LDPC Decoder Reliability Calculation for Dispersion
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Solution Overview
Problem
Conventional LDPC decoding systems face performance degradation due to dispersion of reliability information when applied to actual transmission paths, particularly in communication and recording-regenerating media, as the modulation rule and transmission path characteristics cause deviation in reliability information distribution, leading to inefficient error correction.
Innovation Solution
A decoding system that modulates user data using a modulation rule converting the data into a pattern with a bit length equivalent to or different from the original, dispersing information into plural bits, and calculates reliability information based on distances between regenerative and generation signals, using formulas to accurately estimate bit likelihood and reduce the influence of dispersion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional LDPC decoding is applied to actual transmission paths with modulation rules, then error correction capability is achieved, but reliability information distribution deviates causing performance degradation
Solution Approach 1:
The invention changes the calculation parameters of reliability information by introducing a new formula that incorporates the number of candidate sequences and their distances. This parameter change adapts the reliability calculation to actual transmission path characteristics, correcting the distribution deviation caused by modulation rules while maintaining error correction capability.
Solution Approach 2:
The invention implements feedback by using the calculated reliability information to improve subsequent decoding operations. The corrected reliability values feed back into the decoding process, creating a loop that continuously improves accuracy by accounting for the actual distribution characteristics observed in the transmission path.
2Productivity
If modulation rules are used to convert user data into modulation patterns, then information is dispersed into plural bits enabling transmission, but reliability information distribution deviates
Solution Approach 1:
The invention modifies the reliability calculation parameters to account for the dispersion effect of modulation rules. By incorporating the distance metric and candidate sequence count into the reliability formula, it corrects the distribution deviation while preserving the productivity benefits of information dispersion.
Solution Approach 2:
The invention adds a new dimension to reliability calculation by considering the distance between received signals and candidate sequences, as well as the number of candidates. This dimensional expansion allows the system to account for modulation-induced dispersion while maintaining accurate reliability assessment.
3Measurement precision
If reliability information is calculated based on distance between regenerative and generation signals, then decoding accuracy is improved, but calculation complexity increases
Solution Approach 1:
The invention applies partial action by calculating reliability information only for the top k candidate sequences rather than all possible sequences. This selective approach maintains decoding accuracy for the most probable sequences while reducing calculation complexity by avoiding exhaustive computation.
Solution Approach 2:
The invention simplifies the calculation by changing parameters to use distance metrics and candidate counts that can be computed efficiently. The reformulated reliability expression uses these simplified parameters to achieve accurate decoding without requiring complex computational operations.
Data Source
AI summary
A decoding system includes: a modulator which modulates user data by using a modulation rule which converts the user data into a modulation pattern; a regenerator which generates a regenerative signal from a signal obtained by transmitting the user data after modulation through a transmission path; a transmission path decoder which generates signals as generation signals corresponding to the modulation pattern, and calculates k (k is a positive integer) distances between the regenerative signal and the k generation signals in an interval having a length fixedly or dynamically determined; and a demodulator which calculates reliability information for each bit of the user data, and estimates each bit of the user data based on the calculated reliability information. The demodulator calculates likelihood that each bit of the user data is 1 and each bit of the user data is 0 by Formula (A), and calculates the reliability information by Formula (B).