Adaptive Read Threshold Voltage Estimation for SSD Memory Controllers
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Solution Overview
Problem
Memory systems face challenges in determining optimal read threshold voltages, leading to read errors due to distorted or overlapping threshold voltage distributions, especially in multi-level cell technologies where program and erase cycles cause margin reduction and distribution overlap.
Innovation Solution
A system and method for adaptively determining a read threshold voltage using meta information from previous failed read data, employing mathematical models and regression analysis to estimate checksum values and bit percentages, allowing for the selection of optimal read threshold voltages for subsequent operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed read threshold voltages are used in memory systems, then device complexity is reduced and operation is simplified, but read operation reliability deteriorates due to distorted or overlapping threshold voltage distributions from program and erase cycles
Solution Approach 1:
The system performs preliminary actions by collecting meta information from previous read operations and pre-calculating statistical parameters (mean, standard deviation) of threshold voltage distributions. This preliminary analysis enables the adaptive determination of optimal read threshold voltages for subsequent operations, improving read reliability without requiring complex real-time analysis during actual read operations.
Solution Approach 2:
The patent implements dynamic adaptation by adjusting read threshold voltages based on statistically calculated parameters from previous operations. The system dynamically determines optimal thresholds using the formula Vth = μ + kσ, where μ (mean) and σ (standard deviation) are updated from collected meta information, allowing the read thresholds to adapt to changing threshold voltage distributions caused by program and erase cycles.
2Reliability
If multiple read retry operations are performed with different threshold voltages, then read operation reliability is improved, but time consumption increases due to multiple read attempts
Solution Approach 1:
The system performs preliminary statistical analysis by collecting meta information from previous read operations and calculating optimal threshold voltages in advance. This preliminary work enables the controller to select the most appropriate read threshold voltage for retry operations, reducing the number of unsuccessful read attempts and thereby decreasing overall read latency while maintaining high reliability.
Solution Approach 2:
The patent implements feedback mechanisms by continuously collecting meta information from read operations (including successful and failed reads) and using this information to adjust subsequent read threshold voltages. The controller uses the statistical parameters derived from this feedback to optimize retry operations, ensuring that each retry uses an improved threshold voltage based on previous performance, thus reducing time loss.
3Reliability
If adaptive read threshold determination using statistical analysis is implemented, then read operation reliability is improved, but computational complexity and processing time increase
Solution Approach 1:
The controller performs preliminary statistical analysis by collecting meta information from previous read operations and pre-calculating mean (μ) and standard deviation (σ) of threshold voltage distributions. This preliminary computation simplifies subsequent adaptive threshold determination, as the controller only needs to apply the straightforward formula Vth = μ + kσ using pre-computed parameters, rather than performing complex real-time statistical analysis during read operations.
Solution Approach 2:
The system implements self-service by automatically collecting meta information from its own read operations and using this information to determine optimal read thresholds without external intervention. The controller serves itself by maintaining internal statistical models and autonomously adjusting read thresholds based on its operational history, reducing the need for complex external control systems.
Data Source
AI summary
Embodiments adaptively determine a read retry threshold voltage for a next read operation using meta information collected from previous failed read data. A controller obtains meta information associated with a read operation on a select page, the meta information including a read threshold voltage set. The controller determines a mathematical model for estimating a checksum value for data associated with a next read operation, using a set function of the read threshold voltage set and a set checksum value. The controller determines a set of parameters by performing polynomial regression on the mathematical model. The controller estimates a next read threshold voltage for the next read operation based on the set of parameters.