QC-LDPC Encoding for Non-Integer Circulant Data Lengths
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Solution Overview
Problem
Existing LDPC encoding techniques are limited by requiring data lengths to be integer multiples of the circulant size, restricting their applicability in multistage coding and inefficiently handling data of non-integer multiples, which can lead to suboptimal performance and increased resource utilization.
Innovation Solution
The implementation of a multistage LDPC encoder that breaks down parity check or generator matrices into sub-matrices, allowing for data encoding of non-integer multiples of the circulant size through padding and subsequent removal of zeros, and prioritizing decision and reliability information during decoding to enhance error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If QC-LDPC encoding is used with integer multiple data lengths, then encoding efficiency is improved, but adaptability to non-integer multiple data lengths deteriorates
Solution Approach 1:
The parity check matrix is divided into multiple sub-matrices, allowing the encoding process to handle data of different lengths by selecting appropriate sub-matrices. This segmentation enables the system to process non-integer multiple data lengths while maintaining encoding efficiency through structured sub-matrix operations.
Solution Approach 2:
The system changes the parameters of the parity check matrix by using different sub-matrices with different dimensions. This allows the encoder to adapt to various data lengths (non-integer multiples of circulant size) while maintaining optimal encoding performance through parameter adjustment.
2Adaptability or versatility
If data is padded to achieve integer multiple length, then encoding compatibility is improved, but resource utilization deteriorates
Solution Approach 1:
The system extracts and removes the padded zeros from the encoded data after processing. This extraction process eliminates the waste of resources caused by padding, allowing the system to achieve encoding compatibility for non-integer multiple data lengths without permanently retaining unnecessary padded bits.
Solution Approach 2:
Data is temporarily padded with zeros before encoding to achieve integer multiple length compatibility, but this padding is performed as a preliminary action that is subsequently reversed by removing the padded zeros after encoding, thus maintaining resource efficiency.
3Adaptability or versatility
If multistage encoding is implemented, then flexibility in handling different data lengths is improved, but system complexity deteriorates
Solution Approach 1:
The encoding system is divided into multiple stages, each handling specific sub-matrices. This segmentation provides flexibility in handling different data lengths by activating only the necessary stages, while the modular structure actually reduces overall system complexity compared to a monolithic design.
Solution Approach 2:
The multistage encoder dynamically activates or deactivates specific encoding stages based on the input data length. This dynamic operation provides flexibility for handling non-integer multiple data lengths while keeping the system complexity manageable by only executing necessary processing stages.
Data Source
AI summary
In processing quasi-cyclic low-density parity-check (QC-LDPC) data, an input signal is received which includes decision and reliability information corresponding to unpadded data. Decision and reliability information corresponding to padded data is introduced into the input signal. Message passing is performed one or more times to obtain decoded data. This includes using (1) the decision and reliability information corresponding to the unpadded data and (2) the decision and reliability information corresponding to the padded data, where a preference is given to the decision and reliability information corresponding to the unpadded data over the decision and reliability information corresponding to the unpadded data during message passing. Zero padding is removed from the decoded data.