Digital Back Propagation via Sub-band Processing in Spatial Multiplexing Systems

An advanced digital backward-propagation (DBP) method using a separate-channels approach (SCA) is investigated for the compensation of inter-channel nonlinearities in spatial- and wavelength-multiplexed systems. Compared to the conventional DBP, intra- and inter-mode cross-phase modulation can be efficiently compensated by including the effect of the inter-channel walk-off in the nonlinear step of the split-step Fourier method. We found that the SCA-DBP relaxes the step size requirements by a factor of 10, while improving performance by 0.8 dB for large walk-off and strong linear coupling. For the first time, it is shown that in spatial multiplexed systems transmission performance can be improved by sub-band processing of back propagated channels

Experimental demonstration of dispersion tolerant end-to-end deep learning-based IM-DD transmission system

We experimentally demonstrate an IM-DD system relying on deep neural networks from transmitter to receiver delivering 42 Gb/s over 20 and 40 km at 1550 nm below 3.8×10−3 . The ANN is trained to tolerate deviations in dispersion by as much as ±170ps/n