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Combining a channel memory-shortening filter with maximum likelihood sequence estimation (MLSE) effectively reduces MLSE complexity in low-bandwidth optical fiber communication systems. In this paper, we propose an enhanced decision feedback equalizer (DFE)-MLSE for high-speed fiber optic communication systems. This enhanced algorithm builds on our previous work by introducing a dispersion filter that adjusts channel memory length and by directly applying feedback filter coefficients in MLSE branch metric calculations. These advancements improve channel equalization performance, which we experimentally validate in a pulse-amplitude modulation level-4 (PAM-4) system. At a transmission rate of 112 GBd and a distance of 2 km, the enhanced DFE-MLSE achieves an approximate 0.5 dB improvement over the previous DFE-MLSE at a bit error rate of 3.8·10, demonstrating its potential for 200 Gbps transmission in short-reach optical networks.
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http://dx.doi.org/10.1364/OE.551074 | DOI Listing |
Opt Express
March 2025
Combining a channel memory-shortening filter with maximum likelihood sequence estimation (MLSE) effectively reduces MLSE complexity in low-bandwidth optical fiber communication systems. In this paper, we propose an enhanced decision feedback equalizer (DFE)-MLSE for high-speed fiber optic communication systems. This enhanced algorithm builds on our previous work by introducing a dispersion filter that adjusts channel memory length and by directly applying feedback filter coefficients in MLSE branch metric calculations.
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