Adaptive LDPC Decoding with Dual Parity Matrices for Error Correction
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Solution Overview
Problem
Existing decoding methods for non-volatile memory and wireless communication systems face challenges in maximizing error correction capability while minimizing complexity, particularly in systems with increasing data throughput and fading effects.
Innovation Solution
A decoding method and device using a low-density parity check (LDPC) code that employs multiple parity check matrices, including a first LDPC code based on a single parity check (SPC) code and a second LDPC code with different characteristics, to estimate and correct errors effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single parity check code is used for error correction, then the decoding complexity is reduced, but the error correction capability is limited
Solution Approach 1:
The patent combines multiple parity check matrices (first SPC-based LDPC matrix and second non-SPC LDPC matrix) into a unified decoding system. The decoder merges the advantages of both code types by adaptively selecting or combining their respective parity check matrices based on channel conditions and error characteristics, thereby achieving enhanced error correction capability while maintaining manageable decoding complexity through structured matrix design.
Solution Approach 2:
The patent implements dynamic adaptation in the decoding process by estimating the number of errors in the received signal and adaptively selecting which parity check matrix to use based on the estimated error count. This dynamic approach allows the system to switch between SPC-based decoding (for low error rates) and non-SPC-based decoding (for high error rates), optimizing both complexity and correction capability according to actual channel conditions.
2Reliability
If multiple parity check matrices are used to enhance error correction capability, then the reliability improves, but the device complexity increases
Solution Approach 1:
The patent segments the error correction function into two distinct parts: a first parity check matrix based on SPC code for handling typical error patterns, and a second parity check matrix based on non-SPC LDPC code for handling severe error conditions. This segmentation allows the system to use only the necessary portion of the error correction capability based on channel conditions, avoiding the full complexity of always using the more powerful non-SPC matrix.
Solution Approach 2:
The patent applies partial action by using only the first SPC-based parity check matrix when error rates are low, and only activating the second non-SPC-based matrix when error rates exceed a threshold. This partial utilization of available error correction resources optimizes the trade-off between complexity and performance by deploying enhanced correction capability only when absolutely necessary.
3Productivity
If adaptive error estimation and selective decoding is implemented, then the error correction efficiency is maximized, but the processing time increases
Solution Approach 1:
The patent performs preliminary error estimation immediately upon receiving the transmitted signal, before committing to a full decoding process. This preliminary action of estimating the number of errors allows the system to pre-determine which decoding strategy to employ, avoiding unnecessary computational steps and reducing overall processing time by eliminating trial-and-error decoding approaches.
Data Source
AI summary
A decoding device and a decoding method which relate to: receiving a codeword; estimating a number of errors included in the received codeword; and decoding the codeword based on the estimated number of errors using at least one of a first parity check matrix and a second parity check matrix, wherein the first parity check matrix corresponds to a first low-density parity check (LDPC) code, and the second parity check matrix corresponds to a second LDPC code, and wherein the first parity check matrix is based on a first code type, and the second parity check matrix is based on a second code type different from the first code type.