The delivery of three-dimensional immersive media to individual users remains a highly challenging problem due to the large amount of data involved, diverse network characteristics, and user terminal requirements, as well as user’s context. This paper proposes a framework for quality of experience-aware delivering of three-dimensional video across heterogeneous wireless networks. The proposed architecture combines a Media-Aware Proxy (application layer filter), an enhanced version of IEEE 802.21 protocol for monitoring key performance parameters from different entities and multiple layers, and a QoE controller with a machine learning-based decision engine, capable of modelling the perceived video quality. The proposed architecture is fully integrated with the Long Term Evolution Enhanced Packet Core networks. The paper investigates machine learning-based techniques for producing an objective QoE model based on parameters from the physical, the data link, and the network layers. Extensive test-bed experiments and statistical analysis indicate that the proposed framework is capable of modelling accurately the impact of network impairments to the perceptual quality of three-dimensional video user.
Evaluating Psychoacoustic Parameters and Quality of Transmitted Speech Over Wireless Networks