Collaborative FFE-assisted simplified soft-output MLSE with LDPC for high-speed IM-DD transmissions

Area of Science:

• Optical communication systems
• Signal processing
• Information theory

Background:

• Simplified soft-output maximum likelihood sequence estimation (sMLSE) can lead to undetermined log-likelihood ratio (LLR) magnitudes.
• This limitation degrades the performance of soft-decision forward error correction (SD-FEC) decoding, particularly in high-order modulation schemes like PAM-8.
• Existing methods struggle to maintain SD-FEC performance when simplifying MLSE algorithms.

Purpose of the Study:

• To propose and evaluate a novel feed-forward equalizer (FFE)-assisted sMLSE (sMLSE) approach.
• To address the performance degradation caused by undetermined LLRs in simplified MLSE algorithms.
• To reduce the computational complexity of MLSE while maintaining high decoding performance.

Main Methods:

• Developed an FFE-assisted sMLSE by integrating MLSE with soft-decision low-density-parity-check (LDPC) decoding.
• Utilized pre-set FFE to calculate LLRs, replacing undetermined LLRs in the simplified sMLSE.
• Conducted experimental transmissions of 184-Gb/s PAM-4 and 255-Gb/s PAM-8 signals in an intensity-modulation/direct-detection (IM-DD) system at C-band.

Main Results:

• The FFE-assisted sMLSE effectively compensates for the degradation of LLR quality.
• Experimental results demonstrate significant performance improvements in SD-FEC decoding.
• For 255-Gb/s PAM-8 transmissions, the proposed method achieved comparable SD-FEC performance to conventional sMLSE with an 85% complexity reduction.

Conclusions:

• The FFE-assisted sMLSE is a viable solution for mitigating performance loss in simplified MLSE.
• This approach enhances the efficiency of digital communication systems, especially those employing high-order modulation.
• The proposed method offers a substantial reduction in computational complexity without compromising decoding accuracy.