Read Threshold Voltage Tracking Using Syndrome Weights
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Solution Overview
Problem
Existing solid state storage devices face challenges in maintaining consistent read threshold voltages due to variations and shifts over time, leading to data errors and the need for improved adaptive techniques to adjust these voltages effectively.
Innovation Solution
Independent read threshold voltage tracking techniques using syndrome weights are employed to identify optimum values for multiple read threshold voltages, allowing for adjustments that minimize syndrome weights and improve decoding accuracy, thereby reducing bit error rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing adaptive tracking algorithms are used to adjust read threshold voltages, then the system can adapt to changes in read threshold voltages over time, but the complexity of the adjustment process increases and the number of read operations required grows exponentially
Solution Approach 1:
The patent segments the read threshold voltage adjustment process into independent tracking operations for each read threshold voltage. Instead of adjusting multiple dependent read threshold voltages simultaneously as a single complex operation, the method independently tracks and adjusts each read threshold voltage separately. This segmentation reduces the overall complexity from exponential to linear in the number of read operations, while maintaining the ability to adapt to changes in read threshold voltages over time.
2Productivity
If multiple read threshold voltages are adjusted simultaneously, then the system can maintain performance across multiple pages, but the number of read operations required increases exponentially
Solution Approach 1:
The patent divides the adjustment of multiple read threshold voltages into separate independent tracking operations, one for each read threshold voltage. This allows the system to adjust multiple read threshold voltages for multi-page reads without requiring exponential read operations, as each voltage is tracked and adjusted independently through linear operations.
Solution Approach 2:
The patent changes the approach from simultaneous adjustment of multiple read threshold voltages to independent tracking of each voltage parameter separately. By treating each read threshold voltage as an independent parameter to be optimized, the system achieves multi-page read efficiency without the exponential time cost of simultaneous adjustment.
3Device complexity
If read threshold voltages are not adjusted, then the system operates with simple fixed voltage levels, but data errors increase due to voltage shifts over time
Solution Approach 1:
The patent implements a self-service mechanism where the system automatically tracks and adjusts read threshold voltages based on syndrome weights from decoding operations. The independent tracking algorithm allows each read threshold voltage to self-adjust based on its own performance metrics, eliminating the need for complex external control mechanisms while maintaining high data accuracy despite voltage shifts over time.
Solution Approach 2:
The patent employs feedback through syndrome weight measurements from decoding operations to continuously monitor and adjust read threshold voltages. Each read threshold voltage receives feedback from its own decoding performance, enabling automatic adaptation to voltage shifts over time while keeping the adjustment mechanism relatively simple through independent tracking.
Data Source
AI summary
Read threshold voltage tracking techniques are provided for multiple dependent read threshold voltages using syndrome weights. One method comprises reading codewords of multiple pages using different first read threshold voltages and a default second read threshold voltage; decoding read values for the multiple pages for the different first read threshold voltages and the default second read threshold voltage; aggregating a syndrome weight for each failed decoding attempt for the different first read threshold voltages; identifying a selected first read threshold voltage using a corresponding syndrome weight; reading codewords of the multiple pages using the selected first read threshold voltage and different second read threshold voltages; decoding read values for the selected first read threshold voltage and the different second read threshold voltages; aggregating the syndrome weight for the different second read threshold voltages; and identifying a selected second read threshold voltage using a corresponding syndrome weight.