University of Twente Student Theses


Efficient and Reliable Delivery of VR over 5G Mobile Networks

Evci, H. T. (2020) Efficient and Reliable Delivery of VR over 5G Mobile Networks.

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Abstract:With the introduction of 5G, wireless VR has found a place on the agenda of the VR industry. High data rates and low latency offered by 5G technologies such as mmWave and enhanced mobile edge computing (MEC) provides the opportunity to make a switch from wired to wireless VR. This research focuses on the effcient and reliable delivery of non-interactive VR over 5G mobile networks. The trade-off between efficiency and reliability is the main concern of this research. The FoV transmission scheme makes it possible to deliver VR over mobile networks but requires FoV prediction. Channel prediction can also be a useful tool, as it can provide information about when to transmit the FoVs. These two prediction algo- rithms can be computed in the MEC, so the latency will be minimal. The effect of the MEC and these two predictions on the trade-off between efficiency and reliability is investigated in this thesis. Three main delivery strategies, which doesn't include channel prediction, were designed and tested in a Python simulation environment that was built from scratch, namely the reactive, proactive and combined strategies. Four different simulation scenarios were used to test these strategies, namely different users, different video datasets, different channel qualities and different probability thresholds. Later on the research, two enhanced delivery strategies with channel prediction were created to see the effect on the trade-off. From the experiments, it is concluded that the combined strategy with a low thresh- old was the best in terms of the trade-off in reliability and efficiency. One of the en- hanced delivery strategies with channel prediction resulted in better reliability with little cost in efficiency. To sum up, it is convincing that the MEC and the algorithms computed in the MEC, FoV prediction and channel prediction, helps us to find the optimal trade-off between reliability and efficiency.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:53 electrotechnology
Programme:Electrical Engineering MSc (60353)
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