METHODS AND MODELS FOR ENSURING QUALITY OF EXPERIENCE IN INFORMATION AND COMMUNICATION SYSTEMS

Petro Pelekh

Abstract


Background. Quality of Experience (QoE) has emerged as a fundamental metric for evaluating the effectiveness of modern information and communication systems, especially in video conferencing environments where real-time interaction is critical. Unlike traditional Quality of Service (QoS) metrics, QoE reflects the subjective perception of users and depends on a combination of technical, behavioral, and contextual factors.

Materials and Methods. The research is based on a comprehensive analysis of contemporary scientific approaches to QoE evaluation in telecommunication systems. A structured set of influencing factors was identified, including technical parameters (network delay, bandwidth, packet loss, noise, and distortions), user-related characteristics (perception, expectations, and interaction behavior), and contextual conditions of service usage. Mathematical modeling methods, including linear regression, neural networks, decision trees, Bayesian approaches, and similarity functions, were considered for predicting QoE. Additionally, the E-model was applied as a standardized approach for evaluating QoS.

Results and Discussion. The experimental results demonstrate that network impairments have a significant negative impact on both QoS and QoE in video conferencing systems. In particular, increased network delays lead to communication interruptions and reduced interactivity, while packet loss results in audio degradation and visual artifacts. The data obtained in this work reveals a strong correlation between objective network parameters and subjective user satisfaction. The conducted modeling confirmed the existence of a nonlinear dependence of QoE on network parameters, particularly delay and packet loss. These results demonstrate the effectiveness of an integrated QoE model in evaluating network services.

Conclusion. The study confirms that network delay and packet loss are among the most influential factors affecting user experience in video conferencing systems. The proposed modeling approach allows for more precise evaluation and forecasting of QoE by incorporating both objective and subjective components. The findings highlight the importance of integrating multiple parameters into unified models for accurate QoE prediction.

Keywords: Quality of Experience, Quality of Service, video conferencing, model, adaptation, communication system.


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References


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DOI: http://dx.doi.org/10.30970/eli.34.12

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