Adaptive Bitrate (ABR) Algorithms for Six Degree-of-freedom Virtual Reality Streaming


Applications will be considered as they arrive and all applications should arrive no later than 15 Oct 2021.

This project is part of a 4 year Dual PhD degree programme between the National Tsing Hua University (NTHU) in Taiwan and the University of Liverpool in England. As Part of the NTHU-UoL Dual PhD Award students are in the unique position of being able to gain 2 PhD awards at the end of their degree from two internationally recognised world leading Universities. As well as benefiting from a rich cultural experience, Students can draw on large scale national facilities of both countries and create a worldwide network of contacts across 2 continents.

This project plans to develop optimal and approximation algorithms for bitrate adaptation and packet scheduling in 6 Degree-of-Freedom Virtual Reality streaming systems, in order to maximize the user experience.

Virtual Reality (VR) technologies have gained immense popularity, as indicated by the number of Head-Mounted Displays (HMDs) and VR applications hitting the market. Conventional VR only supports 3 Degrees-of-Freedom (3-DoF), which enables 360-degree viewing orientations using 360-degree videos. However, users can just rotate their heads to see different orientations but cannot move or walk within VR environments. 6 Degree-of-Freedom (6-DoF) was proposed to allow users to change their positions freely. To enable 6-DoF VR, various 3D data representations, e.g., point cloud, mesh, multi-view videos, and light field, are needed to describe 3D scenes. These representations have tremendous data size and are hard to be transmitted in real-time by the current network. To solve this problem, we plan to develop novel Adaptive Bitrate (ABR) algorithms to dynamically adjust the bitrate of 6-DoF streaming according to available bandwidth. To the best of our knowledge, ABR algorithms for 6-DoF VR streaming have not been investigated until very recently. For example, Van der Hooft et al. [1] proposed a streaming system for point clouds consisting of multiple objects. They designed several heuristic ABR algorithms to adjust bitrate according to the user's states and network conditions. Qian et al. [2] proposed a volumetric streaming system for commodity mobile devices, which leveraged edge computing and rate adaptation to adapt bandwidth and reduce motion-to-photon delay dynamically. These two, and other similar studies only adopted heuristic ABR algorithms with little, if any, performance guarantees. This project aims to develop a general ABR algorithm framework suitable for heterogeneous 3D data representations used in 6-DoF VR streaming.

For academic enquires please contact Prof Prudence Wong  & Associate Prof Cheng-Hsin Hsu 

For enquires on the application process or to find out more about the Dual programme please contact 

To apply please visit: When applying please ensure you Quote the supervisor & project title you wish to apply for and note ‘NTHU-UoL Dual Scholarship’ when asked for details of how plan to finance your studies.


Open to students worldwide

Funding information

Funded studentship

It is planned that students will spend 1.5 years at NTHU, followed by 1 year at the University of Liverpool before returning to NTHU for the remaining 1.5 years.
Both the University of Liverpool and NTHU have agreed to waive the tuition fees for the duration of the project and stipend of TWD 11,000/month will be provided as a contribution to living costs (the equivalent of £280 per month when in Liverpool).



[1] Jeroen van der Hooft, Tim Wauters, Filip De Turck, Christian Timmerer, and Hermann Hellwagner, "Towards 6DoF HTTP adaptive streaming through point cloud compression." in Proc. of the ACM International Conference on Multimedia (MM’19). October 2019.
[2] Feng Qian, Bo Han, Jarrell Pair, and Vijay Gopalakrishnan, "Toward practical volumetric video streaming on commodity smartphones." In Proc. of the ACM International Workshop on Mobile Computing Systems and Applications (HotMobile’19). February 2019.