Journal
IEEE PHOTONICS JOURNAL
Volume 14, Issue 3, Pages -Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JPHOT.2022.3168683
Keywords
Passive optical networks; Nonlinear optics; Optical fibers; Fiber nonlinear optics; Optical distortion; Equalizers; Adaptive optics; Directly modulated laser; machine learning; nonlinearity; optical access networks; pulse amplitude modulation
Funding
- Science Foundation Ireland (SFI) [18/SIRG/5579, 12/RC/2276_P2]
- Enterprise Ireland [DT 2019 0014A]
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This work presents the use of a directly modulated laser (DML) in TWDM-PONs, utilizing booster amplification and pre-amplification to improve power budget. The performance of NRZ-OOK, PAM-4, and PAM-8 modulation using a 10G DML is compared. Nonlinear equalizers and machine learning equalizers are applied to mitigate waveform distortions caused by limited bandwidth and laser frequency chirp. The results show that the power budget of PAM-4 54 Gbit/s signals can reach 28 dB for uplink and 35 dB for downlink after 25 km transmission over single-mode fiber.
This work presents the use of a directly modulated laser (DML) in time- and wavelength division multiplexed passive optical networks (TWDM-PONs), in which an EDFA-based booster amplification and an SOA-based pre-amplification are utilized to improve the optical power budget. We experimentally demonstrate the C-band optically amplified data transmissions and compare the performance of the non-return-to-zero on-off keying (NRZ-OOK), four and eight-level pulse amplitude modulation (PAM-4/PAM-8) using a 10-G class DML. With optical amplification, the uplink and downlink power budgets of about 28 dB and 35 dB, respectively, are achieved for the PAM-4 54-Gbit/s signals at the hard-decision forward error correction (HD-FEC) limit of 3.8x10(-3) after transmissions over a 25-km single-mode fiber link. To mitigate waveform distortions caused by the limited bandwidth, nonlinear dynamics, memory effects, and strong laser frequency chirp of the DML, especially during multi-level signal modulations, artificial neural network-based machine learning equalizers and low-complexity Volterra nonlinear equalizers are applied, which operate at the signal baud rate. The bit error ratio performance in conjunction with an enhanced power budget through the use of a low-complexity nonlinear equalizer can justify the validity of using a DML in the next-generation PONs.
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