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Location-Dependent Augmented Reality Services in Wireless Edge-Enabled Metaverse Systems
Communications Society, IEEE Open Journal of the, 2023, Vol.4, p.171-183
2020 IEEE ;DOI: 10.1109/OJCOMS.2023.3234254
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Title:
Location-Dependent Augmented Reality Services in Wireless Edge-Enabled Metaverse Systems
Author:
Zhang, Hongliang
;
Mao, Shiwen
;
Niyato, Dusit
;
Han, Zhu
Subjects:
Downlink
;
Estimation error
;
Location awareness
;
location-dependent augmented reality
;
Metaverse
;
multi-access edge computing
;
Quality of experience
;
resource management
;
Uplink
;
Wireless communication
Is Part Of:
Communications Society, IEEE Open Journal of the, 2023, Vol.4, p.171-183
Description:
Metaverse is envisioned as the next-generation paradigm that links a virtual world to the physical world, providing immersive experience for human activities in the hypothetical environment with augmented reality (AR) and virtual reality (VR) technology. Recent development of wireless multiaccess edge computing (MEC) has accelerated the realization of this vision. In this paper, we consider location-dependent AR services in MEC-enabled Metaverse systems. In such a system, each user performs simultaneous localization and communication first to estimate its position and request AR contents from the MEC server. Due to limited computation and communication resources, the MEC server adaptively adjusts the resolution of AR contents. However, two challenges arise in such a system. First, the localization error will degrade the user's quality-of-experience (QoE); and second, the coupling of communication and computation complicates the resource management. To address these issues, we first model the QoE taking the localization errors into consideration, and then propose a minimum QoE maximization scheme to achieve fairness among users by jointly optimizing the waveform at users, the transmit power at the base station (BS), and the resolution of transmitted videos. Simulation results verify the effectiveness of the proposed scheme in comparison with benchmark schemes.
Publisher:
IEEE
Language:
English
Identifier:
DOI: 10.1109/OJCOMS.2023.3234254
Source:
IEEE Open Access Journals
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