Artificial neural network nonlinear equalizer for coherent optical OFDM

We propose a novel low-complexity artificial neural network (ANN)-based nonlinear equalizer (NLE) for coherent optical orthogonal frequency-division multiplexing (CO-OFDM) and compare it with the recent inverse Volterra-series transfer function (IVSTF)-based NLE over up to 1000 km of uncompensated links. Demonstration of ANN-NLE at 80-Gb/s CO-OFDM using 16-quadrature amplitude modulation reveals a Q-factor improvement after 1000-km transmission of 3 and 1 dB with respect to the linear equalization and IVSTF-NLE, respectively.

Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ∼1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.