NAND Flash Row Programming Parameters for BER and Wear Reduction
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Solution Overview
Problem
NAND flash memory devices experience increased bit-error-rate (BER) due to charge traps and retention effects, especially in high-density structures like QLC and PLC, requiring improved programming and read methods to ensure performance and reliability.
Innovation Solution
A system and method for determining optimal voltage thresholds and program parameters based on production information and adjusting these parameters across rows of non-volatile memory cells to equalize programming voltages, minimizing wear and reducing bit-error-rate through adaptive program voltage window adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple-stage programming is used to achieve accurate state programming with low standard-deviation of voltage thresholds, then manufacturing precision is improved, but programming time increases
Solution Approach 1:
The system performs preliminary determination of optimal program parameters based on production information before actual programming operations. This pre-characterization allows the system to have parameter sets ready for different cell types, eliminating the need for time-consuming real-time optimization during programming operations.
Solution Approach 2:
The system dynamically selects and adjusts program parameters based on the specific cell type being programmed. By making parameters adaptive rather than static, the system can optimize for both speed and accuracy depending on the particular memory cell characteristics without requiring multiple-stage programming for all cells.
2Device complexity
If production information from mass production is used to determine optimal program parameters, then device complexity is reduced, but measurement precision requirements increase
Solution Approach 1:
The system creates a copy or model of production characteristics by collecting and analyzing production information from mass-produced devices. This model is then used to determine optimal parameters for individual devices, avoiding the need for complex real-time measurements while maintaining accuracy through the use of representative production data.
3Reliability
If program parameters are equalized across rows, then reliability is improved, but programming flexibility is reduced
Solution Approach 1:
The system applies different program parameters to different rows based on their specific characteristics while maintaining equalization within appropriate groups. This localized optimization allows the system to improve reliability by addressing specific row issues without imposing uniform constraints on the entire memory array, thus preserving programming flexibility.
Data Source
AI summary
One or more processors of a system may determine one or more program parameters of a plurality of rows of cells of a non-volatile memory, determine a first threshold of a first parameter of each row based on the one or more program parameters of the plurality of rows, determine, by changing a programming time of each row, a set of parameters of each row that causes the first parameter not to cross the first threshold, determine a second threshold of a second parameter of each row based on production statistics of a plurality of dies as a result of mass production, adjust the programming time of each row to cause the second parameter not to cross the second threshold, and program data to a first row of the plurality of rows using the set of parameters of the first row and the adjusted programming time of the first row.