Time-Varying QC-LDPC Convolutional Coding With Periodic Check Matrices
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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-gain performance and high 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
A time-varying periodic LDPC convolutional code with a quasi-cyclic LDPC structure is developed, where check matrix parameters are determined based on system performance and complexity, and a QC-LDPC block code is constructed to form a check matrix that splits into sub-matrices, reducing implementation complexity and enhancing decoding efficiency.
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 smaller sub-blocks that are processed as separate LDPC convolutional code units. Each sub-block is encoded independently with its own check matrix, allowing parallel processing and reducing the complexity of any single encoding operation while maintaining overall error correction performance through the convolutional structure.
Solution Approach 2:
The patent transitions from static LDPC block codes to dynamic LDPC convolutional codes where the check matrix changes over time according to a time-varying periodic pattern. This dynamic structure allows the system to achieve good error correction performance with shorter effective code lengths at any given time step, reducing implementation complexity while maintaining reliability.
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 by periodically changing the check matrix according to a predetermined pattern. This dynamic variation prevents error floors by ensuring that the same error patterns do not repeatedly occur, while the periodic nature maintains reasonable structural simplicity and implementation feasibility.
Solution Approach 2:
The patent changes the parameters of the check matrix over time, specifically the connection patterns between variable nodes and check nodes in the Tanner graph representation. By varying these parameters periodically, the system achieves better error correction performance and avoids error floors while maintaining a systematic approach to code design.
3Reliability
If time-varying periodic LDPC convolutional code is used, then error correction performance improves, but decoding complexity increases
Solution Approach 1:
The patent employs periodic action in the check matrix variation, where the time-varying pattern repeats after a fixed period. This periodicity allows the decoder to reuse computation patterns and storage structures across different time periods, reducing the effective decoding complexity compared to fully time-varying codes. The receiver can implement efficient buffering and processing by exploiting this periodic structure.
4Reliability
If LDPC block code is used, then error correction capability is strong, but transmission efficiency is reduced due to great code length requirements
Solution Approach 1:
The patent segments the long LDPC block code into multiple shorter LDPC convolutional code units that are transmitted sequentially. This segmentation allows for more efficient transmission by reducing the latency associated with encoding and decoding very long codes, while the convolutional structure enables continuous encoding and decoding operations that improve transmission efficiency.
Solution Approach 2:
The patent performs preliminary organization of the code structure by pre-defining the time-varying periodic pattern and sub-block divisions. This preliminary structuring allows the transmitter and receiver to efficiently manage the encoding and decoding processes without requiring buffering of extremely long code sequences, thereby improving transmission efficiency while maintaining strong error correction capability.
Data Source
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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. In the present invention, forward error correction is performed by using time-varying periodic LDPC convolutional code with a QC-LDPC structure. The check characteristics of the QC-LDPC may decrease the complexity of the check; furthermore, the performance of LDPC convolutional code is better than that of LDPC block codes, and the performance of time-varying LDPC convolutional code is better than that of time-invariant LDPC convolutional code. Therefore, the present invention may be applicable to the high-speed optical transmission system and meet the requirements of high-gain performance and high throughput.