research-article

Attention-Aware Resource Allocation and QoE Analysis for Metaverse xURLLC Services

Authors:

Dong In KimAuthors Info & Claims

IEEE Journal on Selected Areas in Communications, Volume 41, Issue 7

Pages 2158 - 2175

https://doi.org/10.1109/JSAC.2023.3280978

Published: 01 July 2023 Publication History

Abstract

Metaverse encapsulates our expectations of the next-generation Internet, while bringing new key performance indicators (KPIs). Although conventional ultra-reliable and low-latency communications (URLLC) can satisfy objective KPIs, it is difficult to provide a personalized immersive experience that is a distinctive feature of the Metaverse. Since the quality of experience (QoE) can be regarded as a comprehensive KPI, the URLLC is evolved towards the next generation URLLC (xURLLC) with a personalized resource allocation scheme to achieve higher QoE. To deploy Metaverse xURLLC services, we study the interaction between the Metaverse service provider (MSP) and the network infrastructure provider (InP), and provide an optimal contract design framework. Specifically, the utility of the MSP, defined as a function of Metaverse users’ QoE, is to be maximized, while ensuring the incentives of the InP. To model the QoE mathematically, we propose a novel metric named Meta-Immersion that incorporates both the objective KPIs and subjective feelings of Metaverse users. Furthermore, we develop an attention-aware rendering capacity allocation scheme to improve QoE in xURLLC. Using a user-object-attention level dataset, we validate that the xURLLC can achieve an average of 20.1% QoE improvement compared to the conventional URLLC with a uniform resource allocation scheme. The code for this paper is available at <uri>https://github.com/HongyangDu/AttentionQoE</uri>.

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cover image IEEE Journal on Selected Areas in Communications

IEEE Journal on Selected Areas in Communications Volume 41, Issue 7

July 2023

334 pages

ISSN:0733-8716

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0733-8716 © 2023 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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Published: 01 July 2023

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