Future 6G X-haul networks must satisfy strict latency and service reliability requirements, placing significant pressure on metro-access transport architectures. As deployments become denser, longer and more heterogeneous routes intensify physical-layer impairments, making feasibility assurance and Quality-of-Transport (QoT) evaluation increasingly complex. To address these challenges, this work proposes an AI-driven converged metro-access Optical Network-as-a-Service (ONaaS) architecture based on coherent Point-to-Multipoint (P2MP) transmission using Digital Subcarrier Multiplexing (DSCM). An experimentally characterized transceiver impairment model is embedded into a network-level simulator to perform end-to-end feasibility analysis under strict latency and BER constraints. The results show that connectivity is primarily bounded by accumulated impairments, while Distributed Unit (DU) densification improves performance mainly by shortening path lengths, with limited benefit beyond moderate routing depth. To enable scalable operation, a lightweight machine-learning-based BER estimator is developed for rapid QoT prediction. Trained on a minimal deployment scenario, the Random Forest model generalizes across DU densities and topologies with R 2 > 0 . 98 , reducing evaluation time by several orders of magnitude. A techno-economic assessment further indicates up to 75% reduction in DU-site transceivers and 27%–30% energy savings compared to Point-to-Point (P2P) provisioning, demonstrating the efficiency and scalability of AI-enabled P2MP metro-access convergence for 6G.

In the imminent era of bandwidth-abundant optical networks, the concept of hierarchical optical network architectures emerges, decoupling the massive spatial division multiplexing (SDM) layer and the wavelength division multiplexing layer. In this paper, we perform a networking-level analysis of a generalized multiband optical cross-connect (OXC) that realizes switching in two steps: grouping wavelengths and switching them as waveband paths. The performed analysis is simulated for multiband and SDM systems, demonstrating that while conventional single-layer wavelength routing remains effective under certain conditions, waveband routing offers a more scalable and cost-effective solution under specific high-load conditions in bandwidth-abundant optical networks. This positions waveband routing as a promising alternative for future high-capacity networks.

In this paper, the authors exploit the OpenROADM standard model for the management and control of commercial ROADMs via an open optical SDN controller. Since each ROADM model has its own operating system, characterized by specific proprietary languages and interfaces, an additional middleware software layer must be introduced between the controller and the ROADM devices. This middleware aims to expose commercial devices through the OpenROADM model. Furthermore, the controller can send requests via the OpenROADM standard to the middleware.

Optical communications and networking are fast becoming the solution to support ever-increasing data traffic across all segments of the network, expanding from core/metro networks to 5G/6G front-hauling. Therefore, optical networks need to evolve towards an efficient exploitation of the infrastructure by overcoming the closed and aggregated paradigm, to enable apparatus sharing together with the slicing and separation of the optical data plane from the optical control. In addition to the advantages in terms of efficiency and cost reduction, this evolution will increase network reliability, also allowing for a fine trade-off between robustness and maximum capacity exploitation. In this work, an optical network architecture is presented based on the physical layer digital twin of the optical transport used within a multi-layer hierarchical control operated by an intent-based network operating system. An experimental proof of concept is performed on a three-node network including up to 1000 km optical transmission, open re-configurable optical add & drop multiplexers (ROADMs) and whitebox transponders hosting pluggable multirate transceivers. The proposed solution is based on GNPy as the optical physical layer digital twin and ONOS as intent-based network operating system. The reliability of the optical control decoupled by the data plane functioning is experimentally demonstrated exploiting GNPy as open lightpath computation engine and software optical amplifier models derived from the component characterization. Besides the lightpath deployment exploiting the modulation format evaluation given a generic traffic request, the architecture reliability is tested mimicking the use case of an automatic failure recovery from a fiber cut.

Nowadays, optical transport and data center networks utilize wavelength-division multiplexing (WDM) and band division multiplexing (BDM) as possible solutions to increase the capacity to support the ever-increasing traffic demand. It is an alternative solution to simple spatial division multiplexing (SDM) intended to utilize more than one fiber per link. In this perspective, we propose a new modular photonic integrated multi-band wavelength selective switch (WSS) to implement a novel reconfigurable optical add-drop multiplexer (ROADM) architecture. The proposed WSS can operate on a broad spectrum range, covering the three S+C+L bands, and is potentially scalable to large numbers of output fibers and routed channels while maintaining a small footprint. We investigated the network performance assessment of the ROADM architecture based on the proposed multi-band WSS on a German network, and a detailed comparison is given for both SDM and BDM solutions. Results show that the increase in network capacity by exploiting more bands in the cost-efficient BDM scenario is quite close to the SDM scenario using existing infrastructure replicated over multiple fibers.

In the evolution of optical networks, spectral efficiency (SE) enhancement has been the most cost-efficient and thus the main driver for capacity increase for decades. As a result, the development of optical transport systems has been focused on the$C$- and$L$-bands, where silica optical fiber exhibits the lowest attenuation, and erbium-doped fiber amplifiers provide an efficient solution to compensate for the optical loss. With a gradual maturity in the SE growth, however, the extension of the optical bandwidth beyond the$C + L$-band is expected to play a significant role in future capacity upgrades of optical networks and, thus, attract increasing research interests. In this article, we discuss the merits and challenges of ultrawideband optical transport systems and networks beyond conventional bands.

Modern elastic optical networking requires additional flexibility at each layer compared to the traditional approach. The application of the Software-defined Networking (SDN) paradigm can provide the required degrees of freedom. The implementation of optical SDN down to the physical layer requires the complete abstraction of network elements to support full control by the centralized controller. In this work, we propose a topological and technological agnostic model based on Machine Learning (ML) to abstract the behavior of optical switches for the computation of Quality-of-transmission (QoT) penalties and the definition of control states. Training and testing datasets are obtained synthetically by software simulation of the photonic switching structure. Results show the capability of the proposed method to predict QoT impairments with high accuracy, and we envision its application in a real-time control plane.

The massive deployment of 5G and beyond will require high capacity and low latency connectivity services, so network operators will have either to overprovision capacity in their transport networks or to upgrade the optical network controllers to make decisions nearly in real time; both solutions entail high capital and operational expenditures. A different approach could be to move the decision making toward the nodes and subsystems, so they can adapt dynamically the capacity to the actual needs and thus reduce operational costs in terms of energy consumption. To achieve this, several technological challenges need to be addressed. In this paper, we focus on the autonomous operation of Digital Subcarrier Multiplexing (DSCM) systems, which enable the transmission of multiple and independent subcarriers (SC). Herein, we present several solutions enabling the autonomous DSCM operation, including: i) SC quality of transmission estimation; ii) autonomous SC operation at the transmitter side and blind SC configuration recognition at the receiver side; and iii) intent-based capacity management implemented through Reinforcement Learning. We provide useful guidelines for the application of autonomous SC management supported by the extensive results presented.

Within a context of software-defined optical transport networks (SD-OTN), this work addresses specifically the management of Raman amplification, aiming to introduce and experimentally validate a system able to autonomously control this feature in-situ. In particular, given the required amplification constraints, an ad-hoc software module has been developed in order to optimize Raman pump power levels. Then, relying on this software, the architecture of an embedded controller to install on board the Raman card has been defined to handle Raman pumps. The use of a conceived probing procedure allows to self-adapt each Raman amplifier to the installed fiber, allowing it to autonomously operate at the working point required by the control plane. Relying on the system telemetry, the proposed architecture controls the Raman pumps in order to achieve the required amplification constraints in terms of average gain and tilt. The entire proposal is validated through a set of experimental measurements that proofs both the achievement of the required gain target and the importance of the probing phase procedure in making the Raman amplifier autonomous and self-adaptable.

Both spatial-division multiplexing (SDM) and band-division multiplexing (BDM) emerge as possible solutions to increase the optical network capacity to support the traffic demand which has been rising over time. In this work, two different ROADM (Re-configurable Optical Add Drop Multiplexer) switching techniques, namely SDM-InS (Independent switching) and SDM-CCC (Core Continue Constant) are investigated and the resulting network capacity is compared with the BDM approach. In the BDM case, both L- and S-bands have been used in addition to C-band to increase the network capacity. The launch power is optimized to control the QoT (Quality of Transmission) summarized by the generalized SNR (GSNR) per channel. Due to: stimulated Raman scattering, frequency variation of loss, frequency variation of dispersion coefficient and noise figures, an optimum power tilt and offset are calculated for each band. We show that the total network capacity increased by $\sim 2 \times$ and $\sim 3 \times$, when using the L-band and L+S-bands in addition to the C-band, respectively, in both a reference German and a reference US network. Additionally, it was also shown that using additional bands, the increase in network capacity is close to the result of using additional optical fibers in the SDM case.

GNPy is an open source project of the Telecom Infra Project (TIP). It aims at the development of a software library for the abstraction of physical layer data transport, implemented as wavelength division multiplexing (WDM) through open-source code and open APIs, with the purpose of automatizing disaggregated, multi-vendor open optical networks. We first introduce the GNPy library of applications and functionalities, then, we present validation of the GNPy core. The quality-of-transmission estimator (QoT-E) enables a quick and accurate prediction of the unique performance metric in WDM data transport of optical networks: the Generalized Signal-to-Noise Ratio (GSNR). The presented validation experiments show an excellent accuracy in predicting the GSNR compared to the values obtained experimentally. Finally, we present the GNPy integration with the ONOS network OS in a multi-vendor scenario including open reconfigurable add drop multiplexers (ROADMs) and the related validation experiment.

Prior provisioning of optical source technologies have techno-economic importance for the operator during the design and planning of optical network architectonics. Advancement towards the latest technology paradigm such as Elastic Optical Networks (EONs) and Software Defined Networking (SDN) open a gateway for a flexible and re-configurable optical network architecture. In order to achieve the required degree of flexibility, a flexible and dynamic behaviour is required both at the control and data plane. In this regards, SDN-enabled flexible optical transceivers are proposed to provide the required degree of flexibility. Sliceable Bandwidth Variable Transponders (SBVTs) is one of the recent type of flexible optical transceivers. Based on the type/technology of optical carrier source, the SBVTs are categorized into two types; Multi-Laser SBVT (ML-SBVT) and Multi-wavelength SBVT (MW-SBVT). Both architectures have their own pros and cons when it comes to accommodate traffic request. In this paper, we propose a selection model for the SBVTs before its actual deployment in the network. The selection model consider various design and planning phase network characteristics. In addition to this selection model, the comparison of centralized Flex-OCSM architecture is also presented with the already discussed SBVT types. The analysis in this work is performed on random network (20 nodes) and the German Network (17 nodes).

Flexible-grid optical networks are the most convincing candidate for the evolution of backbone optical networks thanks to their high spectral efficiency and flexibility. We propose an original approach to the logical topology design (LTD) problem in the offline planning phase. We deal with the LTD problem using heuristic algorithms incorporating a detailed transmission layer model. Several heuristic algorithms, allocating traffic demands in different orderings, are considered for lightpath provisioning. Traffic ordering schemes are mainly based on two parameters: traffic demands capacity and lightpath physical route length. Through simulative analyses, we provide a performance comparison of different heuristics, using parameters like spectral efficiency, amount of blocked traffic and total number of transceivers. We also show the importance of integrating a detailed physical layer modeling in the network design phase.

We present in this paper a novel accurate method to analyze the performance of an optical link where the amplified spontaneous emission noise, enhanced by a fiber nonlinear phenomenon called parametric gain, is the limiting factor. Our method allows us to compute the exact error probability given a generic noise spectral density at the input of a direct detection optical receiver, using arbitrary optical and electrical filters. We compare our results with those predicted using the standard Gaussian technique (based on the Q factor), showing that this approximation may lead to significant errors. Our method is then used to evaluate the impact of parametric gain on a realistic long-haul multiwavelength link operating at 10 Gb/s, showing both the system limitation imposed by this phenomenon and the inaccuracy of the Q factor method.

A novel method to evaluate the bit error rate (BER) in optical links is described. It analyzes systems limited by amplified spontaneous emission (ASE) noise, enhanced by the non-linear parametric gain (PG) effect, and allows one to compute the exact error probability, given a generic optical noise spectral density at the input of a direct detection optical receiver. The method has been employed to evaluate the impact of PG on a 10 Gb/s per channel long-haul multi-wavelength system. It has also been used to show how the system performance evaluation based on the Q-factor Gaussian approximation may lead to erroneous BER evaluations.

We study the effect of parametric gain in long-haul, optically amplified links. We started by introducing a formalism required to evaluate the spectral enhancement of amplified spontaneous emission noise due to the Kerr-effect non-linear interaction between the signal and noise. These results are then used to evaluate parametric gain-induced performance degradation on the system Q value. Finally we analyze long-haul links at 10 Gb/s using different dispersion compensation maps by evaluating the maximum reachable distance in each configuration. We show that less frequent dispersion compensation improves the system performance.

The fast-paced evolution of long-haul and high-bit-rate terrestrial and submarine optical transmission links requires powerful analysis tools that take into account all the relevant phenomena in the fiber. To provide such a tool, we developed a time-domain optical system simulation package, integrated in the TOPSIM simulation environment. The fiber simulation module makes use of the vector form of the propagation equations to account for the quasi-degenerate two-mode (the two polarizations) medium propagation characteristics. This way, all polarization-related effects and their interplay with the other linear and nonlinear phenomena in the fiber can be accurately modeled. In particular, the fiber third-order susceptivity, responsible for all major nonlinear effects, is expressed in its actual vector form, so that nonlinear polarization mode coupling could be accounted for. Conventional birefringence and PMD are generated using appropriate random models. A novel feature of the simulator is that it uses time-domain digital filters to simulate dispersion effects, as opposed to the usual FFT-based algorithms. This approach leads to more efficient computing for a wide range of bandwidth and dispersion values. We present the fiber simulation module in detail. As an example of the use of the simulation package, the analysis of a long-haul two-channel transoceanic WDM transmission system is presented.