Complexity and size of modern optic-fiber networks start to challenge the traditional methods of managing them and yet majority of telecommunication companies still report rapid growth of their optical networks. One of essential problems in managing optic-fiber networks is calculating the Quality of Transmission (QoT) of given path in network. The unit responsible for this task is Optical Performance Unit (OPU) which communicates with Network Management System (NMS). OPU's task is to determine whether it is possible to transmit signal through a given path. Modern OPUs are still operating based on traditional algorithms e.g. these systems take into consideration known physics rules and information about the network parameters, calculating transmission losses for each path. Main parameter that determines the OPUs result is Optical Signal to Noise Ratio (OSNR). However, measuring its value from NMS level is often not practical. An alternative solution to this problem might prove the application of Machine Learning (ML) algorithms for the estimation of OSNR. In this contribution an application of Artificial Neural Network (ANN) to an evaluation of OSNR in an optical Dense Wavelength Division Multiplexing (DWDM) network is investigated.
The paper shows initial experimental results of research works taken by teams of the Institute of Electronic Materials Technology and Military University of Technology aimed at manufacturing in Poland photoconductive semiconductor switches (PCSSs) on semi-insulating (SI) gallium phosphide (GaP) wafers. These devices will allow pulsed switching of power circuits to high-voltage networks as well as triggering the high-energy of electromagnetic radiation. The properties and concentrations of deep-level defects, contributing to the charge compensation enabling the SI GaP crystals to be obtained, have been studied by the high-resolution photoinduced transient spectroscopy (HRPITS). The chips of switches with two planar electrodes separated by a gap of 2 mm were made and the connections enabling the dark current and photocurrent measurements as a function of the electric field strength to be carried out were assembled. The ways of increasing the switch amperage in the conductive state are discussed.
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