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Sanwal Zeb

Sanwal Zeb's picture

Research Assistant
Department of Electronics and Telecommunications (DET)

Ph.D. candidate in Ingegneria Elettrica, Elettronica E Delle Comunicazioni , 40th cycle (2024-2027)
Department of Electronics and Telecommunications (DET)

Profile

PhD

Research topic

Digital twin of physical layer for short-reach scenarios in metro/access/DCI networks

Tutors

Keywords

Big Data, Machine Learning, Neural Networks and Data Science
Communication and Computer Networks
Optical and Wireless Digital Transmissions Systems

Biography

Brief overview of research project and major accomplishments expected
Optical networks form the backbone of the global communication infrastructure, connecting billions of people alongside countless autonomous devices, control systems, and machines. In Computer Networks, physical layer consists of set of components i.e. Network Elements (NEs) that enables end to end communication between sender and the recipient. A digital twin of a physical layer refers to a virtual replica of a physical system or process, used to simulate, analyze, and optimize the system's performance in real-time. The digital twin mirrors this physical system through data collection, sensors, and advanced modeling, and it can be used for various purposes, such as Monitoring, Simulation, Optimization and Maintenance. Also, we can optimize networks key features such as system cost, latency, dynamic reconfigurability, and energy efficiency are becoming increasingly critical for the next generation of access and metro networks.

Research Objectives
  • 1. Quality of transmission (QoT) modelling for multiband short-reach scenarios in optical networks.
  • 2. Trained ML models to reduce network impairments and enhance QoS
  • 3. Modelling of SDON enabled digital twin of physical layer in metro/access/DCI networks

Key Deliverable
  • 1. Validation of a physical -layer digital twin model for links in metro/access networks
  • 2. ML-based failure detection and recovery in networks with high dynamic traffic
  • 3. AI-assisted optical control of disaggregated networks
  • 4. AI-based environmental surveillance and control methods from optical network telemetry

Curriculum

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Publications

Latest publications View all publications in Porto@Iris