Apr 4

CS Tea: Eman Ramadan presents "Measuring, Mapping, and Predicting Commercial 5G Performance and its Impact on Applications"

Thu, April 4, 2024 • 3:30pm - 4:30pm (1h) • Anderson 329

Eman Ramadan is a Lecturer and Research Associate in the Computer Science and Engineering Department (CS&E) at the University of Minnesota - Twin Cities, working with Prof. Zhi-Li Zhang. Her research interests lie broadly in 5G/xG Mobile Networking, Content Distribution Networks (CDN), Resilient Routing, and Software Defined Networks (SDN). Primarily focusing on understanding and improving the performance of emerging 5G Networks to be more scalable and reliable, using cross-layer design and machine learning to support emerging applications with ultra-high bandwidth and low latency requirements, such as volumetric video streaming and autonomous vehicles. Eman has been a co-lead for the first 5G commercial measurements publications since 2019, which are highly cited worldwide.  Eman has earned her PhD in Computer Science in 2022. Eman is the chair of the Inclusivity, Diversity, Equity, and Advocacy Committee CS-IDEA at the CS&E Dept, a lead member of the Diversity & Inclusivity Alliance, and a member of the Inclusivity Council for strategic planning at the College of Science and Engineering.

Abstract:  In 2019, the advent of Commercial 5G brought forth a myriad of promises, including ultra-high bandwidth and low latency, poised to usher in a new era of applications such as AR/VR, Ultra high-definition video streaming, Autonomous Vehicles, and Smart Cities. First, I will start with an overview of 5G characteristics and deployment strategies. After, I will delve into our extensive 5G measurement campaigns spanning the past five years, with a particular focus on our seminal paper detailing the initial commercial 5G measurements. I will share findings from measurements across three major carriers (Verizon, T-Mobile, and Sprint), including a comparison with 4G performance and an exploration of key factors influencing 5G performance.

Following this, I will present how we were able to use machine learning (ML) to predict 5G throughput, addressing the inherent variability caused by numerous factors. Furthermore, I will provide insights into how ML techniques are leveraged to enhance the performance of 5G applications and tackle the associated challenges. Additionally, I will discuss our research into 5G autonomous vehicles, shedding light on the current obstacles impeding the realization of this technology's potential.

Finally, I will share findings from our recent study on 5G roaming in Europe, which will offer users actionable information to optimize their performance abroad.

Join us for treats, tea and community!

Event Contact: Marla Erickson

Event Summary

CS Tea: Eman Ramadan presents "Measuring, Mapping, and Predicting Commercial 5G Performance and its Impact on Applications"
  • Intended For: Students, Faculty, Staff
  • Categories: Lecture/Panel, food offered

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