LAUSR

Photonic reservoir computing (RC) enables us to introduce artificial neural networks (ANNs) as a deployable hardware-based processing unit beyond the von Neumann architecture. Its unique approach to consider only the output layer weights as adaptive, reduces training complexity and enables the use of ANNs in time-sensitive areas like optical communications. In this paper, we numerically investigate and evaluate the requirements of a photonic RC using an active silicon micro-ring resonator as a photonic integrated circuit (PIC) based reservoir system to compensate for transmission impairments such as chromatic dispersion and nonlinear effects occurring in optical transmission systems. We compare the performance of this RC with results from digital signal processing using Kramers-Kronig reception of distorted PAM-4 symbols from a 56 GBaud WDM transmission experiment over 100 km uncompensated SSMF.