LDPC Parity Check Column Permutation for High-Rate Puncturing
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Solution Overview
Problem
High code rates in LDPC codes require puncturing, which affects performance, and existing methods struggle to optimize parity bit puncturing for improved reliability and efficiency in communications systems.
Innovation Solution
The method involves encoding and decoding using a low-density parity-check LDPC matrix with specific permutations of parity check columns to adjust bit sequences, ensuring optimal performance at high code rates by minimizing row entries punctured, thereby enhancing decoding reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If puncturing is applied to achieve high code rates, then code rate is improved, but decoding performance deteriorates
Solution Approach 1:
The patent applies preliminary action by permuting parity check columns before encoding to optimize the positions of punctured bits. The base matrix is designed with specific column permutations that anticipate the puncturing operation, ensuring that punctured bits do not critically impact decoding performance. This pre-arrangement of column positions resolves the contradiction by preparing the code structure in advance to withstand puncturing while maintaining high code rates.
Solution Approach 2:
The patent applies local quality by differentiating the treatment of different column positions in the base matrix. Specific columns (particularly columns n-m to n-1) are identified as parity check columns that require special permutation attention. The permutation operation selectively repositions bits in these critical local regions to minimize performance degradation from puncturing, while leaving other regions unchanged. This localized optimization resolves the contradiction by applying different quality standards to different parts of the code structure.
2Reliability
If parity check columns are permuted to minimize row entries punctured, then decoding reliability is improved, but computational complexity increases
Solution Approach 1:
The patent applies parameter changes by modifying the column permutation parameters of the base matrix to optimize for minimal punctured row entries. The permutation function P(j) is specifically designed to map columns in a way that concentrates non-punctured bits in critical positions. By changing the permutation parameters rather than the fundamental code structure, the patent achieves improved decoding reliability with relatively low additional complexity.
Solution Approach 2:
The patent applies segmentation by dividing the base matrix into distinct column groups: information columns (0 to n-m-1) and parity check columns (n-m to n-1). The permutation operation is specifically applied to the parity check column segment, allowing independent optimization of this segment to minimize puncturing impact. This segmentation enables targeted complexity reduction by focusing permutation efforts only where needed, rather than requiring full-matrix reorganization.
Data Source
AI summary
This application discloses an information processing method and apparatus, a communications device, and a communications system. The method includes: encoding an input sequence by using a low-density parity-check (LDPC) matrix, to obtain a bit sequence D, where a base matrix of the LDPC matrix is represented as a matrix of m rows and n columns, each column corresponds to a group of Z consecutive bits in the bit sequence D, and n and Z are both integers greater than 0; and obtaining an output bit sequence based on a bit sequence V, where the bit sequence V is obtained by permuting two groups of bits corresponding to at least two parity check columns in the bit sequence D.