Magnetic Disk Read Channel Parameter Adaptation
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Solution Overview
Problem
Magnetic disk devices face challenges in efficiently re-learning parameters and minimizing retry times due to read errors caused by drift off write and adjacent track interference, leading to increased noise and signal degradation, which results in prolonged learning processes and potential data loss from timeouts.
Innovation Solution
A magnetic disk device with a read channel that includes a processor to detect read errors, determine error sectors, perform training reads on sectors within a predetermined error range, and adjust parameters based on the results to minimize retry times and efficiently re-learn parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If parameters are optimized for each magnetic head and zone before shipment, then read performance is improved for normal sectors, but the optimized parameters no longer work for error sectors affected by DOW and ATI
Solution Approach 1:
The patent implements dynamic parameter adjustment by performing training reads on error sectors to relearn parameters specific to those sectors. The system transitions from static pre-optimized parameters to dynamic parameter adaptation based on actual error sector characteristics, allowing the read channel to adjust FIR filter coefficients and other parameters specifically for degraded sectors.
Solution Approach 2:
The patent changes parameters by varying training read lengths and selecting different parameter sets based on error sector identification. The system modifies read channel parameters including FIR filter coefficients and training lengths adaptively, changing them from the original optimized values to new values learned from error sector training reads.
2Reliability
If re-learning parameters using the error sector itself is performed, then error recovery rate is improved, but retry time is prolonged
Solution Approach 1:
The patent applies partial action by performing training reads on selected error sectors rather than all sectors. The system identifies specific error sectors and performs parameter relearning only on those, rather than universally relearning parameters across the entire storage medium, thus reducing overall retry time while maintaining error recovery effectiveness.
Solution Approach 2:
The patent implements preliminary action by performing training reads and parameter relearning before actual data read operations on error sectors. The system proactively identifies error sectors and pre-adjusts parameters through training reads, so that when actual data reading occurs, the parameters are already optimized, reducing the time penalty during critical data operations.
3Measurement precision
If training read length is increased to improve parameter re-learning accuracy, then parameter accuracy is improved, but processing time increases and timeout risk increases
Solution Approach 1:
The patent implements dynamic training length adjustment by varying the training read length based on error sector characteristics and required parameter accuracy. The system adapts the training length from fixed values to variable lengths, selecting appropriate lengths that balance accuracy requirements with time constraints, thereby optimizing the trade-off between parameter accuracy and processing time.
Solution Approach 2:
The patent changes the training read length parameter adaptively based on error sector identification and recovery requirements. The system modifies this parameter from static to dynamic, adjusting it according to the specific error conditions and the amount of parameter relearning needed, thus optimizing both accuracy and time efficiency.
Data Source
AI summary
A magnetic disk device includes a magnetic disk, a read head for reading data from sectors and tracks of the magnetic disk, a read channel including a first circuit configured to process an output signal from the read head according to a value of a parameter, and processor. The processor is configured to, upon detection of a read error while the read head is reading data from an error sector of an error track, determine an error amount in each sector in the error track, select from the error track a plurality of sectors having an error amount that is within a predetermined range from an error amount of the error sector, perform a training read on the selected sectors, determine a new value of the parameter based on the training read, and set the new value of the parameter for the read channel.