LDPC LLR Thresholding for Lower-Complexity 5G Decoding
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Solution Overview
Problem
The 5G mobile communication system faces challenges with increased hardware mounting area and power consumption due to the use of LDPC codes for error correction, which require significant variable node and check node computations.
Innovation Solution
A method and apparatus that deactivate variable nodes with high LLR values, change LLR values of other variable nodes to a preset value, and detect check nodes based on these values, thereby reducing decoding complexity and computation amounts, and adaptively adjust the LLR threshold values to optimize the iterative decoding process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LDPC code is used for error correction in 5G communication system, then error correction performance is improved, but hardware mounting area and power consumption are increased
Solution Approach 1:
The patent extracts and processes only the most significant LLR values (those with absolute values greater than threshold Th) while discarding or simplifying processing of less significant values. This selective extraction reduces the computational burden and power consumption while maintaining error correction performance.
Solution Approach 2:
The patent applies different processing methods to different portions of the LLR data based on their significance. High-magnitude LLR values undergo full processing, while low-magnitude values receive simplified or no processing, creating local quality variations that optimize the balance between performance and power consumption.
2Reliability
If LDPC code is used for error correction, then error correction performance is improved, but device complexity is increased
Solution Approach 1:
The patent segments the LLR processing into different stages: initial LLR calculation, threshold-based filtering, and selective processing of remaining values. This segmentation divides the complex decoding task into manageable segments, reducing overall device complexity.
Solution Approach 2:
The patent performs partial processing by applying the full decoding algorithm only to a subset of variable nodes (those with |LLR| > Th) while using simplified or omitted processing for others. This partial action reduces computational complexity while maintaining sufficient error correction performance.
3Measurement precision
If iterative decoding process is performed with multiple variable node and check node computations, then decoding accuracy is improved, but computation amount is increased
Solution Approach 1:
The patent performs a preliminary filtering action before the main iterative decoding process by identifying and marking variable nodes with |LLR| > Th for full processing. This preliminary action prepares the data structure to enable more efficient subsequent processing, reducing the total computation amount required for achieving the same decoding accuracy.
Data Source
AI summary
The present disclosure relates to a pre-5th-generation (5G) or 5G communication system to be provided for supporting higher data rates beyond 4th-generation (4G) communication system such as a long term evolution (LTE). A method of a receiving apparatus in a communication system supporting a low density parity check (LDPC) code is provided. The method includes deactivating variable nodes of which absolute values of log likelihood ratio (LLR) values are greater than or equal to a first threshold value; changing LLR values of variable nodes of which absolute values of LLR values are less than a second threshold value among variable nodes other than the deactivated variable nodes to a preset value, and detecting LLR values of check nodes based on LLR values of the variable nodes other than the deactivated variable nodes.