Kostas Sozos

Kostas Sozos, Francesco Da Ros, Senior Member Optica et al.

High order modulation formats constitute the most prominent way for increasing spectral efficiency in transmission systems. Coherent transceivers that support such higher order formats require heavy digital signal processing (DSP), which increases the power consumption of coherent pluggables, well above the intensity modulation and direct detection (IM/DD) counterparts. Self-coherent or phase retrieval methods have emerged as potential solutions, trying to combine the merits of coherent technology with the simplicity of direct detection. In this work, we experimentally demonstrate the reception of quadrature amplitude modulation (QAM) modulation formats based on direct detection aided by the recurrent optical spectrum slicing (ROSS) photonic accelerator, utilizing minimal DSP and low modulator driving voltages. We experimentally demonstrate 32 Gbaud QAM-4/16 for 25 km, 50 km and 75 km in the C-band aided by a linear digital equalization and the use of programmable photonics as recurrent optical spectrum slicers. We showcase successful detection with driving swings below Vπ/3 in contrast to the full swing required by conventional coherent transceivers. We further improve the system performance utilizing geometric constellation shaping. Finally, we explore the potential power consumption improvement for the next-generation 1.6T pluggables, showcasing over 40% reduction with respect to the most lightweight state of the art coherent solutions reported in literature

Kostas Sozos, Stavros Deligiannidis, Charis Mesaritakis et al.

In this work we numerically analyze a photonic unconventional accelerator based on the four-wave mixing effect in highly nonlinear waveguides. The proposed scheme can act as a fully analogue system for nonlinear signal processing directly in the optical domain. By exploiting the rich Kerr-induced nonlinearities, multiple nonlinear transformations of an input signal can be generated and used for solving complex nonlinear tasks. We first evaluate the performance of our scheme in the Santa-Fe chaotic time-series prediction. The true power of this processor is revealed in the all-optical nonlinearity compensation in an optical communication scenario where we provide results superior to those offered by strong machine learning algorithms with reduced power consumption and computational complexity. Finally, we showcase how the FWM module can be used as a reconfigurable nonlinear activation module being capable of reproducing characteristic functions such as sigmoid or rectified linear unit.