Abstract
Semiconductor optical amplifier (SOA) is widely used for power amplification in O-band, particularly for passive optical networks (PONs) which can greatly benefit its advantages of simple structure, low power consumption and integrability with photonics circuits. However, the annoying nonlinear pattern effect degrades system performance when the SOA is needed as a pre-amplifier in PONs. Conventional solutions for pattern effect mitigation are either based on optical filtering or gain clamping. They are not simple or sufficiently flexible for practical deployment. Neural network (NN) has been demonstrated for impairment compensation in optical communications thanks to its powerful nonlinear fitting ability. In this paper, for the first time, NN-based equalizer is proposed to mitigate the SOA pattern effect for 50G PON with intensity modulation and direct detection. The experimental results confirm that the NN-based equalizer can effectively mitigate the SOA nonlinear pattern effect and significantly improve the dynamic range of receiver, achieving 29-dB power budget with the FEC limit at 1e-2. Moreover, the well-trained NN model in the receiver side can be directly placed at the transmitter in the optical line terminal to pre-equalize the signal for transmission so as to simplify digital signal processing in the optical network unit.
Highlights
The explosive bandwidth consuming services, like virtual reality (VR), 8K videos, and cloud services drive capacity upgrade of the access network to satisfy ever-increasing users’ demand
For the first time, we propose to use a well-trained Neural network (NN)-based pre-equalizer to mitigate semiconductor optical amplifier (SOA) pattern effect in a 50G passive optical networks (PONs) system with intensity modulation and direct detection (IMDD)
To understand how the NN works, we start from the BtB case and first measure the eye diagram of 25Gbaud PAM-4 signal directly detected by a PD without SOA for pre-amplification
Summary
The explosive bandwidth consuming services, like virtual reality (VR), 8K videos, and cloud services drive capacity upgrade of the access network to satisfy ever-increasing users’ demand. Passive optical network (PON) has been demonstrated to be the most promising and cost-effective broadband access technology. Since high-speed signal are sensitive to fiber dispersion, O-band is selected as the working waveband for 100G PON [7] at the expense of a higher insertion loss of 0.33 dB/km, which on the other hand would put more pressures on the system power budget. Avalanche photodiode (APD) with high receiver sensitivity is considered as the receiver in the optical network unit (ONU) to ensure enough power budget for downstream. The SOA works as a pre-amplifier to increase the signal power injected into the PD. The nonlinear pattern effect due to the SOA gain saturation degrades performance, for high-speed signal [8].
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