Error Correction Circuit for Trapping Set Detection in Iterative Decoding
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Solution Overview
Problem
Existing error correction systems in memory systems face challenges in efficiently detecting trapping sets during iterative decoding, which can lead to resource wastage and decoding failures, especially when error correction decoding fails to converge to a valid codeword.
Innovation Solution
An error correction circuit and method that includes a syndrome check history manager and a trapping set detector, which monitor the history of syndrome checks and apply a trapping set determination policy to identify trapping sets, thereby stopping iterative decoding when specific criteria are met, such as changes in syndrome vectors or unsatisfied check nodes, within a maximum iteration number.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If iterative decoding is performed with increased maximum iteration number to improve error correction capability, then error correction performance is improved, but resource consumption and decoding time increase
Solution Approach 1:
The syndrome check history manager maintains a history of syndrome checks from previous iterations, allowing the trapping set detector to identify trapping sets based on historical patterns rather than requiring full iteration completion. This preliminary detection mechanism enables early termination when trapping sets are identified, reducing unnecessary decoding time while maintaining error correction capability.
Solution Approach 2:
The system implements feedback by continuously monitoring syndrome check results and comparing them against stored historical data. The trapping set detector uses this feedback to determine whether to terminate decoding early, creating a closed-loop control system that adapts decoding duration based on actual convergence behavior rather than relying solely on predetermined maximum iteration counts.
2Reliability
If iterative decoding continues for maximum iterations to ensure convergence, then decoding completeness is improved, but resource wastage increases when trapping sets are present
Solution Approach 1:
The syndrome check history manager pre-stores syndrome check results from previous iterations, enabling the trapping set detector to perform preliminary analysis before full iteration completion. This allows the system to identify trapping sets in advance and terminate decoding early, preventing resource wastage while ensuring decoding completeness when convergence is achievable.
Solution Approach 2:
The trapping set detector extracts trapping set patterns from the historical syndrome check data maintained by the syndrome check history manager. By separating the detection function from the full decoding process, the system can identify and remove problematic trapping set cases early, preventing unnecessary resource consumption in iterations that would not contribute to successful convergence.
3Measurement precision
If syndrome check history is maintained for trapping set detection, then decoding accuracy is improved, but device complexity increases
Solution Approach 1:
The error correction circuit is segmented into distinct functional modules: a syndrome check history manager for maintaining historical data, a trapping set detector for pattern recognition, and the core iterative decoding unit. This segmentation allows each component to perform its specific function efficiently, improving trapping set detection accuracy while managing overall circuit complexity through modular design.
Solution Approach 2:
The syndrome check history manager serves multiple functions: it stores historical syndrome data for trapping set detection, provides feedback for convergence monitoring, and supports early termination decisions. This multi-functionality reduces the need for separate dedicated circuits for each function, thereby improving detection accuracy without proportionally increasing device complexity.
Data Source
AI summary
Described herein is an error correction circuit that includes a syndrome check history manager configured to maintain a history of syndrome checks corresponding to one or more iterations of the iterative decoding scheme. The error correction circuit also includes a trapping set detector configured to compare a trapping set determination policy with the history of syndrome checks to determine whether the history of syndrome checks meets criteria of the trapping set determination policy, while error correction decoding is performed, and determine that a trapping set exists when the history of syndrome checks satisfies the trapping set determination policy. The trapping set determination policy is related to at least one of a change in a syndrome vector, a number of UCNs, and a change in the number of UCNs.