Shortened LDPC Codeword Formatting for Variable-Length Data
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Solution Overview
Problem
Low density parity check (LDPC) codes face adaptability issues due to the overhead of maintaining numerous code words, which reduces their effectiveness across different storage mediums, as they require a fixed number of symbols for error correction, leading to inefficiencies with input data of varying lengths.
Innovation Solution
A system that generates short code words and appends dummy values to convert them into full code words, allowing for encoding and decoding processes to proceed without the dummy values, thereby increasing adaptability and efficiency across various storage mediums.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed number of symbols is used for full code words, then error correction capability is maintained, but adaptability to different storage mediums is reduced
Solution Approach 1:
The code word structure is segmented into two parts: a fixed full code word portion for error correction and a variable short code word portion for adaptability. This allows the system to maintain reliable error correction while adapting to different storage medium requirements by adjusting the proportion of full versus short code words.
Solution Approach 2:
The system dynamically adjusts the code word length by appending varying numbers of dummy values to short code words based on the specific storage medium requirements. This dynamic adaptation allows the same LDPC code to work efficiently across different storage mediums while maintaining the fixed error correction capability of the full code word structure.
2Adaptability or versatility
If numerous different code words are maintained for different storage mediums, then compatibility is achieved, but device complexity increases
Solution Approach 1:
A single LDPC code structure serves multiple storage mediums by allowing flexible configuration of full and short code words. The universal code design eliminates the need to maintain numerous different codes for different storage mediums, reducing encoder and decoder complexity while maintaining compatibility across various storage formats.
Solution Approach 2:
The system changes parameters such as code word length and the number of dummy values appended based on storage medium requirements, rather than maintaining entirely different codes. This parameter-based adaptation reduces device complexity by using a single code framework with adjustable parameters.
3Productivity
If short code words are used for input data with fewer symbols, then data efficiency is improved, but encoding and decoding complexity increases
Solution Approach 1:
Dummy values are preliminarily appended to short code words during the encoding process to convert them into full code words. This preliminary action simplifies the subsequent encoding and decoding operations by allowing the use of standard full code word processing logic, thereby reducing overall complexity while maintaining data efficiency.
Data Source
AI summary
Systems, methods, and other embodiments associated with an encoder. In one embodiment, a system includes an encoder having a code word generator and an appending logic. The code word generator is configured to generate code words based on input data and identify one or more short code words. A short code word has a length less than a length of a full code word. The appending logic is configured to append at least one dummy value to at least one of the short code words to convert the at least one short code word to a full code word. The encoder may further be configured to encode the converted full code word and store the converted full code word without the at least one dummy value in a storage medium.