DFE Error Propagation Mitigation in Soft-Input Decoding
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Solution Overview
Problem
Next-generation passive optical networks (PON) face significant inter-symbol interference (ISI) due to bandwidth limitations and increased chromatic dispersion, which degrades the performance of decision feedback equalizers (DFE) and leads to error propagation, requiring complex solutions to mitigate these issues.
Innovation Solution
A method and apparatus that perform decision feedback equalization and postprocess the output to determine a modified log-likelihood ratio value based on previous samples, reducing the impact of DFE error propagation without modifying the equalizer, using a receiver with a decision feedback equalizer, a determining module, and a decoder to improve log-likelihood ratio calculation quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If decision feedback equalization is used to mitigate inter-symbol interference, then signal quality is improved, but error propagation occurs degrading decoding performance
Solution Approach 1:
The patent introduces an intermediary log-likelihood ratio (LLR) calculation step between the DFE equalizer and the decoder. Instead of directly passing DFE decisions to the decoder, the system calculates LLR values that incorporate probabilistic information about previous symbols, acting as a mediator that softens the hard decisions from the DFE and reduces error propagation to the decoder
Solution Approach 2:
The patent implements feedback by using previously decoded symbol information to adjust the current symbol's LLR calculation. The LLR for the current symbol incorporates information about previous symbols through the formula LLR(x[k]) = LLR_DFEx[k]) + Σ log((1-p[j])/p[j]), where p[j] is the probability of previous symbols. This feedback mechanism allows the system to compensate for potential errors in previous decisions
2Reliability
If multiple parallel DFEs are used to mitigate error propagation, then decoding reliability is improved, but system complexity increases significantly
Solution Approach 1:
Instead of implementing multiple parallel DFE structures as suggested in prior art, the patent creates a virtual copy of the decision-making process through probabilistic LLR calculations. The system maintains a single DFE but copies the decision information into soft probabilistic form (LLR values) that can be manipulated mathematically to achieve similar error mitigation effects without the hardware complexity of multiple parallel equalizers
3Reliability
If DFE is moved to the transmitter for nonlinear precoding, then error propagation is eliminated, but transmitter modifications are required
Solution Approach 1:
Instead of moving the DFE to the transmitter as prior art suggests, the patent inverts the approach by keeping the DFE at the receiver but applying nonlinear precoding-like techniques in the opposite direction - using feedback from received symbols to adjust current symbol interpretation. This eliminates error propagation effects without requiring any transmitter hardware modifications
Data Source
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AI summary
The present invention discloses a method in a receiver of a communication link, comprising: performing decision feedback equalization for received samples that are binary modulated, obtaining equalized samples; determining a modified log-likelihood ratio value corresponding to a current sample based at least on a value related to the equalized sample corresponding to the current sample and a respective modified log-likelihood ratio value corresponding to at least one previous sample; and decoding the current sample based on the modified log-likelihood ratio value corresponding to the current sample.