LDPC Protograph Expansion for Incremental Redundancy HARQ
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Solution Overview
Problem
Conventional HARQ schemes, particularly those based on matrix-based low-density parity-check (LDPC) codes, face limitations in generating efficient codes for reliable data transmission, especially in incremental redundancy scenarios, where offline schemes map repeated bits to less reliable constellation points and row-splitting methods vary in splitting degree for different rows.
Innovation Solution
A device and method for generating a second protograph matrix P2 based on a first protograph matrix P1, involving row splitting, random integer number generation, lifting of binary matrices, and specific circulant shift configurations to create a second code H2 for retransmissions, optimizing row weights and circulant shifts for improved reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional offline HARQ schemes map repeated bits to lower reliable bits in constellation points, then memory efficiency is improved, but transmission reliability deteriorates
Solution Approach 1:
The patent inverts the conventional mapping approach by mapping retransmitted bits to higher reliable constellation points instead of lower ones. This reversal maintains memory efficiency while significantly improving transmission reliability, directly resolving the technical contradiction between these two parameters.
Solution Approach 2:
The patent changes the mapping parameter from low-reliability constellation points to high-reliability constellation points for retransmitted bits. This parameter change allows the system to maintain compact memory structure while achieving better error performance and reliability.
2Adaptability or versatility
If row-splitting schemes use different splitting degrees for different rows, then code adaptability is improved, but device complexity increases
Solution Approach 1:
The patent applies row-splitting to divide the protograph matrix into multiple rows with different splitting degrees. This segmentation enables flexible code adaptation to various channel conditions while maintaining manageable device complexity through systematic construction methods.
Solution Approach 2:
The patent creates a universal row-splitting framework that can adapt to different transmission scenarios and channel conditions. The same basic mechanism serves multiple functions: adapting code rate, adjusting to channel quality, and maintaining compatibility with existing HARQ structures.
3Ease of manufacture
If fixed retransmitted payload is used in LTE system, then implementation simplicity is improved, but transmission reliability deteriorates
Solution Approach 1:
The patent introduces dynamic payload construction for retransmissions, where the retransmitted payload is adaptively generated based on channel conditions and previous transmission outcomes. This dynamic approach improves reliability while maintaining reasonable implementation complexity through algorithmic generation.
Solution Approach 2:
The system generates retransmitted payloads autonomously based on the original transmission and channel feedback, without requiring complex external coordination. This self-service mechanism improves reliability while keeping implementation simple through automated payload construction.
Data Source
AI summary
Devices and methods are disclosed for generating on the basis of a first protograph matrix P1 of size m×n, wherein the first protograph matrix P1 defines a first code H1, a second protograph matrix P2 of size (m+d)×(n+d), wherein the second protograph matrix P2 defines a second code H2. The device comprises a processor configured to: generate an auxiliary protograph matrix P′ of size (m+d1)×(n+d1) on the basis of the first protograph matrix P1 using row splitting; generate d2 random integer numbers, wherein d2=d−d1; generate a binary matrix M of size d2×(n−m), wherein rows of the binary matrix M are generated on the basis of the d2 random integer numbers; generate a matrix M′ by lifting the binary matrix M; Other operation steps are also included.