Video Quality Prediction in Streaming Services using 5G Networks

• Ivo A. Pimenta UECE
• Michael S. Souza UECE
• Carlos A. Aquino UECE
• Ariel L. Portela UECE
• Rafael L. Gomes UECE

DOI: https://doi.org/10.5753/courb.2024.2882

Abstract

The advent of 5G networks has brought about a significant transformation in contemporary society, highlighting notable growth, especially in the real-time video transmission sector but also in streaming services. However, users still face issues with inadequate video quality, particularly when the transmission characteristics of 5G networks vary. Within this context, this article presents an Artificial Intelligence (AI) model for predicting the video quality delivered to the end user. The proposed model considers both static and dynamic scenarios in vehicular devices, recognizing the importance of understanding content delivery according to the user’s situation. This work’s proposal uses real network data from 5G network measurements, enabling the optimization of user experience in dynamic 5G environments. The results demonstrate that the proposal is capable of contributing to the continuous improvement of video quality delivery in the context of mobile networks.

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