QC-LDPC Shift Values With Rate-Specific ACE Constraints
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Solution Overview
Problem
Existing solutions for constructing parity-check matrices in LDPC codes face challenges in avoiding harmful cycles, particularly in high-rate parts of rate-compatible LDPC codes, where ACE constraints for full parity-check matrices allow harmful cycles with low connectivity, and it is difficult to find cyclic shifts that fulfill tough ACE constraints for large cycles.
Innovation Solution
A lifting method is introduced that applies different approximate cycle extrinsic message degree (ACE) constraints for different code rates and cycle lengths, optimizing ACE constraints for each shift size separately to ensure short cycles have higher connectivity than longer cycles, and specifying separate constraints for systematic and parity bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If ACE constraints are applied to the full parity-check matrix, then cycle connectivity is improved, but harmful cycles with low connectivity still occur in high-rate parts of rate-compatible LDPC codes
Solution Approach 1:
The patent segments the parity-check matrix into different rate parts (base matrix and extension parts) and applies different ACE constraints to each segment. Specifically, it applies stricter ACE constraints to the base matrix and relaxed constraints to extension parts, allowing different connectivity requirements for different code rates. This resolves the contradiction by ensuring high connectivity where needed while avoiding harmful cycles in high-rate extensions.
Solution Approach 2:
The patent applies different quality levels of ACE constraints to different parts of the code structure. The base matrix (lower code rates) receives higher ACE constraints for better connectivity, while extension parts (higher code rates) receive lower constraints. This local differentiation allows the system to maintain high reliability for base codes while enabling flexible high-rate extensions without harmful cycles.
2Reliability
If tough ACE constraints are applied to avoid harmful cycles, then cycle connectivity improves, but it becomes difficult to find cyclic shifts that fulfill the constraints for large cycles
Solution Approach 1:
The patent divides the ACE constraint application into segments: strict constraints for the base matrix and relaxed constraints for extension parts. This segmentation reduces the overall complexity of finding valid cyclic shifts, as the extension parts have more freedom in shift selection while the base matrix ensures proper connectivity.
Solution Approach 2:
The patent changes the ACE constraint parameter values depending on the code rate and matrix section. By adjusting the threshold values of ACE constraints based on the specific part of the parity-check matrix being constructed, the system finds a balance between ensuring connectivity and allowing feasible shift coefficient selection.
3Object-affected harmful factors
If different ACE constraints are applied for different code rates, then harmful cycles are avoided in high-rate parts, but the lifting algorithm complexity increases
Solution Approach 1:
The patent segments the lifting process into two phases: base matrix lifting with strict ACE constraints and extension part lifting with relaxed constraints. This segmentation allows the algorithm to systematically handle different code rates with appropriate constraints, avoiding harmful cycles while maintaining manageable complexity through a structured approach.
Data Source
AI summary
According to some embodiments, a method for use in a wireless transmitter of a wireless communication network comprises encoding information bits using a parity check matrix (PCM) and transmitting the encoded information bits to a wireless receiver. The parity click matrix (PCM) is optimized according to two or more approximate cycle extrinsic message degree (ACE) constraints. In some embodiments, a first portion of the PCM is optimized according to a first ACE constraint and a second portion of the PCM is optimized according to a second ACE constraint.