Trellis Error-Correction Coding With Local Detection Codes
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Solution Overview
Problem
Current error correction codes, such as turbo codes and LDPC codes, have high decoding complexity, which increases the silicon surface area and production costs of electronic chips and consumes more power, especially in portable devices, and exhibit low performance for small block sizes, leading to a need for reduced complexity and improved error correction capacity.
Innovation Solution
The use of simple local codes, primarily error detector codes, interconnected to form a trellis structure, which creates a comprehensive error correction code with reduced complexity and improved performance, allowing for better error correction and approaching Shannon's limit, especially for short codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current error correction codes (turbo codes, LDPC codes) are used, then error correction capability is improved, but decoding complexity increases
Solution Approach 1:
The patent segments the error correction code into multiple independent local codes (error detector codes) that operate on different portions of the data. Each local code is simple and can be decoded independently, avoiding the high complexity of traditional turbo codes and LDPC codes while maintaining effective error correction through the collective action of all local codes.
Solution Approach 2:
The patent introduces an intermediary structure (the trellis formed by interconnecting state words of local codes) that mediates between the simple local error detector codes and the overall error correction function. This intermediary allows complex error correction to be achieved through composition of simple components rather than through inherently complex decoding algorithms.
2Reliability
If high decoding complexity is accepted, then error correction performance is improved, but silicon surface area and production costs increase
Solution Approach 1:
By segmenting the error correction function into multiple simple local codes, the patent reduces the silicon surface area required for implementation. Each local code requires minimal decoding resources, and their parallel or sequential execution avoids the need for large, complex decoding circuits found in traditional error correction codes.
3Reliability
If high decoding complexity is used, then error correction capability is improved, but power consumption increases
Solution Approach 1:
The patent divides the error correction task into multiple simple local code operations that consume less power individually. The segmented approach allows for more efficient use of computational resources and reduces overall power consumption compared to the intensive decoding required by traditional error correction codes.
4Reliability
If traditional error correction codes are used, then error correction is provided, but performance is low for small block sizes
Solution Approach 1:
The patent applies segmentation by using multiple local codes that can be effectively applied to small data blocks. Each local code operates on a portion of the data, allowing effective error correction even when the overall block size is small, whereas traditional codes require larger block sizes to achieve similar performance.
Data Source
AI summary
A coding method is provided for associating redundant and source data and for carrying out a plurality of local codes associating at least one input status word and at least one output status word according to at least one label word and permutations applicable on at least certain of said words. The local codes are embodied in the form of detection codes and not error correction codes on a predetermined coding alphabet. The local codes are interconnected by the status words in such a way that at least one coding matrix is formed, each of which defining a base code.