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Faculty of Graduate Studies

Ali Ahangarpour

  • BSc (Isfahan University of Technology, 2023)

Notice of the Final Oral Examination for the Degree of Master of Science

Topic

Identifying and Analyzing Available and Serving Satellites for Starlink, with a Comparative Analysis of OneWeb

Department of Computer Science

Date & location

  • Friday, December 5, 2025

  • 1:00 P.M.

  • Engineering Computer Science Building

  • Room 467

Reviewers

Supervisory Committee

  • Dr. Jianping Pan, Department of Computer Science, University of Victoria (Supervisor)

  • Dr. Alex Thomo, Department of Computer Science, UVic (Member) 

External Examiner

  • Dr. Levi Smith, Department of Electrical and Computer Engineering, University of Victoria 

Chair of Oral Examination

  • Prof. Malcolm Gaston, School of Public Administration, UVic 

Abstract

Low-Earth-orbit (LEO) satellite networks (LSNs) have emerged as a transformative architecture for broadband Internet, reducing propagation delay compared to traditional geostationary equatorial orbit (GEO) and medium-Earth-orbit (MEO) systems. However, their low altitude necessitates frequent handovers, complex satellite selection strategies, and dense ground infrastructure. Understanding which satellite serves a user terminal (UT) at a given moment is therefore fundamental for characterizing performance and reconciling measurement studies. While early Starlink UT firmware directly exposed serving satellite identifiers, such telemetry has since been removed, leaving the serving satellite opaque to both users and researchers. OneWeb, by contrast, provides serving satellite identifiers through certain Antenna Interface Modules (AIMs), but systematic analysis remains scarce.

This thesis presents a novel methodology for identifying the available and serving satellites for Starlink, which combines UT telemetry with orbital geometry. We introduce a serving satellite inference pipeline that integrates obstruction map snapshots, UT orientation, and public two-line element (TLE) ephemerides. The pipeline converts obstruction map pixels to topocentric coordinates, applies a tilt-aware elliptical field-of-view (FOV) model, and selects the serving satellite by minimizing angular separation. To provide a comparison for Starlink, we reconstruct OneWeb’s serving-satellite sequences and assess its satellite availability using AIM tracking logs.

Utilizing these methods, we compile a cross-constellation dataset of serving and available satellites, covering UTs across multiple continents. Our analysis reveals the policies shaping satellite selection and handovers, and quantifies their impact on the overall network performance.

Overall, this work presents the first UT-focused, measurement-driven characterization of serving satellite identification for Starlink. It also provides the first analysis of serving satellite selection strategy and its impact on network performance in both Starlink and OneWeb systems, closing a key gap in LSN research. The results offer new insights into constellation behavior and the interplay between satellite mobility and user experience.

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