LDPC Decoding with Adaptive Flip Perturbation for Short Codes
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Solution Overview
Problem
Existing LDPC decoding methods face performance degradation and increased computational complexity when applied to short code lengths in ultra-reliable and low latency communications (URLLC), failing to meet stringent reliability and latency requirements due to structural limitations of BP decoding schemes.
Innovation Solution
The proposed LDPC decoding method employs a perturbation scheme that selects a perturbation space based on code length and maximum perturbation rounds, performing flip perturbations in parallel to improve decoding performance while reducing computational complexity, using a flip perturbation scheme that adds noise to selected symbols with maximum amplitude opposite to their LLR signs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If belief propagation decoding scheme is applied to short LDPC codes, then decoding performance is sufficient for long codes, but decoding performance deteriorates for short codes due to structural limitations
Solution Approach 1:
The patent applies dynamic perturbation strategies where the perturbation space dimension and perturbation patterns are adaptively adjusted based on the code length and decoding iteration stage. For short codes, the system dynamically increases perturbation intensity and adjusts the number of perturbation rounds, allowing the decoding scheme to adapt to different code length requirements rather than using a fixed approach.
Solution Approach 2:
The system changes key parameters including perturbation space dimension, perturbation amplitude, and maximum perturbation rounds based on code length. For short LDPC codes, the patent increases the perturbation space dimension and adjusts perturbation parameters to compensate for structural limitations, thereby improving decoding performance across different code lengths.
2Reliability
If iterative perturbation is applied to improve short code decoding performance, then decoding performance improves, but computational complexity and decoding time increase
Solution Approach 1:
The patent applies partial perturbation by selecting a specific dimension of perturbation space rather than perturbing all code bits. The system performs perturbation on a subset of bits determined by the perturbation space dimension, which is optimized based on code length. This partial action approach reduces computational complexity compared to full perturbation while still improving decoding performance for short codes.
Solution Approach 2:
The patent segments the perturbation process into multiple rounds with different perturbation patterns. Instead of applying one complex perturbation, the system divides the process into sequential rounds where each round applies a specific perturbation pattern to different bit positions. This segmentation allows the system to achieve better decoding performance through multiple targeted perturbations rather than a single comprehensive perturbation, managing computational complexity more effectively.
3Reliability
If detailed perturbation operation is applied to improve decoding performance, then decoding performance improves, but additional computational complexity occurs and flexibility is restricted
Solution Approach 1:
The patent implements a universal perturbation framework that can handle different code lengths, perturbation rounds, and perturbation patterns through a single unified structure. The system uses a configurable perturbation space dimension and selectable perturbation patterns that work across various LDPC code configurations. This multi-functional approach maintains decoder flexibility while improving performance, as the same basic mechanism adapts to different requirements without requiring separate specialized structures.
Data Source
AI summary
An LDPC decoding method of a received signal including a plurality of received symbols is provided. A decoding apparatus selects a perturbation space in which perturbation is to be performed based on a code length of the received signal and a maximum number of perturbation rounds indicating a number of perturbation rounds that can be performed, and performs a perturbation round. The decoding apparatus performs perturbation on a corresponding received symbol among the plurality of received symbols in each perturbation round, and decodes the received signal on which the perturbation has been performed. The decoding apparatus determines that decoding is successful when there is a perturbation round in which a decoding result of the received signal satisfies a predetermined condition.