Cyclic LDPC Encoder Layout for Flexible Code Rates
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently implementing low density parity check (LDPC) codes to support high data rates without increasing hardware complexity, particularly in multi-media applications like streaming video and high-speed web surfing.
Innovation Solution
The method involves generating a codeword using a mother code parity check matrix with cyclic structure and a macro matrix, allowing for flexible code rates and reduced storage requirements by using row combining techniques, which maintains a constant codeword size and avoids bi-diagonal sub-matrices and length-four cycles, applicable to the IEEE 802.11n MIMO standard.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If LDPC codes are used to support high data rates, then data transmission performance is improved, but hardware complexity increases
Solution Approach 1:
The parity check matrix is segmented into sub-matrices with cyclic structures, allowing the encoding process to be divided into manageable stages. This segmentation enables high data rates through efficient parallel processing while controlling hardware complexity by breaking down the overall encoding task into smaller, reusable computational blocks.
Solution Approach 2:
The invention changes the structural parameters of the parity check matrix by imposing cyclic structures on sub-matrices and defining specific non-zero element patterns. These parameter changes enable the use of efficient encoding algorithms that achieve high data rates with reduced hardware complexity compared to fully random LDPC matrices.
2Reliability
If large sparse matrices are stored for LDPC coding, then coding performance is improved, but storage requirements increase
Solution Approach 1:
The large sparse parity check matrix is segmented into smaller sub-matrices with cyclic structures. This segmentation allows the system to store only the essential parameters defining each sub-matrix (such as cycle shifts and non-zero element positions) rather than the entire matrix, significantly reducing storage requirements while maintaining coding performance.
Solution Approach 2:
The cyclic structure of sub-matrices provides universality, where a small set of base patterns can generate multiple equivalent structures through cyclic shifts. This multi-functionality allows the system to achieve diverse coding performances using a limited set of stored parameters, reducing storage requirements while maintaining high reliability.
3Adaptability or versatility
If code rate is varied to support different applications, then adaptability is improved, but system complexity increases
Solution Approach 1:
The system implements dynamic code rate adjustment by selectively using different subsets of the parity check matrix rows and columns based on the desired code rate. This dynamic reconfiguration allows the same hardware structure to support multiple code rates (e.g., 1/2, 2/3, 3/4, 5/6) without requiring separate encoders for each rate, thus improving adaptability while controlling system complexity.
Data Source
AI summary
A method of coding data for transmission in a communication medium or channel. A codeword is generated from a mother code parity check matrix and a macro matrix. The mother code parity check matrix includes sub-matrices that are m-by-m square matrices with cyclic structure, and the macro matrix includes elements that represent nonzero sub-matrices of the mother code parity check matrix.