End-to-end deep learning of geometric shaping for unamplified coherent systems.

With the increasing data rate requirements on short-reach links, the recent standardization of unamplified coherent optical systems is paving the way for a cost and power-effective solution, targeting a massive deployment in the near future. However, unamplified systems are introducing new challenges. Particularly, the performance is highly dependent on the peak-to-average power ratio (PAPR) of the transmitted signal, which puts at question the use of the typical constellation formats. In this work, we use an end-to-end deep learning framework to optimize the geometry of different constellation sizes, ranging from 8- to 128-ary constellations. In general, it is shown that the performance of these systems is maximized with constellations whose outer symbols are disposed in a square shape, owing to the minimization of the real-valued PAPR. Following this premise, we experimentally demonstrate that odd-bit constellations can be significantly optimized for unamplified coherent links, achieving power budget gains in the range of 0.5-3 dB through the geometric optimization of 8-, 32- and 128-ary constellations.

Enhanced resilience towards ROADM-induced optical filtering using subcarrier multiplexing and optimized bit and power loading.

In flexible optical networks, lightpaths are routed from source to destination thanks to reconfigurable optical add-drop multiplexers (ROADMs) placed in every node connected by a line system. As ROADMs are based on wavelength selective switches (WSSs), which imply channel filtering, a non negligible performance reduction can be observed when lightpaths traverse many network nodes. Control plane software network controllers that base their decision on the quality of transmission of the physical layer must also take into account the impact of ROADMs cascading. The penalties caused by WSS cascading in single-carrier systems are mostly driven by uncompensated inter-symbol interference (ISI), and therefore their evaluation cannot be based on simple analytical solutions as required for real-time network control. In this paper, we consider a 200G optical system based on multi-subcarrier (MSC) modulation with hybrid modulation formats. Using a fully analytical framework, we show that it is possible to predict ROADM-induced penalties offline and accurately estimate the required settings for their transmitter-side mitigation through bit and/or power-loading. Moreover, resorting to both simulations and experiments, we also demonstrate that properly optimized MSC signals can provide an increased resilience to ROADM filtering with respect to standard single-carrier systems: applying analytically-driven bit-loading over 8×4 Gbaud and 16×2 Gbaud MSC signals after crossing 8 cascaded WSSs in a noise loading scenario, we experimentally found ∼2 dB gain in required SNR with respect to a traditional 32 Gbaud single-carrier signal.