Defence of doctoral thesis in the field of Networking Technology, M.Sc. Ermias Walelgne
M.Sc. Ermias Walelgne will defend the thesis "Performance and Usage Patterns of Mobile Networks" on 19 November 2021 at 12 in Aalto University School of Electrical Engineering, Department of Communications and Networking, in lecture hall AS1, Maarintie 8, Espoo.
Opponent: Prof. Tommi Mikkonen, University of Helsinki, Finland
Custos: Prof. Jukka Manner, Aalto University School of Electrical Engineering, Department of Communications and Networking
Thesis available for public display at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/
Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53
These days accessing the Internet using mobile networks has become part of our daily life. Since the introduction of mobile networks, there has been an overwhelming growth in users, traffic demands, and the need to access various services over mobile devices.
Mobile networks involve large parameter spaces, including user mobility, geographical location, operator network, radio technology type and usage patterns, and user quality of experience. As a result, there is a need to understand and characterize the performance of mobile networks. Understanding the performance of mobile networks is not only important for the general public and society as a whole but also for network operators, as they need to identify bottlenecks and issues that limit the achievable performance from the user's point of view.
This thesis contributes to the evolving mobile network quality by focusing on two essential aspects: how users actually use mobile networks and what performance they experience. This thesis mainly used large data sets from crowd-sourced measurement platforms such as Netradar and test-bed-based measurements. Such data sets span many operators, users, geographical regions and contain many measurements points. A data-driven analysis and machine learning methods have been applied to build models that draw novel conclusions to answer the research questions. The study looks into mobile network performance from users' perspective to identify factors affecting the performance of mobile networks by considering network throughput, latency, location and time of a day, and radio technology types. It includes a study and analysis of mobile users' data usage patterns across different countries and a clustering model based on data usage patterns.
Furthermore, the thesis also conducted a measurement-based study on the feasibility of teleoperated driving in the existing mobile networks. As the 5G is becoming the next available technology with very low latency and high throughput, a data-driven study and results on network throughput, users' data usage patterns, and the usefulness of existing networks for different uses cases are at most important.
Contact information of doctoral candidate: