ASIC Implementation of Time-Domain Digital Backpropagation with Deep-Learned Chromatic Dispersion Filters

We consider time-domain digital backpropagation with chromatic dispersion filters jointly optimized and quantized using machine-learning techniques. Compared to the baseline implementations, we show improved BER performance and 40% power dissipation reductions in 28-nm CMOS. Joint Filter Optimization using Deep Learning The system setup is shown in Figure 1, where the four quantization blocks can be ignored for now. Introduction Fiber nonlinearities impose a fundamental limitation on transmission performance and various nonlinear compensation schemes have been proposed. Our focus is on digital backpropagation (DBP) which emulates backward fiber propagation using digital signal processing (DSP).