LDPC Decoding Early Stopping Using Syndrome Weight Thresholds
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Solution Overview
Problem
Existing memory sub-systems perform unnecessary iterations of bit-flip LDPC decoding, leading to inefficiencies in time and resource usage, as they fail to effectively utilize syndrome weight to determine the likelihood of successful error correction.
Innovation Solution
Implementing an early stopping mechanism in the bit-flip LDPC decoding process based on syndrome weight, where the parity check component determines if the current syndrome weight meets a threshold criterion associated with each iteration, allowing for the termination of the bit-flip decoding process and the initiation of a more capable decoding process, such as Min-Sum decoding, when the syndrome weight is high.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the bit-flip LDPC decoding process completes all iterations regardless of syndrome weight, then the decoding process is simple to implement, but time and energy are wasted on unnecessary iterations
Solution Approach 1:
The patent checks the syndrome weight before each iteration to determine whether to continue decoding. This preliminary check allows the system to stop unnecessary iterations in advance, improving decoding speed while maintaining manageable control complexity through a straightforward threshold comparison mechanism.
Solution Approach 2:
The patent uses syndrome weight as feedback to dynamically control the decoding process. By monitoring the syndrome weight after each iteration and comparing it against thresholds, the system adjusts its behavior to stop early when appropriate, resolving the contradiction between speed and complexity.
2Loss of time
If early stopping based on syndrome weight is implemented, then time and energy consumption are reduced, but the decoding control mechanism becomes more complex
Solution Approach 1:
The patent performs syndrome weight checking before each iteration to predict whether continuing decoding would be beneficial. This preliminary assessment reduces decoding time by avoiding unnecessary iterations while keeping the control mechanism relatively simple through threshold-based decision making.
Solution Approach 2:
The patent changes the control parameter from a fixed iteration count to a dynamic syndrome weight threshold. This parameter change enables early stopping to reduce time consumption while the complexity remains manageable because the threshold comparison is a simple operation that can be implemented efficiently.
3Reliability
If the syndrome weight threshold is set low, then more iterations are performed improving error correction, but time and energy are wasted on unnecessary iterations
Solution Approach 1:
The patent uses dynamic threshold adjustment where the syndrome weight threshold varies based on the iteration stage and error conditions. This dynamic approach ensures sufficient error correction capability is maintained while avoiding excessive energy consumption by adapting the stopping criterion to actual decoding needs rather than using a fixed low threshold.
Solution Approach 2:
The patent changes the threshold parameter adaptively during decoding based on syndrome weight trends and iteration progress. This parameter change allows the system to maintain high reliability when needed while reducing energy consumption by stopping early when the syndrome weight indicates successful convergence, resolving the contradiction between correction capability and energy use.
Data Source
AI summary
A processing device in a memory sub-system determines a syndrome weight for a sense word read from a memory device and determines whether the syndrome weight for the sense word satisfies a threshold criterion. Responsive to the syndrome weight for the sense word satisfying a respective threshold criterion associated with a next iteration of a first decoding operation, bypassing the first decoding operation and initiating a second decoding operation for the sense word, wherein the second decoding operation has a higher error correction capability than the first decoding operation.