Structured LDPC Coding for High-Rate Low-Delay Signal Reception
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Solution Overview
Problem
Next generation communication systems face challenges in supporting high data rates due to limitations in codeword length and maximum degree of variable nodes in Tanner graphs of LDPC codes, which restrict decoding complexity and delay.
Innovation Solution
A structured LDPC code is implemented, utilizing a parity check matrix with sub-matrices and specific parameter sets to maximize girth in Tanner graphs, reducing short-length cycles and enhancing coding rate while maintaining efficient decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the codeword length of the LDPC codeword is increased to approach channel capacity limit, then the performance is improved, but the decoding complexity increases considerably
Solution Approach 1:
The parity check matrix is divided into multiple sub-matrices, creating a structured LDPC code where the matrix is segmented into manageable blocks. This segmentation allows for reduced decoding complexity while maintaining the ability to achieve channel capacity limits through proper sub-matrix configuration and relationships.
2Productivity
If the maximum degree of variable node in Tanner graph is increased to support high data rate, then the data rate is improved, but the decoding delay increases
Solution Approach 1:
Different sub-matrices within the parity check matrix are designed with different properties and degrees. This local quality variation allows certain regions to handle high data rates while other regions maintain lower decoding delays, optimizing the overall system performance by having different parts serve different functions.
3Productivity
If the coding rate is increased to support high data rate transmission, then the productivity is improved, but the error correction capability may be reduced
Solution Approach 1:
The structured LDPC code uses a composite parity check matrix structure combining multiple sub-matrices with different properties. This composite structure enables the code to achieve both high coding rates and strong error correction capabilities by leveraging the complementary strengths of different sub-matrix configurations.
Data Source
AI summary
A signal transmission/reception apparatus of a communication system. The signal transmission apparatus receives an information vector, encodes the information vector into a structured Low Density Parity Check (LDPC) codeword using a structured LDPC coding scheme, and transmits the generated structured LDPC code to the signal reception apparatus. Then the signal reception apparatus receives a signal, and detects an information vector by decoding the received signal using a decoding scheme corresponding to the structured LDPC coding scheme used in the signal transmission apparatus.


