Abstract: Example systems, read channels, and methods provide states equalization for a digital data signal in preparation for a soft output detector. The states equalizer determines a set of signal values from the digital data signal and filters the set of signal values through a set of finite impulse response filters configured to generate a set of state values for a target signal value, where each filter corresponds to a potential state of the target signal value. Based on the state values, a set of probabilities for possible states is determined and used to populate a decision matrix for a soft output detector.

Abstract: Example control circuitry, data storage devices, and methods to provide a spiral data track format that is different from the underlying servo track format are described. The data storage device may include a storage medium configured with a plurality of tracks in at least one continuous spiral pattern and a head actuated over the storage medium. The data tracks may be written to the storage medium with track lengths that are different than a single revolution of the storage medium.

Abstract: Example channel circuits, data storage devices, and methods for using an adjustable code rate based on an extendable parity code matrix based on write verification determining extended parity are described. A data unit with a base set of parity bits may be written to a non-volatile storage medium and then read back for write verification. The data unit may be decoded using the base set of parity bits and corresponding primary parity matrix. Based on the decoding of the write verification read signal, a number of parity bits for an extended set of parity bits may be determined and the extended set of parity bits may be stored to an extended parity storage location for use during subsequent read operations.

Abstract: Example channel circuits, data storage devices, and methods for asynchronous sampling from an oversampled analog-to-digital converter are described. The channel circuit may include an analog-to-digital converter configured to generate an oversampled digital signal from an analog data signal using a sample rate that is an integer multiple of the baud rate of the channel circuit. A digital sample interpolator may then interpolate interpolated digital signal values from multiple signal values of the oversampled digital signal and select values at baud rate to generate a baud rate digital signal. The baud rate digital signal may be used by an iterative detector in a timing loop and, once a target timing is achieved, for the iterative detector to detect data bits from the interpolated digital signal.

Abstract: Example systems, read channels, and methods provide states equalization for a digital data signal in preparation for a soft output detector. The states equalizer determines a set of signal values from the digital data signal and filters the set of signal values through a set of finite impulse response filters configured to generate a set of state values for a target signal value, where each filter corresponds to a potential state of the target signal value. Based on the state values, a set of probabilities for possible states is determined and used to populate a decision matrix for a soft output detector.

Abstract: Example read channel circuits, data storage devices, and methods to provide overlapping processing of data tracks are described. The data storage device may include media configured with a plurality of tracks in a concentric or continuous pattern. The read signal for a data track may be processed using error correction codes (ECC) as it is read during a first track read operation period. Some portion of its data sectors may need additional ECC postprocessing after the first track is initially received and processed by the read channel circuit. While the read signal for a next data track is being read and processed, the read channel circuit may continue postprocessing of the portion of data sectors from the first track during the second track read operations. Various decision parameters for managing the data stream, additional postprocessing time, and rereading tracks for data recovery are also described.

Abstract: Example control circuitry, data storage devices, and methods to provide a spiral data track format that is different from the underlying servo track format are described. The data storage device may include a storage medium configured with a plurality of tracks in at least one continuous spiral pattern and a head actuated over the storage medium. The data tracks may be written to the storage medium with track lengths that are different than a single revolution of the storage medium.

Abstract: Example channel circuits, data storage devices, and methods for using an adjustable code rate based on an extendable parity code matrix are described. Data units may be read from a storage medium. Multiple sets of parity bits may be available for different data units, different sets of parity bits having a different number of parity bits corresponding to different parity matrices and desired code rates. A primary parity matrix may provide a base code rate and one or more extended parity matrices may provide increased code rates based on additional rows for increased decoding. Error correction code (ECC) decoding may be selectively performed based on the different sets of parity bits and corresponding parity matrices, resulting in the output of a decoded data units based on the data units from the read signal.

Abstract: Example systems, read channels, and methods provide bit value detection from an encoded data signal using a neural network soft information detector. The neural network detector determines a set of probabilities for possible states of a data symbol from the encoded data signal. A soft output detector uses the set of probabilities for possible states of the data symbol to determine a set of bit probabilities that are iteratively exchanged as extrinsic information with an iterative decoder for making decoding decisions. The iterative decoder outputs decoded bit values for a data unit that includes the data symbol.

Abstract: Various illustrative aspects are directed to a data storage device comprising data tracks N and N?1, and one or more processing devices, configured to identify, during a track write on the data track N, a write abort event based upon an expected risk for the data track N?1 exceeding a risk threshold, read one or more sectors of the data track N?1 and collect one or more corresponding sector metrics, verify the one or more sectors based upon the collected sector metrics, wherein the verifying comprises assigning each of the one or more sectors as one of a readable or a non-readable sector, and continue the track write on the data track N upon determining each of the one or more sectors is a readable sector, or recovering and relocating the data track N?1 based on determining at least one of the sectors is a non-readable sector.

Abstract: Example read channel circuits, data storage devices, and methods to provide overlapping processing of data tracks are described. The data storage device may include media configured with a plurality of tracks in a concentric or continuous pattern. The read signal for a data track may be processed using error correction codes (ECC) as it is read during a first track read operation period. Some portion of its data sectors may need additional ECC postprocessing after the first track is initially received and processed by the read channel circuit. While the read signal for a next data track is being read and processed, the read channel circuit may continue postprocessing of the portion of data sectors from the first track during the second track read operations. Various decision parameters for managing the data stream, additional postprocessing time, and rereading tracks for data recovery are also described.

Abstract: Various illustrative aspects are directed to a data storage device comprising data tracks N and N?1, and one or more processing devices, configured to measure signal to noise ratio (SNR) metrics for corresponding sectors of at least one of the data tracks N?1 and N, where the measuring is based at least in part on reading one or more of the data tracks N and N?1 using one or more read offsets, estimate a position of at least one of the data tracks based on measuring the one or more SNR metrics, and reconstruct one or more of risk values for at least a portion of the data track N?1 based on the one or more SNR metrics for the data track N?1, and a position error signal (PES) for at least one of the data tracks N?1 and N based on the corresponding estimated positions.

Abstract: Example channel circuits, data storage devices, and methods for using an extendable parity code matrix are described. A data unit may be read from a storage medium. Multiple sets of parity bits may be available for the data unit, each set of parity bits having a different number of parity bits corresponding to different parity matrices, including a primary parity matrix and at least one extended parity matrix. The extended parity matrix includes the primary parity matrix and additional rows for increased decoding. Error correction code (ECC) decoding may be selectively performed based on the different sets of parity bits and corresponding parity matrices, resulting in the output of a decoded data unit based on the data unit from the read signal.

Abstract: Various illustrative aspects are directed to a data storage device comprising data tracks N and N?1, and one or more processing devices, configured to measure signal to noise ratio (SNR) metrics for corresponding sectors of at least one of the data tracks N?1 and N, where the measuring is based at least in part on reading one or more of the data tracks N and N?1 using one or more read offsets, estimate a position of at least one of the data tracks based on measuring the one or more SNR metrics, and reconstruct one or more of risk values for at least a portion of the data track N?1 based on the one or more SNR metrics for the data track N?1, and a position error signal (PES) for at least one of the data tracks N?1 and N based on the corresponding estimated positions.

Abstract: Disclosed are systems and methods for providing programming of multi-level memory cells using an optimized multiphase mapping with a balanced Gray code. A method includes programming, in a first phase, a first portion of data into memory cells in a first-level cell mode. The method may also include reading, from the memory cells, the programmed first portion of the data. The method may also include programming, in a second phase, a second portion of the data into the memory cells in a second-level cell mode, wherein programming the second phase is based on applying, to the read first portion of the data, a mapping from the first-level cell mode to the second-level cell mode. The mapping may be selected based on minimizing an average voltage change of the memory cells from the first to second phase while maintaining a balanced Gray code.

Abstract: Example systems, read channel circuits, data storage devices, and methods to provide signal correction based on soft information in a read channel are described. The read channel circuit includes a soft output detector, such as a soft output Viterbi algorithm (SOVA) detector, and a signal correction circuit. The soft output detector passes detected data bits and corresponding soft information to the signal correction circuit. The signal correction circuit uses the soft information to determine a signal correction value, which is combined with input signal to return a corrected signal to the soft output detector for a next iteration. In some configurations, the signal correction value may compensate for DC offset, AC coupling poles, and/or signal asymmetries to reduce baseline wander in the read channel.

Abstract: Example systems, read channel circuits, data storage devices, and methods to provide signal correction based on soft information in a read channel are described. The read channel circuit includes a soft output detector, such as a soft output Viterbi algorithm (SOVA) detector, and a signal correction circuit. The soft output detector passes detected data bits and corresponding soft information to the signal correction circuit. The signal correction circuit uses the soft information to determine a signal correction value, which is combined with input signal to return a corrected signal to the soft output detector for a next iteration. In some configurations, the signal correction value may compensate for DC offset, AC coupling poles, and/or signal asymmetries to reduce baseline wander in the read channel.

Abstract: Example systems, read channel circuits, data storage devices, and methods to use inter-symbol interference message passing (ISI-MP) data in a read channel are described. The read channel circuit includes a soft output detector, such as a soft output Viterbi algorithm (SOVA) detector, configured to determine both the first most likely and second most likely sets of symbols and output inter-symbol interference data based on the adjacent symbols and corresponding ISI in each set of symbols. The inter-symbol interference data may be used by an ISI-MP circuit configured to model ISI-MP and provide feedback to an iterative decoder during local iterations.

Abstract: Storage device programming methods, systems and devices are described. A method may generate a mapping of data based on a set of data, the mapping of data including a first mapped data and a second mapped data. The method may include performing a first programming operation to write, in a first mode, the first mapped data to the memory device. The method may include storing the second mapped data to a cache. The method may include generating a second set of data, based on an inverse mapping of the mapping of data including the second mapped data from the cache and the first mapped data from the memory device, for writing, in a second mode, to the memory device, wherein the second set of data includes the set of data, and the first mode and the second mode correspond to different modes of writing to the memory device.

Abstract: Systems and methods for read level tracking and optimization are described. Pages from a wordline of a flash memory device read and the raw page data read from the wordline may be buffered in a first set of buffers. The raw page data for each of the pages may be provided to a decoder for decoding and the decoded page data for each of the pages buffered in a second set of buffers. First bin identifiers may be identified for memory cells of the wordline based on the raw page data and second bin identifiers may be identified for the memory cells of the wordline based on the decoded page data. Cell-level statistics may be accumulated based on the first bin identifiers and the second bin identifiers, and a gradient may be determined for respective read levels based on decoding results for each of the pages and the cell-level statistics. Settings for the read levels may be configured in the flash memory device based on the determined gradients.