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• W2941885305 abstract "We propose and experimentally demonstrate a multiple input multiple output - artificial neural network (MIMO-ANN) nonlinear equalizer (NLE) to process the complex quadrature amplitude modulation (QAM) signal in a single-sideband (SSB) self-coherent detection (SCD) system. In the proposed scheme, a 2-by-2 MIMO structure with two ANNs is employed to effectively mitigate the signal distortions induced by in-phase and quadrature (IQ) imbalance and fiber nonlinear effects. By using the proposed MIMO-ANN NLE, we successfully transmit a 112-Gb/s SSB 16-QAM signal over a single-span 120-km single mode fiber (SMF) in a direct detection (DD) system with a bit error rate (BER) lower than 3.8 × 10-3. We also conduct a comparative study between the proposed MIMO-ANN NLE, a feedforward equalizer (FFE), a NLE consisting of two independent real-valued Volterra filters, and a MIMO-Volterra filter. The proposed MIMO-ANN NLE outperforms other equalizers with the longer fiber length and thus stronger nonlinearities, since it can easily approximate a complicated nonlinear function. To the best of our knowledge, this is the first experimental demonstration of an ANN-based equalizer in an SSB SCD system." @default.
• W2941885305 created "2019-05-03" @default.
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• W2941885305 date "2019-04-22" @default.
• W2941885305 modified "2023-10-17" @default.
• W2941885305 title "112-Gb/s SSB 16-QAM signal transmission over 120-km SMF with direct detection using a MIMO-ANN nonlinear equalizer" @default.
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• W2941885305 doi "https://doi.org/10.1364/oe.27.012794" @default.
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