Estimation of NAND Flash Memory Threshold Voltage Distribution for Optimum Soft-Decision Error Correction
Estimation of NAND Flash Memory Threshold Voltage Distribution for Optimum Soft-Decision Error Correction
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DOI：
10.1109/tsp.2012.2222399
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发表时间：
2013
影响因子：
5.4
通讯作者：
Dong-hwan Lee;Wonyong Sung
中科院分区：
文献类型：
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作者：
Dong-hwan Lee;Wonyong Sung
随着NAND闪存特征尺寸的减小，阈值电压信号变得不那么可靠，并且其分布随着编程-擦除（PE）周期的数量和数据保持时间而显著变化。我们已经开发了参数估计算法，以找到的阈值电压分布，这是建模为高斯混合的均值和方差。所提出的方法通过最小化测量的阈值电压值和从高斯混合模型获得的阈值电压值之间的平方欧几里德距离来找到最佳拟合参数。对于参数估计，采用基于梯度下降（GD）和Levenberg-Marquardt（LM）的方法。所开发的算法适用于模拟和真实的NAND闪存。它还表明，估计的均值和方差值的误差校正产生更好的性能相比，只更新均值的方法。
As the feature size of NAND flash memory decreases, the threshold voltage signal becomes less reliable, and its distribution varies significantly with the number of program-erase (PE) cycles and the data retention time. We have developed parameter estimation algorithms to find the means and variances of the threshold voltage distribution that is modeled as a Gaussian mixture. The proposed methods find the best-fit parameters by minimizing the squared Euclidean distance between the measured threshold voltage values and those obtained from the Gaussian mixture model. For the parameter estimation, the gradient descent (GD) and the Levenberg-Marquardt (LM) based methods are employed. The developed algorithms are applied to both simulated and real NAND flash memory. It is also demonstrated that error correction with the estimated mean and variance values yields much better performance when compared to the method that only updates the mean.