There is an urgent reflection on traditional nonlinear signal processing methods in communications before Artificial Intelligence (AI) dominates the field. It implies a need to reassess or reinterpret established theories and tools, highlighting the tension between data-driven and model-based approaches. This paper calls for preserving valuable insights from classical signal processing while exploring how they can coexist or integrate with emerging AI methods.
@article{arxiv.2511.02493,
title = {Before AI Takes Over: Rethinking Nonlinear Signal Processing in Communications},
author = {Ana Pérez-Neira and Marc Martinez-Gost and Miguel Ángel Lagunas},
journal= {arXiv preprint arXiv:2511.02493},
year = {2025}
}