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- W4200165123 abstract "Directly modulated lasers (DMLs) are the most viable transmitter choice in a direct-detection optical access network. Pulse amplitude modulation (PAM) can greatly increase spectral efficiency and can compensate for the issue of bandwidth limitation in a DML. However, the nonlinear responses, memory effects, and interaction between the fiber's chromatic dispersion and frequency chirp are other dominant sources of impairments in a DML-based transmission systems and are often seen as the major obstacles to realize multi-level signals in an IM/DD optical access network. In this paper, we experimentally validate a transmission of 54-Gbit/s PAM-8 signal with optical amplification over a 25-km standard single-mode fiber (SSMF) and observe a power budget of about 30 dB by using an artificial neural network-based nonlinear equalizer called ANN-NLE for the application of a DML-based passive optical network (PON). Furthermore, we investigate and verify the performance of the system under different transmission scenarios and compare the performance of the ANN-NLE with the traditional feed-forward equalizer (FFE) and Volterra equalizer (VE)." @default.
- W4200165123 created "2021-12-31" @default.
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- W4200165123 date "2021-10-25" @default.
- W4200165123 modified "2023-10-16" @default.
- W4200165123 title "54-Gbit/s PAM-8 Transmission in Next-Generation Passive Optical Networks using Directly Modulated Lasers with Machine Learning Techniques" @default.
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- W4200165123 doi "https://doi.org/10.1109/icumt54235.2021.9631606" @default.
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