Soft-Decision Decoding With Early Mis-Decoding Detection
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Solution Overview
Problem
The existing modified Random Redundant Decoding (mRRD) algorithm for High Density Parity-Check codes faces increased decoding complexity due to the generation of multiple decoding candidates, which hampers efficient error correction and mis-decoding detection.
Innovation Solution
A semi-parallel Random Redundant Decoding (sRRD) algorithm is introduced, which includes a detector that analyzes the inner product of received vectors and decoding results to determine successful decoding, using a threshold value and automorphism groups to reduce complexity by selectively iterating through decoding processes and identifying mis-decoding early.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the modified Random Redundant Decoding (mRRD) algorithm generates all decoding result candidates to prevent mis-decoding, then the error correction performance is improved, but the decoding complexity increases in proportion to the number of decoding result candidates
Solution Approach 1:
The patent extracts only the necessary decoding candidates for further processing rather than generating all possible candidates. The detector identifies and selects promising candidates based on initial decoding results, eliminating the need to process all exponential number of candidates while maintaining error correction performance.
Solution Approach 2:
The patent performs preliminary detection to identify promising decoding candidates before full decoding. The detector analyzes initial decoding results and pre-selects candidates that are likely to be correct, performing the complex decoding operation only on these selected candidates rather than all candidates.
2Measurement precision
If multiple decoding candidates are generated to detect mis-decoding, then the detection accuracy is improved, but the computational overhead increases
Solution Approach 1:
The patent implements a feedback mechanism where the detector continuously monitors decoding results and provides feedback to select the next promising candidate. This iterative feedback process enables accurate mis-decoding detection by comparing successive decoding results while minimizing computational overhead through intelligent candidate selection.
Solution Approach 2:
The patent performs partial action by processing only a limited number of promising decoding candidates identified by the detector, rather than exhaustively processing all possible candidates. This partial processing approach achieves sufficient mis-decoding detection accuracy with reduced computational overhead.
Data Source
AI summary
Provided are a method of low-complexity decoding based on soft decision and a computing device for performing the method. The method of low-complexity decoding based on soft decision, performed by a computing device, includes receiving a vector, in which a codeword is modulated, through a channel, determining a decoding result by sequentially applying the received vector to one or more decoding algorithms, and decoding the codeword based on an analysis on the decoding result of a detector corresponding to each of the one or more decoding algorithms.