SbL-DBP decomposes signals into subbands for efficient dispersion handling and applies end-to-end trained MIMO filters plus sparsification to compensate nonlinear effects, delivering higher SNR gains with fewer steps than conventional DBP in 11-channel 2000 km simulations.
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ML-assisted Subband Learned Digital Backpropagation for Nonlinearity Compensation in Wideband Optical Systems
SbL-DBP decomposes signals into subbands for efficient dispersion handling and applies end-to-end trained MIMO filters plus sparsification to compensate nonlinear effects, delivering higher SNR gains with fewer steps than conventional DBP in 11-channel 2000 km simulations.