English

Low-complexity neural network equalization for long-haul coherent transmission with cascaded semiconductor optical amplifiers

Optics 2026-03-23 v1

Abstract

In this letter, we numerically investigate a long-haul coherent data transmission system with a cascade of semiconductor optical amplifiers (SOAs). We exploit low-complexity neural networks that can be implemented in real time to compensate for the accumulated distortions induced by a cascade of SOAs. This equalization provides an order-of-magnitude reduction in bit error rate at low dispersion (in the O-band), whereas higher dispersion degrades performance.

Keywords

Cite

@article{arxiv.2603.20138,
  title  = {Low-complexity neural network equalization for long-haul coherent transmission with cascaded semiconductor optical amplifiers},
  author = {S. Bogdanov and S. Sygletos and O. Sidelnikov and G. Gomes and M. Kamalian-Kopae and S. K. Turitsyn},
  journal= {arXiv preprint arXiv:2603.20138},
  year   = {2026}
}
R2 v1 2026-07-01T11:30:05.182Z