QC-LDPC Convolutional Coding for High-Throughput Optical FEC
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Solution Overview
Problem
Existing FEC technologies, such as LDPC block codes and time-invariant LDPC convolutional codes, face challenges in achieving high performance and throughput, especially in high-speed optical transmission systems, due to high complexity, error floor issues, and low parallelism, making them unsuitable for optical transmission.
Innovation Solution
The implementation of a time-varying periodic LDPC convolutional code with a quasi-cyclic (QC-LDPC) structure, where check matrix parameters are determined based on system performance and complexity, and a QC-LDPC check matrix is constructed to reduce complexity and improve performance, enabling high-gain and high-throughput error correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LDPC block codes are used to achieve satisfactory error correction performance, then a very great code length is required, but this leads to very high implementation complexity
Solution Approach 1:
The patent segments the LDPC block code into multiple sub-blocks and processes them through a convolutional structure with memory elements. The code is divided into segments that can be processed sequentially with shared computational resources, reducing the overall implementation complexity while maintaining the required code length for performance
Solution Approach 2:
The patent transforms the static LDPC block code into a dynamic time-varying periodic convolutional code structure. This dynamic structure allows the use of shorter effective processing windows and reusable check matrices over time periods, reducing the complexity of implementing very long codes while maintaining performance through the time-varying nature of the code
2Device complexity
If time-invariant LDPC convolutional code is used, then the structure is simple, but the performance is weak and error floor risk is high
Solution Approach 1:
The patent introduces time-varying periodicity into the LDPC convolutional code structure, where the check matrix changes over time periods. This dynamic variation breaks the repetitive patterns that cause error floors in time-invariant codes while maintaining the convolutional structure's simplicity and enabling high-parallelism-degree decoding through the periodic nature of the time-varying check matrices
3Device complexity
If time-invariant LDPC convolutional code is used, then the structure is simple, but high-parallelism-degree decoding is difficult to implement and throughput is low
Solution Approach 1:
The patent employs periodic time-varying check matrices where the same pattern of check matrices repeats over a defined period. This periodic structure enables the decoder to reuse computational resources and processing paths across different time periods, facilitating high-parallelism-degree decoding implementations and significantly increasing throughput while keeping the underlying structure relatively simple
Data Source
AI summary
The present invention discloses a coding and decoding method, apparatus, and system for forward error correction, and pertains to the field of communications. The method includes: determining check matrix parameters of time-varying periodic LDPC convolutional code according to performance a transmission system, complexity of the transmission system, and a synchronization manner for code word alignment, constructing a QC-LDPC check matrix according to the determined check matrix parameters, and obtaining a check matrix (Hc) of the time-varying periodic LDPC convolutional code according to the QC-LDPC check matrix; de-blocking, according to requirements of the Hc, data to be coded, and coding data of each sub-block according to the Hc, so as to obtain multiple code words of the LDPC convolutional code; and adding the multiple code words of the LDPC convolutional code in a data frame and sending the data frame.