Asymmetric Distance Coding for Error-Prone Datawords
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Solution Overview
Problem
Existing error detection coding techniques face a trade-off between increasing minimum coding distance for improved error detection and correction, which reduces coding efficiency, as higher minimum coding distance limits the number of codewords available for encoding digital information.
Innovation Solution
Asymmetric distance coding divides datawords into groups with different susceptibility to transmission errors, assigning codewords with higher minimum coding distance to more error-prone datawords and lower minimum coding distance to less error-prone datawords, allowing for efficient error protection while maximizing the number of codewords in the coding space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If minimum coding distance is increased to improve error detection and correction capability, then error protection is improved, but coding efficiency deteriorates due to reduced number of available codewords
Solution Approach 1:
The patent applies local quality by differentiating coding strategies for different dataword groups based on their error susceptibility. High-error-susceptibility datawords are mapped to codewords with higher minimum coding distance for enhanced protection, while low-error-susceptibility datawords use codewords with lower minimum coding distance to maximize coding efficiency. This localized differentiation resolves the contradiction by optimizing error protection where needed without unnecessarily reducing coding efficiency elsewhere.
Solution Approach 2:
The patent implements asymmetry through asymmetric distance coding, where different minimum coding distances are assigned to different codeword groups. Specifically, a first minimum coding distance is used for codewords corresponding to high-error-susceptibility datawords, while a second minimum coding distance (lower than the first) is used for codewords corresponding to low-error-susceptibility datawords. This asymmetric approach allows the system to achieve both improved error protection for critical datawords and maintained coding efficiency overall.
2Reliability
If minimum coding distance is increased to protect error-prone datawords, then error protection for susceptible datawords is improved, but the number of available codewords decreases
Solution Approach 1:
The patent applies local quality by differentiating coding strategies for different dataword groups based on their error susceptibility. High-error-susceptibility datawords are mapped to codewords with higher minimum coding distance for enhanced protection, while low-error-susceptibility datawords use codewords with lower minimum coding distance to maximize coding efficiency. This localized differentiation resolves the contradiction by optimizing error protection where needed without unnecessarily reducing coding efficiency elsewhere.
Solution Approach 2:
The patent applies partial action by providing enhanced error protection (higher minimum coding distance) only to the extent necessary for high-error-susceptibility datawords, rather than uniformly applying maximum protection to all datawords. This partial application of strong protection to critical cases while using lighter protection for less critical cases maximizes the number of available codewords overall.
Data Source
AI summary
A digital electronic message comprising datawords to be transmitted in a communications system can be encoded prior to transmission using an asymmetric error detection coding scheme. The coding scheme is asymmetric because the coding scheme includes multiple codeword groups each with a different minimum coding distance. The codewords in a group having a greater minimum coding distance can correspond to datawords that have a relatively high susceptibility to transmission errors. The codewords in a group having a lesser minimum coding distance can correspond to datawords that have a relatively low susceptibility to transmission errors.


