NAND Flash Bad Page Column Detection Method
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Solution Overview
Problem
Existing methods for detecting and analyzing bad pages and columns in NAND flash memory are inaccurate, leading to a decrease in available storage capacity due to false bad column identification and interference between bad pages and columns.
Innovation Solution
A method involving alternating selection and updating of bad page and column sets based on error thresholds, using strategies for interference elimination and template iteration to refine the identification of bad elements, thereby improving accuracy and available capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection methods are used to identify bad pages and columns in NAND flash, then the detection process is simple, but the identification accuracy is poor leading to false bad column identification
Solution Approach 1:
The patent applies dynamics by making the detection process adaptive and iterative. The error threshold is dynamically adjusted based on statistical analysis of read errors, and the detection repeatedly identifies bad columns multiple times with updating the bad column set. This dynamic approach allows the system to adapt to different flash memory states and improve identification accuracy without requiring overly complex static detection mechanisms.
Solution Approach 2:
The patent implements feedback mechanisms where the results of each detection iteration are used to update the bad column set, which then influences subsequent detection iterations. The error threshold is also adjusted based on feedback from statistical analysis of observed errors. This feedback loop continuously refines the identification accuracy while managing the complexity through systematic iteration rather than complex one-pass detection.
2Quantity of substance
If existing detection methods are used to identify bad pages and columns, then the detection process is fast, but the available storage capacity decreases due to false positives
Solution Approach 1:
The patent applies preliminary action by performing statistical analysis of read errors and determining an optimized error threshold before the actual bad column identification process. This preliminary step configures the detection system with optimal parameters, ensuring that subsequent identification is both accurate and reliable. The bad column set is also updated iteratively, with preliminary identification results informing subsequent refinement steps, thereby maximizing storage capacity while maintaining data integrity.
Solution Approach 2:
The patent changes parameters by adjusting the error threshold based on statistical analysis of read errors. Instead of using a fixed threshold, the system determines an optimized threshold that balances false positive reduction with reliable bad column identification. This parameter optimization allows the system to identify fewer false bad columns, thereby increasing available storage capacity while maintaining the reliability needed to guarantee data integrity through accurate bad column mapping.
3Measurement precision
If bad pages and columns are identified without considering interference between them, then the detection process is simple, but the identification accuracy is poor
Solution Approach 1:
The patent applies segmentation by separating the detection process into distinct phases: first identifying bad pages, then using that information to guide bad column identification. The bad column detection is further segmented into multiple iterations where the bad column set is updated progressively. This segmentation allows the system to account for interference between bad pages and columns without requiring overly complex simultaneous analysis of all factors.
Solution Approach 2:
The patent performs preliminary identification of bad pages before proceeding to bad column identification. This preliminary action provides crucial information about which pages are already known to be bad, allowing the subsequent column detection to account for page-level interference. The bad column set is also preliminarily initialized and then refined through iterative updates, ensuring that interference effects are systematically handled without excessive complexity.
Data Source
AI summary
An intelligent terminal, and a computer-readable storage medium is provided. The detection method includes: obtaining a column set, a page set, and a block set, and presetting a bad column set, a bad page set, an error threshold, and an initial bad block template; alternately obtaining bad page elements and bad column elements from the block set in sequence based on the error threshold, and alternately updating the bad page set and the bad column set in sequence; based on the bad column sets and the bad page sets corresponding to different error thresholds, updating the error threshold, obtaining a final column set from the bad column sets, and obtaining a final page set from the bad page sets; and obtaining a final bad block template. The present invention can reduce the impact of a bad page on a subsequent operation of selecting a bad column element.