The rapid growth in mobile video consumption, driven by advancements in mobile devices and network infrastructure, has raised user expectations for seamless video Quality of Experience (QoE) despite improvements in video streaming, network impairments like packet loss, delay, jitter, and outages. For instance, outages can cause visual artifacts like freezing, jumping, and missing frames, which negatively affect user perception. Understanding the relationship between network performance and QoE is crucial for improving user satisfaction.

This thesis investigates the impact of network performance on mobile video QoE and proposes strategies to mitigate these effects. The objectives include: (1) understanding TCP/IP’s role in influencing QoE, (2) exploring the effects of Quality of Service (QoS) parameters such as delay, jitter, and packet loss on video quality, (3) analyzing the impact of network outages on QoE, and (4) developing a buffer-based solution to mitigate network disruptions.

The research employs theoretical modeling, controlled emulation experiments, and subjective assessments to evaluate QoE. The QoE Hourglass Model links network-layer parameters to user-perceived quality. Subjective tests, guided by ITU-T recommendations, use the Absolute Category Rating (ACR) method and Mean Opinion Scores (MOS) to assess video quality under various conditions. Additionally, the effectiveness of a sender buffer mechanism is tested through statistical analyses and user evaluations.

The findings reveal that network impairments, especially packet loss and delay variation, significantly degrade QoE. The QoE Hourglass Model provides a structured framework for understanding these effects. Experimental results show that higher frame rates and proactive buffering improve user perception. Perceptual Evaluation of Video Quality (PEVQ) and Temporal Quality Metric (TQM) measurements correlate with user ratings but are less accurate in predicting video freezes. The sender buffer mechanism effectively reduces freeze durations and enhances QoE during network outages.

This research emphasizes the impact of network impairments on video QoE and offers practical solutions, such as the sender buffer mechanism, to mitigate disruptions and enhance user satisfaction in video streaming.