ML-assisted Subband Learned Digital Backpropagation for Nonlinearity Compensation in Wideband Optical Systems

TL;DR

This paper introduces a subband-based learned digital backpropagation framework that reduces computational complexity and improves performance in wideband optical systems through joint optimization and sparsification.

Contribution

It proposes a novel subband decomposition and trainable filtering approach for digital backpropagation, enhancing efficiency and accuracy in wideband optical communication.

Findings

Outperforms conventional DBP in simulation tests.

Achieves better performance-complexity trade-offs.

Requires fewer propagation steps for similar or improved SNR gains.

Abstract

Digital backpropagation (DBP) is one of the most effective techniques for compensating nonlinear distortions in coherent optical fiber communication systems. However, its practical application to wideband transmission remains limited by high computational complexity caused by large channel memory and the requirement for fine spatial discretization. In this work, we propose a subband-based learned digital backpropagation (SbL-DBP) framework for wideband optical transmission systems. The received signal is decomposed into multiple subbands, enabling independent frequency-domain compensation of the chromatic dispersion with reduced effective channel memory and lower computational complexity. Nonlinear intra- and inter-subband interactions are addressed in the time domain using a trainable multi-input multi-output filtering structure. The parameters of the proposed framework are jointly optimized using end-to-end gradient-based learning. In addition, sparsification techniques are employed to remove insignificant coefficients and further reduce computational complexity. Numerical simulations of an 11$\times$40~Gbaud WDM RRC-16QAM 20$\times$100 km transmission system demonstrate that the proposed method provides a superior performance--complexity trade-off compared to conventional DBP and enhanced DBP. In the low- and medium-complexity regimes, SbL-DBP provides higher signal-to-noise ratio gains while requiring fewer propagation steps.