Analysis and experiments on C band 200G coherent PON based on Alamouti polarization-insensitive receivers

Passive optical network (PON) based on coherent detection has attracted a great deal of attention in recent years as a future solution for 100+ Gbps per wavelength. Particularly for 200G-PON, one of the most attractive options would be to switch to QAM transmission and coherent detection, due to its well know advantages compared to the Direct-Detection approaches used so far in PON. However, coherent technology, extensively used in core networks, has costs that are still perceived as too high for the access ecosystem. In order to perform cost reduction, some groups have studied the option of coherent polarization-independent (PI) detection, since it halves the number of optoelectronic components in the receiver front end. In this paper, we thus present a detailed simulative and experimental investigation of polarization-independent receivers to achieve 200 Gbps transmission in C band using the Alamouti polarization time block coding (PTBC). Our goal is to show what would be the system requirements in terms of optoelectronic bandwidths, laser phase noise and ultimate power budget limitations. We study two different modulation formats: quadrature phase-shift keying (QPSK) and 16 quadrature amplitude modulation (16QAM). We also compare heterodyne and homodyne/intradyne solutions through simulations. As a summarizing result, we experimentally show that 200G PON based on 50 Gbaud-16QAM single-polarization Alamouti coded signals would be possible with today state-of-the-art coherent technologies, demonstrating an Optical Distribution Network loss above 33 dB with 25 km fiber length, a very promising result that is compliant with the PON power budget E1 class

Experimental Demonstration of Linear Inter-Channel Interference Estimation Based on Neural Networks

In this paper, an algorithm for the estimation of the linear inter-channel crosstalk in a dense-WDM polarization-multiplexed 16-QAM transmission scenario is proposed and demonstrated. The algorithm is based on the use of a feed-forward neural network (FFNN) inside the coherent digital receiver. Two types of FFNNs were considered, the first based on a regression algorithm and the second based on a classification algorithm. Both FFNN algorithms are applied to features extracted from the histograms of the in-phase and quadrature components of the equalized digital samples. After a simulative investigation, the performance of the channel spacing estimation algorithms was experimentally validated in a 3 × 52 Gbaud 16-QAM WDM system scenario