Soft-Decision Linear Code Decoding With MRB Cost Screening
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Solution Overview
Problem
The high computational complexity of ordered statistics decoding (OSD) methods for soft decision-based linear code decoding hinders efficient decoding performance, necessitating a method to reduce operation complexity while maintaining performance.
Innovation Solution
The proposed method involves sorting received signals, obtaining hard decision signals, identifying most reliable bases, and using an error vector to calculate a cost function, with predefined speeding conditions to omit unnecessary calculations, thereby reducing computational complexity and enhancing decoding speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ordered statistics decoding (OSD) is used for soft decision-based linear code decoding, then decoding performance is improved to be close to maximum likelihood scheme, but operation complexity becomes very high
Solution Approach 1:
The patent segments the OSD process into distinct stages: hard decision stage, error pattern generation stage, and cost calculation stage. By dividing the complex decoding process into manageable segments, the patent enables selective execution of only necessary operations, thereby reducing overall computational complexity while preserving decoding performance.
Solution Approach 2:
The patent implements partial action by calculating cost functions for only a subset of error patterns rather than all possible patterns. Specifically, it generates error patterns up to a predetermined weight and selectively processes those that meet certain criteria, avoiding the exhaustive search required by traditional OSD while maintaining near-ML performance.
2Measurement precision
If traditional OSD method is used, then decoding accuracy is maintained, but decoding speed is slow due to high computational complexity
Solution Approach 1:
The patent performs preliminary hard decision on the received signal before generating error patterns. This preliminary action separates the most reliable bits from less reliable ones, allowing the subsequent cost calculation to focus only on potential error positions. This pre-processing step significantly reduces the number of operations needed while preserving decoding accuracy.
Solution Approach 2:
The patent extracts and processes only the relevant error patterns from the complete set of possible error patterns. By identifying and focusing on error patterns with weight up to a predetermined value, it extracts the essential computational work needed for accurate decoding while discarding unnecessary calculations, thereby improving decoding speed.
Data Source
AI summary
Disclosed are a method and an apparatus for fast decoding a linear code based on soft decision. The method may comprise sorting received signals in a magnitude order to obtain sorted signals; obtaining hard decision signals by performing hard decision on the sorted signals; obtaining upper signals corresponding to MRBs from the hard decision signals; obtaining a permuted and corrected codeword candidate using the upper signals and an error vector according to a current order; calculating a cost for the current order using a cost function; determining the permuted and corrected codeword candidate as a permuted and corrected codeword according to a result of comparing the calculated cost with a minimum cost; and determining a predefined speeding condition.