Magnetic Disk Read Quality Index via Iterative Decoding Segmentation
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Solution Overview
Problem
Magnetic disk devices face challenges in accurately measuring read/write quality, as existing methods either prohibit repeated Viterbi and iterative decoding, leading to unreliable index acquisition, or require additional time for parameter learning during normal reading operations.
Innovation Solution
A magnetic disk device configuration that includes a Viterbi decoder, iterative decoder, and control circuits to repeatedly execute decoding and update parameters, determining the number of decoding iterations and acquiring numerical information on bit errors and parity violations to assess read/write quality without prohibiting decoding repetition, thus optimizing read/write conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of moving object
If repeated Viterbi and iterative decoding is prohibited, then parameter learning time is reduced, but read/write quality measurement reliability deteriorates
Solution Approach 1:
The patent segments the decoding process into distinct phases: an initial decoding phase where repeated Viterbi and iterative decoding are performed to acquire reliable index information, followed by a normal reading phase where decoding is performed once without repetition. This segmentation allows the system to prioritize reliability during measurement without permanently increasing the time cost for normal operations.
Solution Approach 2:
The patent implements dynamic control of the decoding process by adjusting whether repeated decoding is performed based on the operational context. The control circuit determines whether to execute repeated Viterbi and iterative decoding based on whether the current operation is a read/write quality measurement or normal reading, thereby adapting the decoding behavior to minimize time consumption while maintaining measurement reliability.
2Measurement precision
If repeated decoding is performed for index acquisition, then read/write quality measurement accuracy is improved, but measurement time increases
Solution Approach 1:
The patent performs repeated Viterbi and iterative decoding as a preliminary action during the read/write quality measurement process to acquire accurate index information before normal reading operations begin. By completing the parameter learning and index acquisition in advance during the measurement phase, the system ensures measurement accuracy without delaying subsequent normal reading operations.
Solution Approach 2:
The patent maintains continuous useful action by performing repeated decoding only when necessary for quality measurement, while allowing normal reading operations to proceed without interruption once the index is acquired. The control circuit ensures that the repeated decoding is executed continuously during measurement to gather sufficient statistical data, then stops to allow normal operations to continue uninterrupted.
3Reliability
If parameter learning is performed during normal reading, then read/write quality can be optimized, but reading productivity decreases
Solution Approach 1:
The patent segments reading operations into two distinct types: read/write quality measurement operations where repeated decoding is performed to optimize parameters, and normal reading operations where decoding is performed once for productivity. This segmentation allows the system to dedicate specific time and resources to parameter learning without interfering with the productivity of normal reading operations.
Solution Approach 2:
The patent implements dynamic adjustment of decoding behavior based on the operational mode. During read/write quality measurement, the control circuit enables repeated Viterbi and iterative decoding to optimize read/write quality. During normal reading, the control circuit disables repeated decoding to maintain high reading productivity. This dynamic switching resolves the contradiction by applying the appropriate decoding strategy to the appropriate operation type.
Data Source
AI summary
According to one embodiment, a first decoding circuit calculates likelihood information by executing Viterbi decoding using a parameter for normalizing a branch metric on a signal sequence read from a magnetic disk. The second decoding circuit generates a first bit data sequence by iterative decoding using the likelihood information, and executes a check using a parity check matrix on the first bit data sequence. The control circuit causes the first decoding circuit and the second decoding circuit to repeatedly execute decoding, and updates the parameter in accordance with a check result obtained every time the decoding by the first decoding circuit and the second decoding circuit is executed. An acquisition circuit acquires numerical information corresponding to the number of bit errors included in the first bit data sequence obtained when the number of times of executions of the decoding is equal to a first value.