M-ary Differential Decoding LDPC Optimization
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Solution Overview
Problem
In high-speed optical transmission systems, the bit error rate is increased due to bit error spread during differential decoding, which affects system performance and accuracy of signal transmission.
Innovation Solution
A decoding method and apparatus that performs M-ary differential decoding using the Bahl-Cocke-Jelinek-Raviv algorithm, followed by optimizing the degree distribution of LDPC codes for FEC decoding, and incorporating interleaving processes to reduce bit error rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If differential decoding is performed to prevent data stream polarity reversal, then carrier phase ambiguity is resolved, but bit error spread occurs leading to increased bit error rate
Solution Approach 1:
The patent segments the decoding process into multiple independent stages: differential decoding stage, bit error correction stage, and optional iterative refinement stages. Each stage processes specific aspects of the signal separately, allowing bit error correction to be applied selectively without reprocessing the entire signal through differential decoding, thereby preventing error propagation while maintaining phase ambiguity resolution.
Solution Approach 2:
The patent implements feedback mechanisms where decoding results and error statistics from previous processing stages are fed back to adjust and optimize subsequent decoding operations. This feedback loop enables the system to learn from previous errors and improve bit error rate performance while maintaining the benefits of differential decoding for phase ambiguity resolution.
2Measurement precision
If iterative decoding processing is performed to reduce bit error rate, then signal transmission accuracy is improved, but processing time and computational complexity increase
Solution Approach 1:
The patent performs preliminary error correction and processing on decoded signals before they are fully integrated into the main decoding pipeline. By pre-processing signals to correct obvious errors and filter noise beforehand, the iterative decoding process requires fewer iterations to achieve the same level of accuracy, thereby reducing overall processing time while maintaining high signal transmission accuracy.
Solution Approach 2:
The patent applies partial iterative processing where only the necessary portion of the signal requiring correction undergoes full iterative decoding, while other portions use simplified processing. This selective approach reduces overall computational complexity and processing time while still achieving the required signal transmission accuracy for the most critical parts of the signal.
Data Source
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AI summary
Embodiments of the present invention provide a decoding method and apparatus. The method includes: acquiring a demodulation signal; acquiring a first decoding signal, where the first decoding signal is a signal fed back after the ith M-ary differential decoding processing is performed on the demodulation signal, and i is an integer greater than or equal to 0; and performing M-ary differential decoding processing on the demodulation signal according to the first decoding signal, to obtain a second decoding signal. The first decoding signal that is fed back is added and input to a decoder, thereby lowering a bit error rate of an output signal.