The utilization of hybrid Erbium-doped fiber (EDF)/Raman amplifiers enables to extend the reach of optical channels and, consequently, reduce the number of expensive 3R regenerators required in long-haul optical networks. However, hybrid amplifiers are costlier than the widely deployed EDF amplifiers (EDFAs). Therefore, it is critical to place them only at selected fiber spans of the network such that their number is also kept to a minimum. Hybrid amplifier placement is a complex task in mesh networks due to the diverse optical channels (i.e., with different source and destination nodes) traversing each fiber span. This paper proposes an optimal method to solve the problem of placing hybrid amplifiers in mesh networks. It builds on the approximation that noise adds up incoherently along the transmission path to derive an integer linear programming (ILP) model that determines the minimum number and location of hybrid EDF/Raman amplifiers required to reach a target set of feasible optical channels (i.e., without intermediate 3R regenerators). A comprehensive set of network simulations using a reference optical network provides evidence that the proposed method outperforms existing approaches.

This paper proposes an Integer Linear Programming (ILP) framework to optimize the multi-period planning of metro-aggregation networks exploiting both point-to-multipoint coherent pluggable transceivers and a filterless line system architecture. We investigate several planning strategies to minimize cost while also considering traffic prediction and operational expenditures. The results of a reference network provide evidence of transceiver cost reductions between 20% and 32% compared to the point-to-point approach over a five-year planning period.

Emerging applications are driving traffic requirements to new heights, from IoT and autonomous driving to augmented reality and Industry 4.0. Urban areas, which have a significant fraction of the telecom infrastructure capital expenditures (CAPEX), are experiencing even more growth than other segments. Noteworthy, the traffic pattern in aggregation networks is hub-and-leaf, with only a few hub nodes communicating with multiple leaf nodes. Traditional point-to-point optical solutions are not the best fit for this pattern. A novel optical technology enabling point-to-multipoint operation has recently been proposed to address this limitation. Since this solution relies on broadcasting the optical signal over a virtual tree, its optimal deployment in generic fiber topologies (with failure survivability conditions) requires specific designs. This paper describes an integer linear programming model to optimize the design of survivable metro-aggregation networks exploiting point-to-multipoint coherent transceivers. Results obtained on a mesh network show evidence that transceiver expenditures can be reduced by a figure between 25% and 60%.

The ever-increasing traffic requirements need cost-efficient and reliable solutions. Metropolitan networks are responsible for a large fraction of the telecom infrastructure CAPEX. Albeit the traffic pattern in these networks tends to be hub-and-spoke, the current transceiver deployments do not leverage this feature. This paper describes and models various survivable metro-aggregation network scenarios using point-to-multipoint capable coherent transceivers. The results obtained over a reference mesh network show that these transceivers can reduce total transceiver costs by ~40% on average.

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.

In clinical practice and in particular in the diagnostic process, the assessment of cardiac and respiratory functions is supported by electrocardiogram and auscultation. These exams are non-invasive, quick and inexpensive to perform and easy to interpret. For these reasons, this type of assessment is a constant in the daily life of a clinician and the information obtained is central to the decision making process. Therefore, it is essential that during their training, students of health-related subjects acquire skills in the acquisition and evaluation of the referred physiological signals. Simulation, considering the technological possibilities of today, is an excellent preparation tool since it exposes trainees to near real contexts but without the associated risks. Hence, the simulation of physiological signals plays an important role in the education of healthcare professionals, bioengineering professionals and also in the development and calibration of medical devices. This paper describes a project to develop synchronized electrocardiogram (ECG), phonocardiogram (PCG) and breathing sounds simulators that aims to improve an existing phantom simulator. The developed system allows, in an integrated way, to generate normal and pathological signals, being contemplated several distinct pathologies. For engineering education, it is also possible to simulate the introduction of signal disturbances or hardware malfunctions. A graphical interface allows changing operating parameters in real time.

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.

Narrowband multiple-input-multiple-output (MIMO) measurements using 16 transmitters and 16 receivers at 2.11 GHz were carried out in Manhattan. High capacities were found for full, as well as smaller array configurations, all within 80% of the fully scattering channel capacity. Correlation model parameters are derived from data. Spatial MIMO channel capacity statistics are found to be well represented by the separate transmitter and receiver correlation matrices, with a median relative error in capacity of 3%, in contrast with the 18% median relative error observed by assuming the antennas to be uncorrelated. A reduced parameter model, consisting of 4 parameters, has been developed to statistically represent the channel correlation matrices. These correlation matrices are, in turn, used to generate H matrices with capacities that are consistent within a few percent of those measured in New York. The spatial channel model reported allows simulations of H matrices for arbitrary antenna configurations. These channel matrices may be used to test receiver algorithms in system performance studies. These results may also be used for antenna array design, as the decay of mobile antenna correlation with antenna separation has been reported here. An important finding for the base transmitter array was that the antennas were largely uncorrelated even at antenna separations as small as two wavelengths.

Narrowband MIMO measurements using 16 transmitters and 16 receivers at 2.11 GHz were carried out in Manhattan. High capacities were found for full as well as smaller array configurations, all within 80% of the fully scattering channel capacity. It was found that two streets which might be considered near LOS, had different capacities, one about 45% of and the other about 75% of the fully scattering channel capacity.