Ericsson Master thesis: Supporting mobile VR services in 5G networks in Stockholm, Sweden


Eye tracking sensors have been successfully adopted, over the years, in several areas of application including medical, marketing and as novel Human-Machine Interfaces (HMIs). Recent technological developments have led to novel embodiments of eye-tracking sensors designed to capture users’ eye-gaze information for wearable Head Mounted Displays (HMDs), such as Virtual Reality (VR) or Augmented Reality (AR) headsets and glasses, opening up new consumer-oriented areas of applications. The eye-gaze information captured by an eye-tracker can be used to estimate the portion of the user screen which is mapped onto the viewer’s fovea, thus allowing to perform a spatial optimization of the visual information on the screen of an HMD, assigning higher image resolution to the pixel areas estimated being within the user’s fovea and lower quality to those contributing to the peripheral vision. Initial research activities within the SEEN project have focused on defining a novel codec, supporting fast video quality transitions, and a cloud architecture for storing and processing eye-gaze information and for supporting intelligent switching among different video quality levels in function of the end-to-end achievable communication bitrates and RTTs and targeted end-user experience levels.

This Master Thesis will focus on the definition of a Dynamic Orchestration (DO) approach for enabling the provision of 360 video streaming services to mobile users, including:

  • defining SLA functions that are specific for foveated content provision and tactile services in general
  • implementing cloud-based solutions (DO) optimizing quality levels in the frame’s foreground and background regions to achieve intended user experience levels,
  • evaluating achievable performances in a real 5G testbed and assessment with real users.

The goal of this Thesis is to define and experimentally validate algorithms and schemes implementing a cloud-based solution for foveated streaming for VR. This thesis work is directly contributing to the Vinnova funded SEEN project and some of the development and testing will be performed using state-of-the-art software and hardware from the project partners.

We are looking for a motivated MSc student who has fulfilled the course requirements for the degree project. Excellent knowledge of C# and Python programming is required, as well as a good understanding of cloud deployment, streaming protocols and content delivery mechanisms. In addition, we require good spoken and written English.


Applications should include a brief personal statement, CV, and a list of grades. In the application, make sure to mention previous activities or other projects that you consider relevant for the position. Candidates are encouraged to send in their application to the contact below as soon as possible. Suitable applicants will be interviewed as applications are received.

SEEN project

The SEEN project aim at creating a novel content delivery mechanism that optimizes information display based on real-time information from connected eye-trackers, with applications including VR, AR and tactile Internet. The Thesis will be run in cooperation with the project’s partners: Ericsson, KTH, and Tobii.


For more information, please contact Calin Curescu at Ericsson or Pietro Lungaro at KTH.

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Primary country and city: Sweden (SE) || No Selection || Stockholm || Stud&YP;

Req ID: 211441