Bit-Flipping Decoder Using Adaptive Threshold Sequences
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Solution Overview
Problem
Existing NAND type memory systems face challenges in efficiently decoding data due to hardware and software failures, leading to data errors, and existing decoding methods are inefficient and lack flexibility in selecting appropriate flipping thresholds.
Innovation Solution
A decoder system that selects a preset threshold sequence based on the check formula weight, assigning a flipping threshold to a bit flipping circuit to determine bit flipping, improving flexibility and reducing decoding time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed flipping threshold is used in the bit flipping circuit, then the decoding process is simple and fast, but the decoding performance deteriorates under varying error levels
Solution Approach 1:
The patent implements dynamic threshold selection by maintaining multiple preset threshold sequences (first threshold sequence, second threshold sequence, third threshold sequence) and dynamically switching between them based on the check formula weight. The processor selects different threshold sequences adaptively according to the error level detected in each iteration, transforming the static threshold into a dynamic parameter that adapts to varying decoding conditions, thereby improving decoding performance without requiring complex real-time threshold calculation mechanisms
Solution Approach 2:
The patent changes the parameter of flipping threshold from a fixed value to a variable that can take multiple discrete values from different preset sequences. By modifying the threshold parameter based on check formula weight ranges, the system achieves adaptive decoding performance across different error scenarios while maintaining implementation simplicity through pre-defined threshold sequences
2Adaptability or versatility
If multiple preset threshold sequences are selected based on check formula weight, then adaptability to different error levels is improved, but the processing time increases due to additional comparisons
Solution Approach 1:
The patent prepares multiple threshold sequences (first, second, and third threshold sequences with different threshold values) in advance before the decoding process begins. These preset sequences are stored and ready for immediate selection, eliminating the need for complex real-time threshold calculations during decoding iterations. The processor only needs to compare the check formula weight against predefined ranges and select the corresponding pre-prepared sequence, significantly reducing processing time while maintaining high adaptability
Solution Approach 2:
The patent segments the threshold selection space into multiple discrete threshold sequences, each optimized for specific error level ranges. By dividing the continuous threshold parameter space into segmented sequences (first sequence for low errors, second sequence for medium errors, third sequence for high errors), the system achieves fine-grained adaptability while using simple comparison logic to select the appropriate segment, balancing adaptability and processing efficiency
3Measurement precision
If the flipping threshold is updated in every iteration, then decoding accuracy is improved, but the computational complexity and time consumption increase
Solution Approach 1:
The patent updates the flipping threshold periodically by selecting from preset sequences at specific iteration points rather than continuously recalculating. The processor compares the check formula weight with predefined thresholds and switches between the three preset threshold sequences at periodic intervals during the decoding process. This periodic update mechanism ensures decoding accuracy by adapting thresholds when necessary while maintaining high decoding speed by avoiding unnecessary continuous recalculations
Solution Approach 2:
The patent implements feedback-based threshold selection where the processor continuously monitors the check formula weight and uses this feedback to dynamically select the appropriate threshold sequence. The feedback loop compares the current decoding state (check formula weight) with predefined thresholds and adjusts the flipping threshold accordingly, ensuring high decoding accuracy through adaptive feedback control while maintaining efficiency by using simple comparison-based decision logic rather than complex optimization algorithms
Data Source
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AI summary
According to one aspect of the present disclosure, a decoder is provided. The decoder may include a first processing circuit to: obtain a check formula and check formula weight based on a codeword to be decoded in a current iteration and a check matrix; a second processing circuit to: obtain energy of the codeword to be decoded based on the check formula, the check matrix and a flipping state of the codeword to be decoded; a processor to: in a first iteration, select a preset threshold sequence as an initial threshold sequence based on the check formula weight; and assign a flipping threshold in the initial threshold sequence to a bit flipping circuit; and the bit flipping circuit to: output a codeword to be decoded in a following iteration based on a result of a comparison between energy of the codeword to be decoded and the flipping threshold.