LDPC Parity Check Matrix Layout for Incremental Redundancy Retransmission
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Solution Overview
Problem
Existing LDPC codes face challenges in implementing the Incremental Redundancy (IR) method due to the lack of correlation between previously transmitted and retransmitted parity parts, which hinders efficient data retransmission in mobile communication systems.
Innovation Solution
The proposed method involves encoding data using a parity check matrix with sub-matrices that have a dual diagonal structure, allowing for efficient retransmission by maintaining parity part correlation and adjusting coding rates through additional parity bit generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing LDPC codes are used for data retransmission, then encoding can be performed, but correlation between previously transmitted and retransmitted parity parts is lost, hindering efficient retransmission
Solution Approach 1:
The parity check matrix is divided into multiple sub-matrices, where each sub-matrix corresponds to a specific coding rate. This segmentation allows the system to select appropriate sub-matrices for initial transmission and retransmission, maintaining correlation between parity parts while adapting to different channel conditions and coding rate requirements.
Solution Approach 2:
The system dynamically selects which sub-matrix to use based on the coding rate and retransmission scenario. For initial transmission, a first sub-matrix is selected, and for retransmission, a second sub-matrix is selected such that their parity parts maintain correlation. This dynamic selection enables efficient incremental redundancy retransmission while adapting to varying channel conditions.
2Reliability
If parity check matrix is used for encoding, then channel coding can be performed, but device complexity increases due to matrix storage and computation
Solution Approach 1:
The large parity check matrix is segmented into multiple smaller sub-matrices, each corresponding to a specific coding rate. This reduces the computational burden and memory requirements for each encoding operation, as the encoder only needs to store and process the relevant sub-matrix for the current coding rate rather than the entire large matrix.
Solution Approach 2:
Different sub-matrices are designed with specific structures optimized for their respective coding rates. Each sub-matrix has locally optimized properties that enhance error correction capability for its specific coding rate, while the overall system maintains flexibility to switch between different sub-matrices based on channel conditions.
3Adaptability or versatility
If coding rate is adjusted for retransmission, then adaptability to channel conditions improves, but maintaining parity part correlation becomes more difficult
Solution Approach 1:
The system employs dynamic sub-matrix selection based on coding rate requirements. When adjusting coding rate for retransmission, the encoder selects a different sub-matrix that is specifically designed to maintain parity part correlation with the initial transmission sub-matrix. This dynamic adaptation allows coding rate adjustment while preserving the correlation necessary for efficient incremental redundancy retransmission.
Solution Approach 2:
The set of sub-matrices is designed to serve multiple functions: each sub-matrix can be used for both initial transmission and retransmission scenarios. The sub-matrices are constructed such that they can work together to provide correlation across different coding rates, enabling a single encoding apparatus to handle various coding rates and retransmission scenarios universally.
Data Source
AI summary
A method of encoding data using a parity check matrix is disclosed. The method of encoding data using a parity check matrix includes receiving information bit streams, and encoding the information bit streams using the parity check matrix which includes a systematic part and a parity part having a lower triangle type.