Syndrome-Based 1-Bit Error Correction Without Data Re-Read
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Solution Overview
Problem
Existing storage devices struggle to quickly detect and correct 1-bit errors in data without re-reading the data, which can lead to inefficiencies in data processing.
Innovation Solution
An error correction device that includes a memory unit and a calculation circuit to calculate a syndrome using preset matrices, determine the presence of errors, and identify the specific data unit with a 1-bit error based on Hamming weights, enabling rapid error detection and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the storage device re-reads data when an error is detected, then data accuracy is ensured, but data processing speed decreases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing syndrome values and error vectors for all possible 1-bit error scenarios during system initialization. When an error is detected during data reading, the system can immediately query these pre-prepared values to identify and correct the error position without re-reading the data, thus maintaining both high accuracy and fast processing speed
Solution Approach 2:
The patent implements partial action by focusing the error correction mechanism specifically on 1-bit errors rather than attempting to handle all possible error types. The syndrome calculation and error vector comparison are designed to efficiently identify single-bit errors, providing a targeted solution that achieves high correction accuracy for the most common error type while maintaining fast processing speed
2Measurement precision
If the storage device implements comprehensive error checking, then error detection accuracy improves, but processing time increases
Solution Approach 1:
The patent applies segmentation by dividing the error detection and correction process into distinct stages: syndrome calculation, error detection based on syndrome values, and error position identification using error vectors. This segmented approach allows each stage to be optimized independently, achieving high detection accuracy through systematic analysis while minimizing total processing time through efficient stage transitions
Solution Approach 2:
The patent introduces syndrome values as an intermediary element that bridges data verification and error position identification. The syndrome acts as a compact representation of error status that can be quickly calculated and compared against pre-stored values, enabling accurate error detection without requiring time-consuming comprehensive analysis of the entire data set
Data Source
AI summary
An error correction device may calculate a syndrome S for target data on the basis of a first matrix M and a second matrix Q which are determined according to a preset cyclic redundancy check polynomial, may determine, on the basis of the syndrome S, whether an error has occurred in the target data, and when it is determined that an error has occurred in the target data, may search for an error data unit in which a 1-bit error has occurred among N number of data units on the basis of Hamming weights of error vectors for the N number of data units.