Decoder Input Refresh for Trapping-Set Error Recovery
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Solution Overview
Problem
Data processing systems face issues with error convergence in decoders due to trapping sets, leading to high error floors and increased latency, particularly in flash memory systems where uncorrectable bit error rates are undesirable.
Innovation Solution
The implementation of a refresh, run, and aggregate decoder recovery method, which involves refreshing the decoder input by altering log likelihood ratio values and aggregating decoder outputs to generate new initial inputs, allowing the decoder to avoid trapping sets and converge correctly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the decoder uses normal error correction procedures, then the decoding process is simple and fast, but it fails to correct stubborn errors and leads to high error floors
Solution Approach 1:
The patent applies preliminary action by performing a refresh operation before the main decoding process. The decoder input is initialized with refreshed values derived from the received encoded data, preparing the decoder in advance to avoid trapping sets and improve convergence for stubborn errors.
Solution Approach 2:
The patent implements feedback by monitoring decoder convergence and using the decoder output to generate refreshed input values. When the decoder fails to converge, the output is fed back through the initialization circuit to create new input values, forming a closed-loop recovery mechanism.
2Reliability
If the decoder implements recovery features to correct stubborn errors, then error correction capability improves, but latency increases due to additional processing steps
Solution Approach 1:
The refresh operation is performed preliminarily and efficiently using the received encoded data itself, rather than requiring extensive reprocessing. This preliminary initialization reduces the need for multiple full decoding passes, thereby reducing overall latency while maintaining error correction capability.
Solution Approach 2:
The patent changes the parameter state of the decoder input by refreshing the initial values. This parameter change allows the decoder to converge faster by starting from a more favorable initial state, reducing the number of iterations needed and thus reducing latency.
3Reliability
If the decoder input is refreshed using the received encoded data, then decoder convergence improves and error floors are reduced, but the system complexity increases
Solution Approach 1:
The decoder initialization circuit serves multiple functions: it refreshes the decoder input, generates new input values from received data, and provides recovery capability. This multi-functionality reduces the need for separate dedicated circuits for each function, thereby limiting the increase in system complexity.
Solution Approach 2:
The system uses the received encoded data itself to generate the refreshed decoder input values, rather than requiring external reference data or complex initialization sequences. The received data serves itself as the source for refreshing, simplifying the overall system architecture.
Data Source
AI summary
A data processing system includes a likelihood input operable to receive encoded data, a decoder operable to apply a decoding algorithm to likelihood values for the received encoded data and to yield a decoded output, and a decoder input initialization circuit operable to generate new decoder input values based in part on the likelihood values for the received encoded data after the likelihood values for the received encoded data have failed to converge in the decoder.