Reduced-State Sequence Estimation for Soft-Decision FEC Decoding
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Solution Overview
Problem
Existing communication systems are power hungry and spectrally inefficient, particularly when dealing with phase noise and non-linear distortion, leading to a gap between maximum and actual spectral efficiency, especially with higher-order modulation schemes.
Innovation Solution
A method and system that improve bit error rate (BER) performance using a sequence estimation algorithm and forward error correction (FEC), incorporating partial response pulse shaping filters and equalizers to manage inter-symbol interference and non-linearity, with a reduced-state sequence estimation algorithm to generate soft decisions based on symbol survivors and histograms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If complex linear modulation schemes such as QAM are used to increase spectral efficiency, then throughput increases, but performance degrades in the presence of phase noise and non-linear distortion
Solution Approach 1:
The patent transforms the modulation scheme from conventional linear QAM to a non-linear modulation scheme based on partial response signaling. This fundamental parameter change in the modulation approach enables the system to achieve high spectral efficiency while being inherently more tolerant to non-linear distortion and phase noise, directly resolving the contradiction between throughput and reliability under adverse channel conditions
Solution Approach 2:
The patent converts the harmful effect of non-linear distortion into a beneficial feature by designing a non-linear modulation scheme where the partial response filtering intentionally shapes the signal to exploit rather than suffer from non-linearities. The controlled non-linearity in the pulse shaping filter becomes an advantage that improves robustness while maintaining spectral efficiency
2Productivity
If higher-order modulation is used to drive more throughput, then spectral efficiency increases, but the gap to Shannon capacity bound increases due to sensitivity to non-linear distortion
Solution Approach 1:
The patent employs high-order non-linear modulation with partial response signaling that fundamentally changes how information is encoded and transmitted. This parameter change enables achieving higher throughput while maintaining proximity to Shannon capacity by making the modulation inherently more robust to the non-linear distortions that would otherwise cause information loss
3Device complexity
If reduced-state sequence estimation algorithm is used, then complexity is reduced, but soft decision output quality must be maintained for effective FEC decoding
Solution Approach 1:
The patent applies reduced-state sequence estimation that examines only a subset of possible signal paths rather than all possible paths. This partial action approach significantly reduces computational complexity while the algorithm is designed to maintain sufficient soft decision output quality by focusing computational resources on the most probable paths, achieving an optimal balance between complexity and decoding performance
Data Source
AI summary
A receiver may be operable to receive an inter-symbol correlated (ISC) signal, and generate a plurality of soft decisions as to information carried in the ISC signal. The soft decisions may be generated using a reduced-state sequence estimation (RSSE) process. The RSSE process may be such that the number of symbol survivors retained after each iteration of the RSSE process is less than the maximum likelihood state space. The plurality of soft decisions may comprise a plurality of log likelihood ratios (LLRs). Each of the plurality of LLRs may correspond to a respective one of a plurality of subwords of a forward error correction (FEC) codeword.