QoE Assessment Aspects for Virtual Reality and Holographic Telepresence Applications

Kougioumtzidis, Georgios; Poulkov, Vladimir; Zaharis, Zaharias D.; Lazaridis, Pavlos I.

doi:10.1007/978-3-031-15101-9_12

Cited by 6 publications

(5 citation statements)

References 23 publications

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“…The literature reports two ways of evaluating QoE, subjective and objective evaluation [21]. In subjective methods, participants evaluate the quality of a service after being subjected to a set of tests or stimuli.…”

Section: A Prediction Methodologiesmentioning

confidence: 99%

QoE Prediction for Gaming Video Streaming in O-RAN Using Convolutional Neural Networks

Kougioumtzidis,

Vlahov,

Poulkov

et al. 2024

IEEE Open J. Commun. Soc.

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The growing popularity of online and cloud gaming applications is reshaping the landscape of the entertainment industry and acting as a key driver of market growth. However, the dependency of these applications on network resources poses significant challenges to the communication infrastructure. This is particularly critical as network performance plays a key role in influencing user satisfaction during gameplay. Inevitably, these inherently interactive applications are also closely linked to the concept of quality of experience (QoE), which expresses the perceived quality of a service by end-users. In this paper, we leverage deep learning methodologies to develop an objective QoE prediction model. Specifically, the proposed prediction model investigates the effect of wireless network operation on the QoE of gaming video streaming. Employing a tailored multi-headed convolutional neural network (multi-headed CNN), the model can predict in real-time the transmission-related QoE value using measurable quality of service (QoS) parameters. To validate the effectiveness of the model, tests and evaluations were conducted in an open radio access network testbed environment equipped with O-RAN-compatible interfaces.

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Section: A Prediction Methodologiesmentioning

confidence: 99%

QoE Prediction for Gaming Video Streaming in O-RAN Using Convolutional Neural Networks

Kougioumtzidis,

Vlahov,

Poulkov

et al. 2024

IEEE Open J. Commun. Soc.

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“…Since the perceived QoE is a crucial performance indicator for holographic telepresence applications [58], [59], meeting HTC demands is essential. However, this is not a trivial task and 5G networks encounter challenges in this context.…”

Section: G Limitations To Meet Htc Kpismentioning

confidence: 99%

On the Way to Holographic-Type Communications: Perspectives and Enabling Technologies

Petkova,

Bozhilov,

Manolova

et al. 2024

IEEE Access

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Holographic-type communication (HTC) is on the verge of revolutionizing current communication paradigms. It will seamlessly connect people from distant locations through a fully immersive experience that will engage all five senses: sight, hearing, touch, smell, and taste. However, the practical realization and widespread adoption of HTC impose significant demands on current networks and enduser devices. While recent studies have primarily focused on discussing the HTC challenges and potential research directions, this paper takes a further step by evaluating the capabilities of wireless networks to meet HTC requirements. Specifically, it highlights the limitations of the fifth-generation (5G) networks by identifying HTC-related Key Performance Indicators (KPIs) and explores the potential of the sixth-generation (6G) networks. Moreover, it not only proposes potential research approaches for HTC enhancement but also analyzes their impact on the challenges in HTC implementation. Finally, the paper questions the ubiquitous potential of 6G, suggesting that a coordinated approach leveraging artificial intelligence (AI) for jointly optimizing user sites and communication networks is the most promising strategy, rather than solely relying on the capabilities of specific network generations.

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“…Second, managing network resources to guarantee the QoE of individual users in immersive communications necessitates user-level information. Even if several users request the same service, they may have different resource demands for improving their QoE (Kougioumtzidis et al, 2022). For example, due to the difference in the sensitivity of haptic perception, e.g., reaction time, the haptic sensors of interest and the scan time for each haptic sensor may differ in supporting different users, yielding different communication and computing resource demands (Coutinho and Boukerche, 2022).…”

Section: Qoe-oriented Networkingmentioning

confidence: 99%

Toward immersive communications in 6G

Shen

Gao

et al. 2023

Front. Comput. Sci.

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The sixth generation (6G) networks are expected to enable immersive communications and bridge the physical and the virtual worlds. Integrating extended reality, holography, and haptics, immersive communications will revolutionize how people work, entertain, and communicate by enabling lifelike interactions. However, the unprecedented demand for data transmission rate and the stringent requirements on latency and reliability create challenges for 6G networks to support immersive communications. In this survey article, we present the prospect of immersive communications and investigate emerging solutions to the corresponding challenges for 6G. First, we introduce use cases of immersive communications, in the fields of entertainment, education, and healthcare. Second, we present the concepts of immersive communications, including extended reality, haptic communication, and holographic communication, their basic implementation procedures, and their requirements on networks in terms of transmission rate, latency, and reliability. Third, we summarize the potential solutions to addressing the challenges from the aspects of communication, computing, and networking. Finally, we discuss future research directions and conclude this study.

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QoE Assessment Aspects for Virtual Reality and Holographic Telepresence Applications

Cited by 6 publications

References 23 publications

QoE Prediction for Gaming Video Streaming in O-RAN Using Convolutional Neural Networks

QoE Prediction for Gaming Video Streaming in O-RAN Using Convolutional Neural Networks

On the Way to Holographic-Type Communications: Perspectives and Enabling Technologies

Toward immersive communications in 6G

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