Real-time optical spectrum monitoring in filterless optical metro networks

Abstract

Filterless optical networks (FON) have been proposed as a feasible solution for optical metro networks. In addition, as a result of the shorter distance compared to core optical networks, direct-detection optical transmission systems can be used in metro FONs, which reduces costs, as compared to coherent-detection systems. In this work, we present two optical signal tracking approaches for FONs that allow to detect small frequency laser drift problems and enable safely reducing channel spacing. Additionally, we study the most proper resolution for optical spectrum analyzers (OSA) continuously scanning the whole C-band. Proposed approaches are: i) feature-based tracking and ii) residual-based tracking. Experiments are carried out to compare the performance of the approaches for both direct-detection and coherent-detection systems, in the case of a single optical signal with no neighboring signals nearby in the spectrum, as well as in the case of a group of optical signals closely allocated in the spectrum. The results show that the residual-based approach enriched with contextual information enables to better track and correct the wavelength drifts before they reach their limits (e.g., ±2.5 GHz), leading to the guard band reduction for what concerns wavelength drifts.

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

“…[11], [12], [13], the results in the following sections are expressed in terms of a single value of channel spacing ∆f , thus assuming that the frequency spacing is the same between the channel under study and its two neighbors. Note that, if the neighboring channels are not equally spaced, the two values of channel spacing can still be estimated, for instance by complementing the ML algorithm results with spectral estimation methods, such as those described in [8], [9], able to identify the ratio between the linear ICI induced by the left and right channel, respectively.…”

“…Another approach consists in minimizing the impact of linear ICI by adapting the characteristics of the transmitted signal (modulation format, symbol rate, spectral shaping, etc.) to the conditions of the link by monitoring the frequency spacing among adjacent channels [8], [9], [10], a parameter that is strictly linked to the linear ICI. Machine learning (ML)-based methods have recently received considerable attention for linear ICI and channel spacing estimation.…”

Metropolitan Optical Networks: A Survey on New Architectures and Future Trends

“…The description of the necessary and sufficient infrastructure for the architectures in the metro-access segment, that is, the part of the metro with the shortest distances, such as those of type FL and, also SIMON and TDGMON, are only presented in their respective seminal papers, referenced in the Table XVI. For these ecosystems, some generic approaches to analyzing the optical signal [76] can be relevant both to improve transmission performance where there is no optical filter, identifying, for example, cases of signal overlap and as a metric for implementing path protection mechanisms. However, it is also necessary to deepen research in this field, in a more targeted way for each architecture individually.…”

“…Node C, of FL architecture [64], is built using a coupler, which only divides the signal into multiple outputs, consequently causing a reduction in power [76]. Both Node B and Node C have Drop and Waste (DnW) architectures [1].…”

Dantzig–Wolfe decomposition for the design of filterless optical networks

“…There is a compromise to be found between the usage of more spectrum efficient technologies thanks to, e.g., pure optical layer switching using expensive Reconfigurable Optical Add-Drop Multiplexers (ROADMs) (see, e.g., Simons [3]), and filterless optical networks which rely on cheap couplers/splitters at the expense of a reduction in the spectral efficiency performance [4].…”