Multi-Symbol Reservoir Computing-Based Equalization for PAM-4 IM/DD Transmission

Inter-symbol interference (ISI) induced by chromatic dispersion combined with square-law detection is a key impairment in intensity-modulated and directly detected (IM/DD) links. The ISI significantly degrades the link performance and limits fiber transmission reach. The IM/DD receivers cannot rely on equalizers with high inference phase computational complexity (CC) such as deep neural networks. However, high CC can be reduced by applying a low complexity reservoir computing (RC) combined with a multi-symbol equalization scheme. In this work, we numerically investigate the multi-symbol RC equalizer applied to a spectrally sliced receiver for 32-GBd PAM-4 transmission in single-mode fiber. We show that up to 17 sequential symbols can be equalized simultaneously while still achieving transmission performance of 68 km distance below the KP4 FEC threshold. The multi-symbol method can significantly reduce CC to a couple of hundred multiplications per symbol compared to a single-symbol. The RC equalization has a high potential for receiver-end integration due to its reduced CC and easy training.