Finite-Precision Optimization of Time-Domain Digital Back Propagation by Inter-Symbol Interference Minimization

Abstract

We consider the effects of limited-resolution arithmetic on the performance of Time-Domain Digital Back Propagation. By minimizing resulting ISI of the quantized FIR impulse responses, we can achieve floating-point performance using 9-bit pairwise optimized filter coefficients.

Deep Learning of the Nonlinear Schrödinger Equation in Fiber-Optic Communications

“…However, 70-tap filters are required to obtain acceptable accuracy using FDS [5]. Similar observation apply to the results in [12], [13], [20], [21], i.e., the required filter length is significantly longer than predicted by (2).…”

“…Time-domain FIR filtering has been suggested for DBP in, e.g., [5], [12], [13], [20], [21]. In the SSFM, approximating H(ω) with a short FIR filter can be interpreted as a truncation of A δ to obtain a sparse banded matrix.…”

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

“…We have studied TD-DBP based on deep-learned CD filters from an ASIC perspective. It was shown that the obtained filters have similar signal resolution requirements compared to our previous work 5,6 , and significantly reduced coefficient resolution requirements. Moreover, reduced filter lengths directly translate into lower power dissipation and chip area.…”

“…A major issue with DBP based on the splitstep Fourier method (SSFM) is the large complexity caused by the fast Fourier transforms (FFTs). Time-domain DBP (TD-DBP) with finite impulse response (FIR) filters may be competitive [5][6][7][9][10][11][12] , assuming that the chromatic dispersion (CD) steps are sufficiently short. Design methods for the FIR filters include least squares 5,6,13 or wavelets 10 , but accumulating truncation errors due to repeated filter use can lead to severe performance degradations.…”

Wideband Time-Domain Digital Backpropagation via Subband Processing and Deep Learning

“…Real-time digital backpropagation (DBP) based on the split-step Fourier method (SSFM) is widely considered to be impractical due to the complexity of the chromatic dispersion (CD) steps. To address this problem, finite impulse response (FIR) filters may be used instead of fast Fourier transforms (FFTs) to perform time-domain CD filtering [1][2][3][4][5][6][7] . Indeed, the FIR filters can be as short as 3 taps per SSFM step, provided that the step size is sufficiently small (i.e., many steps are used) and the filters in all steps are jointly optimized 6 .…”