Fuzzy logic inference system-based hybrid quality prediction model for wireless 4kUHD H.265-coded video streaming

Networked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real-time streaming because they require the original video sequence available at the receivers side. The primary aim of this study is to present a hybrid no-reference prediction model for the perceptual quality of 4kUHD H.265-coded video in the wireless domain. The contributions of this paper are two-fold: first, an investigation of the impact of quality of service (QoS) parameters on 4kUHD H.265-coded video transmission in an experimental environment; second, objective model based on fuzzy logic inference system is developed to predict the visual quality by mapping QoS parameters to the measured quality of experience. The model is evaluated in contrast to random neural networks. The results show that good prediction accuracy was obtained from the proposed hybrid prediction model. This study will help in the development of a reference-free video quality prediction model and QoS control methods for 4kUHD video streaming

Interval Type-2 Fuzzy Logic Quality prediction model for wireless 4kUHD H.265-coded video streaming

This paper proposes a prediction model for the perceptual quality of wireless 4kUHD H.265 video streaming. Based on Interval Type-2 Fuzzy Logic System (IT2FLS), the model exploits application and physical layer parameters. The results show that good prediction accuracy was obtained from the proposed prediction model. This study should help in the development of a reference-free video quality prediction model and QoS control methods for 4kUHD video streaming