An overview of quality assessment methods of video transmission over wireless networks

Chaari, Hekma; Mnif, Kais; Kamoun, Lotfı

doi:10.1109/melcon.2012.6196537

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Video streaming will provide new sources of income for network operators and content providers, since it will be a major application in future wireless systems and a key factor in ensuring their success [3,4]. At the same time, users have been producing, sharing, and accessing thousands of video services on wireless devices.…”

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A real-time video quality estimator for emerging wireless multimedia systems

et al. 2014

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Wireless Mesh Networks (WMNs) are increasingly deployed to enable thousands of users to share, create, and access live video streaming with different characteristics and content, such as video surveillance and football matches. In this context, there is a need for new mechanisms for assessing the quality level of videos because operators are seeking to control their delivery process and optimize their network resources, while increasing the user's satisfaction. However, the development of in-service and non-intrusive Quality of Experience assessment schemes for real-time Internet videos with different complexity and motion levels, Group of Picture lengths, and characteristics, remains a significant challenge. To address this issue, this article proposes a nonintrusive parametric real-time video quality estimator, called MultiQoE that correlates wireless networks' impairments, videos' characteristics, and users' perception into a predicted Mean Opinion Score. An instance of MultiQoE was implemented in WMNs and performance evaluation results demonstrate the efficiency and accuracy of MultiQoE in predicting the user's perception of live video streaming services when compared to subjective, objective, and well-known parametric solutions.

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A real-time video quality estimator for emerging wireless multimedia systems

et al. 2014

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“…In cellular networks, a video streaming is considered as a major research problem nowadays because of the increased demand for high video quality [1,2]. Since the wireless channel has different time features, the video streams playing process may be interrupted, which causes frames not to complete their flow into the buffer on client's device [3,4].…”

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Developing a Video Buffer Framework for Video Streaming in Cellular Networks

Jabbar

Kadhim

2018

Wireless Communications and Mobile Computing

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This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different videos at different bitrates. Meanwhile, at the proposed distribution mechanism, a predetermined threshold value is selected for lower and upper levels of playout outage probability. Then, the control unit at the base station will distribute the radio resources and decide the minimum rate requirement based on clients’ urgency categories. Simulation results showed that the VBF grantees fairness of resources distribution among different clients within the same cellular network while minimizing the interruption duration and controlling the video buffer at an acceptable level. Also, the results showed that the system throughput of the proposed framework outperforms other existing algorithms such as playout buffer and discontinuous reception aware scheduling (PBDAS), maximum carrier-to-interface ratio (MAX-CIR), and proportional fair (PF) due to enhancing the quality of experience for video streaming by increasing the radio resources in fairness manner.

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