LDPC Channel Encoding with Variable Block Sizes and Rates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current LDPC code designs face challenges in supporting various input lengths and coding rates, particularly for short information word lengths and fixed coding rates, due to limitations in lifting methods and trapping set characteristics.
Innovation Solution
The proposed method involves designing LDPC codes using a lifting technique and considering trapping set characteristics, with a channel encoding method that identifies a block size and shift value sequence for LDPC encoding and decoding, employing a permutation matrix of size ZXZ, where the shift value sequence is predetermined for circular shifts, to support variable lengths and rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional LDPC code designs are used, then implementation is straightforward, but they cannot support various input lengths and coding rates effectively
Solution Approach 1:
The patent creates a universal LDPC code design that can handle multiple input lengths and coding rates through a single base matrix structure. The base matrix with carefully designed column weights and trapping set characteristics serves as a universal foundation that adapts to different communication requirements without requiring separate code designs for each scenario.
Solution Approach 2:
The patent enables adaptability by changing parameters such as the lifting size and selecting different column subsets from the base matrix. By varying these parameters, the same base matrix can generate LDPC codes suitable for different input lengths and coding rates, achieving versatility through parameter adjustment rather than structural redesign.
2Adaptability or versatility
If lifting methods are used to support variable lengths, then code flexibility increases, but trapping set characteristics deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-designing the base matrix with optimal trapping set characteristics before the lifting process. The column weights and connections are carefully arranged in advance to minimize trapping sets, ensuring that even after lifting to support variable lengths, the fundamental reliability properties are preserved.
Solution Approach 2:
The patent applies local quality by ensuring that different parts of the base matrix have optimized local structures. Specific columns are designed with particular weight distributions and connection patterns that locally minimize trapping sets, while the overall matrix maintains flexibility for various lifting operations. This local optimization ensures reliability is maintained across the entire code structure.
3Reliability
If dedicated LDPC codes are designed for short information words, then error correction performance improves, but design complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the code structure into a base matrix and multiple lifted versions. The base matrix contains the essential error correction properties optimized for short information words, while the lifting operation segments the generation of different code lengths from this unified foundation. This reduces design complexity compared to creating entirely separate codes for each length.
Solution Approach 2:
The patent uses copying by creating multiple instances of the optimized base matrix structure through the lifting operation. Rather than designing separate dedicated codes for each short information word length, the same optimized structural patterns are copied and scaled through lifting, maintaining error correction performance while reducing overall design complexity.
Data Source
Figure 1~2
Figure 3a
Figure 3b
AI summary
A pre-5th-generation (pre-5G) or 5G communication system for supporting higher data rates beyond a 4th-generation (4G) communication system, such as long term evolution (LTE) is provided. A channel encoding method in a communication or broadcasting system includes identifying an input bit size, determining a block size (Z), determining a low density parity check (LDPC) sequence to perform LDPC encoding, and performing the LDPC encoding based on the LDPC sequence and the block size.