A data storage device is disclosed comprising a non-volatile storage medium (NVSM). A reliability metric for each symbol of each of a plurality of codewords read from the NVSM is generated, and a number of erasures for a first codeword are generated, wherein the number of erasures exceeds the correction power of the first codeword. A reliability metric of the first codeword is modified corresponding to one of the erasures. The reliability metrics for each codeword including the modified reliability metrics of the first codeword are first iteratively processed using a low density parity check (LDPC) type decoder, thereby first updating the reliability metric for each symbol of each codeword. The reliability metrics for the first codeword are second updated using the parity sector, and the second updated reliability metrics for the first codeword are second iteratively processed using the LDPC-type decoder.

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 data storage device is disclosed comprising a non-volatile storage medium (NVSM). A reliability metric for each symbol of each of a plurality of codewords read from the NVSM is generated, and a number of erasures for a first codeword are generated, wherein the number of erasures exceeds the correction power of the first codeword. A reliability metric of the first codeword is modified corresponding to one of the erasures. The reliability metrics for each codeword including the modified reliability metrics of the first codeword are first iteratively processed using a low density parity check (LDPC) type decoder, thereby first updating the reliability metric for each symbol of each codeword. The reliability metrics for the first codeword are second updated using the parity sector, and the second updated reliability metrics for the first codeword are second iteratively processed using the LDPC-type decoder.

The disclosed embodiments are directed to systems, devices, and methods for iterative message-passing decoding. In one embodiment, a method is disclosed comprising decoding a first codeword at a storage device using a detector and a decoder, the first codeword comprising a set of symbols from a first set of codewords; assigning, via the decoding, a set of confidence levels for each symbol in the first codeword; transmitting, by the storage device, the confidence levels to an iterative decoder; generating, by the iterative decoder, a second codeword based on the set of confidence levels, the second codeword excluding at least one symbol in the set of symbols; and iteratively decoding, by the iterative decoder, the second codeword using an erasure decoder; and transmitting, by the iterative decoder, soft information generated by the erasure decoder to the storage device for subsequent decoding by the storage device.

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 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.

In one embodiment, a system provides for optimizing an error rate of data through a communication channel. The system includes a data generator operable to generate a training sequence as a Markov code, and to propagate the training sequence through the communication channel. The system also includes a Soft Output Viterbi Algorithm (SOVA) detector operable to estimate data values of the training sequence after propagation through the communication channel. The system also includes an optimizer operable to compare the estimated data values to the generated training sequence, to determine an error rate based on the comparison, and to change the training sequence based on the Markov code to lower the error rate of the data through the communication channel.

Systems and methods are provided for decoding a codeword using an iterative decoding process. The systems and methods include receiving a codeword comprising a plurality of symbols, and concurrently processing the received codeword with a detector and a decoder based in part on extrinsic information associated with the plurality of symbols to obtain updated extrinsic information. The systems and methods further include modifying the extrinsic information associated with the plurality of symbols based on the updated extrinsic information, and repeating the processing and modifying steps until a stopping criterion is met.

A method of processing a digitally encoded radio signal (102) comprising a bit to be determined is disclosed. The method comprises correlating a first bit sequence (103) comprising the bit with a plurality of predetermined filters (104a-h) to create a first set of filter coefficients (110a-h); calculating (120) a first likelihood data set (124) comprising a likelihood of said bit having a given value for each bit position from the first set of filter coefficients. A second bit sequence (103) comprising the bit at a different position is then correlated with the filters to create a second set of filter coefficients (10a-h), from which a second likelihood data set (124) is calculated. A soft output bit (26) comprising a probability weighted bit value from data corresponding to the bit at a first and second bit positions from the first and second likelihood data sets respectively is then calculated.

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.