Structured LDPC Encoding Using Block-Triangular Parity Sub-Matrices
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Solution Overview
Problem
Communication systems face challenges in high-speed digital communication due to noise, fading, and Inter-Symbol Interference (ISI), which affect link performance, particularly in applications like 60 GHz personal area networks and next-generation mobile communication, where existing error-correcting codes are insufficient in ensuring high data throughput and reliability.
Innovation Solution
The use of systematic Low Density Parity Check (LDPC) codes with a specific matrix structure, comprising a first sub-matrix for information symbols, a second sub-matrix with a block triangular structure for a subset of parity check symbols, and a third invertible sub-matrix for another subset of parity check symbols, to encode information words into codewords, addressing noise and ISI issues through efficient error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional error-correcting codes are used in high-speed digital communication systems, then the system can operate in noisy channels, but the data throughput and reliability are insufficient
Solution Approach 1:
The parity check matrix H is segmented into sub-matrices with specific structures (cyclic permutation matrices and identity matrices), allowing the encoding process to be divided into manageable operations that can be performed efficiently in parallel, thereby improving both reliability and data throughput simultaneously
2Reliability
If LDPC codes with sparse parity check matrices are used, then error correction capability is improved, but the encoding complexity increases
Solution Approach 1:
The patent changes the structural parameters of the parity check matrix by using specific cyclic permutation patterns and identity matrix blocks, which transforms the encoding operation into a series of simpler modular arithmetic operations that reduce computational complexity while preserving error correction capability
3Productivity
If systematic LDPC codes are used with explicit information symbols in codeword, then decoding efficiency is improved, but the matrix structure becomes more complex
Solution Approach 1:
The systematic LDPC code structure segments the codeword into explicit information symbols and parity check symbols, with the parity check matrix accordingly divided into sub-matrices. This segmentation allows the decoder to process information and parity parts separately, improving decoding efficiency while the modular matrix structure actually simplifies implementation
Solution Approach 2:
Instead of designing the code structure first and then deriving the matrix, the patent inverts the approach by designing the parity check matrix with specific invertible sub-matrices first, which naturally leads to a systematic code structure that is both efficient for decoding and manageable in complexity
Data Source
AI summary
A method and apparatus are disclosed that include encoding an information word to generate a codeword using a systematic low density parity check matrix using an encoder, the low density parity check matrix comprising a first sub-matrix associated with information symbols, a second sub-matrix having a block triangular structure associated with a first subset of parity check symbols and a third sub-matrix that is invertible and associated with a second subset of parity check symbols, the encoding performed over the second sub-matrix before the third sub-matrix.