Research Fields at ComLab

ComLab’s research encompasses a broad spectrum of digital communications, advanced signal processing, networking, and machine learning. Our current efforts are strategically focused on four pillars of innovation:

1. Machine Learning for Optical Transmission and Networking

Modern optical networks are increasingly complex, posing challenges that often surpass the capabilities of conventional analytical techniques. At ComLab, we leverage Machine Learning (ML) to address critical bottlenecks, including failure management, signal equalization, optical performance monitoring (OPM), Quality of Transmission (QoT) estimation, and predictive traffic modeling. By bridging the gap between data science and photonics, we partner with both industry and academia to build more resilient and autonomous networks.

2. Distributed Optical Fiber Sensing

We explore the dual-use of fiber-optic infrastructure, transforming telecommunication cables into high-resolution environmental sensors. Our research focuses on Distributed Acoustic Sensing (DAS). We develop advanced Digital Signal Processing (DSP) algorithms to detect anomalies and monitor critical infrastructure with high sensitivity.

3. Advanced Modulation and Signal Processing for SDM Systems

Space-Division Multiplexing (SDM) is the key technology to sustain the exponential growth of global data traffic. ComLab is a pioneer in the study of coupled-channel SDM systems using multi-core and multi-mode fibers. We develop tailored DSP suites and modulation formats designed to mitigate impairments in SDM media, particularly for inter- and intra-data-center interconnects.

4. Optical Satellite Communications

To meet the demands of global ubiquitous connectivity, we investigate the challenges of Free-Space Optical (FSO) communications for satellite-to-ground and inter-satellite links. Our research addresses the impact of atmospheric turbulence on optical signals and the development of robust modulation and coding schemes to ensure high-capacity, long-distance wireless optical transport in space-based networks.

A simulation tool for space-division multiplexing elastic optical networks

About Space-D

This software is a custom discrete event-driven simulator for Space-division Multiplexed Elastic Optical Networks (SDM-EON) with support to uncoupled channels that are represented by single-mode multi-core fibers as the links of the network.

The dynamics of the system is represented by the event chaining. The events are associated with the snapshot system actions that indicate state transitions and can trigger other events that will be executed in the future.

The events are connection requests to connect source-destination pairs of nodes in the network. The network is managed by the Control Plane, which checks if there are enough resources to accomodate all requirements before to install each connection request in the network.

This project was supported by CNPq and by FAPESP grant 2015/04382-0.

Click here to get the source-code (GitHub)