Data Word Decoding with Syndrome-Guided Viterbi Error Correction
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Solution Overview
Problem
Viterbi decoding for convolutional codes is computationally expensive and inefficient, especially when error correction is not required or when errors are undetectable, as it performs unnecessary state-to-state iterations.
Innovation Solution
The method involves using a parity-check matrix to determine if error correction is needed, avoiding unnecessary processing by estimating transmission errors with the Viterbi algorithm only in error-prone zones and performing algebraic decoding for error-free data, thus reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Viterbi decoding is performed on all received data words, then error correction capability is maintained, but computational complexity increases significantly
Solution Approach 1:
The patent applies preliminary action by performing a quick error detection check using syndrome calculation before committing to full Viterbi decoding. The receiver first calculates the syndrome of the received data word to determine if errors are present and correctable. Only when the syndrome indicates correctable errors does the system proceed to execute the computationally intensive Viterbi decoding algorithm, thus avoiding unnecessary complexity for error-free or uncorrectable data words.
Solution Approach 2:
The patent implements local quality by applying different processing strategies to different types of received data words based on their error characteristics. Error-free data words undergo simple syndrome checking, correctable error data words receive full Viterbi decoding treatment, and uncorrectable data words are discarded. This selective approach optimizes computational resources by matching processing intensity to actual data quality requirements.
2Measurement precision
If Viterbi decoding is performed on error-free data words, then decoding accuracy is maintained, but unnecessary processing time is consumed
Solution Approach 1:
The patent applies partial action by performing only the necessary minimum processing for error-free data words. Instead of executing the complete Viterbi decoding algorithm on all received data, the system performs a partial check using syndrome calculation to verify error-free status, and only executes full decoding when errors are detected. This partial processing approach maintains decoding accuracy for error-free data while eliminating wasteful processing time.
3Reliability
If full Viterbi decoding is applied to uncorrectable data words, then decoding attempts are made, but computational resources are wasted
Solution Approach 1:
The patent uses preliminary syndrome calculation to identify uncorrectable data words before attempting full Viterbi decoding. By first computing the syndrome and analyzing the error pattern, the system can determine in advance whether the data word contains too many errors to be correctable. Uncorrectable data words are discarded at this preliminary stage, preventing waste of computational resources on decoding attempts that would inevitably fail.
Solution Approach 2:
The patent extracts and removes uncorrectable data words from the processing pipeline before they can consume significant computational resources. The syndrome calculation serves as a filtering mechanism that identifies and extracts problematic data words, separating them from the main decoding flow. This extraction approach prevents these defective data words from entering the resource-intensive Viterbi decoding stage, thereby protecting overall processing efficiency.
Data Source
AI summary
A method of decoding a received data word (r) having been transmitted over a radio communication channel, the corresponding sent data word (m) having been encoded as a code word (c), the method includes:multiplying of the received data word by a parity-check matrix,and if the result of the multiplication is zero: performing an algebraic decoding of the received data word without error correction, otherwise performing an error correction by estimating the transmission error, subtracting the estimated error from the received data word, and performing an algebraic decoding of the result of the subtraction, wherein for estimation of the transmission error is used to identify an approximate location of potential errors and the Viterbi algorithm is only applied for these locations, thus avoiding iterations in error-free areas.