According to one embodiment, a memory controller includes: a memory I/F that reads a codeword written in a NAND memory as any one of hard-bit information, first soft-bit information, and second soft-bit information; a codeword processor that generates a codeword of an first soft-decision value from the first soft-bit information, and generates a codeword of a second soft-decision value from the second soft-bit information; a first decoder that executes hard-decision decoding on a codeword of a hard-decision value configured from the hard-bit information; a second decoder that executes first soft-decision decoding on the codeword of the first soft-decision value; and a third decoder that executes second soft-decision decoding on the codeword of the second soft-decision value, wherein the first soft-bit information includes information having a first number of bits greater than the number of bits of the hard-bit information, and the second soft-bit information includes information having a second number of bits greater than the number of bits of the first soft-bit information.

A data storage device is disclosed comprising a storage medium. Input data is encoded according to at least one channel code constraint to generate first data and second data. The first data is encoded into a first codeword, and the second data is encoded into a second codeword, wherein a first code rate of the first codeword is less than a second code rate of the second codeword. The first codeword and the second codeword are interleaved to generate an interleaved codeword, and the interleaved codeword is written to the storage medium.

SISO decoding of a reception signal having a scrambled symbol arrangement is realized using a process having reduced complexity. Coordinates are generated for a reference point obtained by scrambling and mapping a symbol number not a symbol reference point position. This reference point simulates transmission-side scrambling and is generated for each symbol number by a first mapping unit. Because the binary expression of a corresponding original signal number is retained, a bit likelihood calculation unit can easily calculate a bit likelihood based on the distance between the reference point and a reception signal. The calculated bit likelihood is then deinterleaved and subjected to SISO error-correcting decoding. The thus obtained bit likelihood is then reinterleaved and used to calculate a symbol probability. Soft symbols are generated through the multiplication of all the calculated symbol probabilities by corresponding reference points output by a second mapping unit similar to the first mapping unit.

A soft decision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and soft bits. The soft bits may be utilized by a soft audio decoder to determine whether the digital signal should be decoded or muted. The soft bits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the soft bits may indicate confidence in the strength of the hard bit generation. The soft decision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.

A soft decision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and soft bits. The soft bits may be utilized by a soft audio decoder to determine whether the digital signal should be decoded or muted. The soft bits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the soft bits may indicate confidence in the strength of the hard bit generation. The soft decision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.

A method and data storage system receives a confidence vector for a non-binary symbol value read from a memory cell of a non-volatile memory device, where the confidence vector includes a first plurality of confidence values and transforms the first plurality of confidence values into a first plurality of likelihood values using a forward tensor-product transform. A respective binary message passing decoding operation is performed with each of the first plurality of likelihood values to generate a second plurality of likelihood values, and the second plurality of likelihood values are transformed into a second plurality of confidence values of the confidence vector using a reverse tensor-product transform.

A controller for a solid state drive is proposed. The solid state drive comprises memory cells each one for storing a symbol among a plurality of possible symbols that the memory cell is designed to store. The controller comprises a unit for encoding information bits into encoded bits; a unit for mapping the encoded bits into the symbols, wherein the symbols are determined based on a plurality of allowed symbols, among the possible symbols, that the memory cells are allowed to store, whereas the symbols, among the possible symbols, other than the allowed symbols define forbidden symbols not allowed to be stored in the memory cells; a unit for demapping read symbols and for providing an indication of the reliability of the read symbols based on the forbidden symbols; and a unit for soft decoding the read symbols according to the reliability indication thereby obtaining the information bits.

A soft output detector is programmed with a first set of parameters. Soft information is generated according to the first set of parameters, including likelihood information that spans a maximum likelihood range. Error correction decoding is performed on the soft information generated according to the first set of parameters. In the event decoding is unsuccessful, the soft output detector is programmed with a second set of parameters, soft information according is generated to the second set of parameters (including likelihood information that is scaled down from the maximum likelihood range), and error correction decoding is performed on the soft information generated according to the second set of parameters.

SISO decoding of a reception signal having a scrambled symbol arrangement is realized using a process having reduced complexity. Coordinates are generated for a reference point obtained by scrambling and mapping a symbol number not a symbol reference point position. This reference point simulates transmission-side scrambling and is generated for each symbol number by a first mapping unit. Because the binary expression of a corresponding original signal number is retained, a bit likelihood calculation unit can easily calculate a bit likelihood based on the distance between the reference point and a reception signal. The calculated bit likelihood is then deinterleaved and subjected to SISO error-correcting decoding. The thus obtained bit likelihood is then reinterleaved and used to calculate a symbol probability. Soft symbols are generated through the multiplication of all the calculated symbol probabilities by corresponding reference points output by a second mapping unit similar to the first mapping unit.

A soft decision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and soft bits. The soft bits may be utilized by a soft audio decoder to determine whether the digital signal should be decoded or muted. The soft bits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the soft bits may indicate confidence in the strength of the hard bit generation. The soft decision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.