages and update of the check node states. The method allows reducing the computational complexity, as well as the storage requirements, of the processing units in the check node update. Several embodiments for the apparatus are presented, using one or more predictive magnitude maps, targeting significant savings in resource usage and power consumption, while minimizing the impact on the error correction performance loss.

According to one embodiment, a controller includes a decoder, calculation section, table creation, and control section. The decoder converts ECC frames into likelihood information based on a set table, generates decoded ECC frames by decoding using the likelihood information and switches the set table when there is an ECC frame in which the decoding is unsuccessful. The calculation section generates calculation data based on an ECC frame of calculation target among the decoded ECC frames and its ECC frame before decoded. The table creation section sets the new table to the decoder based on the calculation data. The control section controls the calculation target so that a calculation in the calculation section is not repeated for an ECC frame in which the decoding is successful.

A low-density parity check (LDPC) decoding apparatus for performing shuffle decoding includes: an input wrapper, for receiving input data and padding the input data; an LDPC decoder, coupled to the input wrapper, for receiving the padded input data, performing a plurality of iterations of LDPC decoding upon the padded input data to generate channel values corresponding to the padded input data, and outputting a hard decision channel value in a final iteration; and an initialization circuit, coupled to the LDPC decoder, for receiving the input data in a first iteration of the plurality of iterations, storing the input data into an ordered set data, and immediately sending the ordered set data to the LDPC decoder.