Deep Learning-Aided QoE Prediction for Virtual Reality Applications Over Open Radio Access Networks

Deep Learning-Aided QoE Prediction for Virtual Reality Applications Over Open Radio Access Networks

Nowadays, innovative applications in the field of virtual reality (VR) are being developed, attracting the interest of both academia and industry. Wireless VR applications focus on various aspects of daily life, such as smart education, entertainment, healthcare, tourism, architecture, automotive, a...

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Bibliographic Details
Main Authors: Georgios Kougioumtzidis, Atanas Vlahov, Vladimir K. Poulkov, Pavlos I. Lazaridis, Zaharias D. Zaharis
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Deep learning
deep neural network (DNN)
long short-term memory (LSTM)
open radio access network (Open RAN)
quality of experience (QoE)
QoE prediction
Online Access:https://ieeexplore.ieee.org/document/10363177/

Internet

https://ieeexplore.ieee.org/document/10363177/

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