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Human-Centric Resource Allocation in the Metaverse Over Wireless Communications | IEEE Journals & Magazine | IEEE Xplore

Human-Centric Resource Allocation in the Metaverse Over Wireless Communications


Abstract:

The Metaverse will provide numerous immersive applications for human users, by consolidating technologies like extended reality (XR), video streaming, and cellular networ...Show More

Abstract:

The Metaverse will provide numerous immersive applications for human users, by consolidating technologies like extended reality (XR), video streaming, and cellular networks. Optimizing wireless communications to enable the human-centric Metaverse is important to satisfy the demands of mobile users. In this paper, we formulate the optimization of the system utility-cost ratio (UCR) for the Metaverse over wireless networks. Our human-centric utility measure for virtual reality (VR) applications of the Metaverse represents users’ perceptual assessment of the VR video quality as a function of the data rate and the video resolution and is learned from real datasets. The variables jointly optimized in our problem include the allocation of both communication and computation resources as well as VR video resolutions. The system cost in our problem comprises the energy consumption and delay and is non-convex with respect to the optimization variables. To solve the non-convex optimization, we develop a novel fractional programming technique, which contributes to optimization theory and has broad applicability beyond our paper. Our proposed algorithm for the system UCR optimization is computationally efficient and finds a stationary point to the constrained optimization. Through extensive simulations, our algorithm is demonstrated to outperform other approaches.
Published in: IEEE Journal on Selected Areas in Communications ( Volume: 42, Issue: 3, March 2024)
Page(s): 514 - 537
Date of Publication: 21 December 2023

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I. Introduction

The Metaverse is expected to offer a myriad of opportunities for mobile users to interact with the immersive virtual world [1]. In various Augmented/Virtual Reality (AR/VR) applications for the Metaverse, humans are at the core since users judge whether the AR/VR videos or games provide a satisfying Quality of Experience (QoE) [2]. Compared with the traditional Quality of Service (QoS) that measures the objective service performance (e.g., bit rate, data accuracy), QoE as a utility measure concerns the enjoyment of users [3]. Providing satisfying utilities to multiple users in a resource-constrained system requires allocating resources wisely. In this paper, we formulate and solve human-centric resource allocation for VR in the Metaverse over wireless communications. Our goal is to reduce the Metaverse system’s cost in terms of delay and energy, as well as to enhance the human-centric utilities of mobile users accessing the Metaverse via wireless networks. Tackling this problem also motivates us to propose a new optimization technique.

Cites in Papers - |

Cites in Papers - IEEE (10)

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1.
Lei Feng, Xiaoyi Jiang, Yao Sun, Dusit Niyato, Yu Zhou, Shiyi Gu, Zhixiang Yang, Yang Yang, Fanqin Zhou, "Resource Allocation for Metaverse Experience Optimization: A Multi-Objective Multi-Agent Evolutionary Reinforcement Learning Approach", IEEE Transactions on Mobile Computing, vol.24, no.4, pp.3473-3488, 2025.
2.
Liangxin Qian, Chang Liu, Jun Zhao, "User Connection and Resource Allocation Optimization in Blockchain Empowered Metaverse Over 6G Wireless Communications", IEEE Transactions on Wireless Communications, vol.24, no.1, pp.19-34, 2025.
3.
Yingzhi Huang, Kaiyi Chi, Qianqian Yang, Zhaohui Yang, Zhaoyang Zhang, "Soft Actor-Critic-Based Multi-User Multi-TTI MIMO Precoding in Multi-Modal Real-Time Broadband Communications", IEEE Transactions on Wireless Communications, vol.23, no.12, pp.18286-18301, 2024.
4.
Bowen Shen, Kwok-Yan Lam, Yuhang Zheng, Kai Wey Lim, Wenzhuo Yang, Feng Li, "An Efficient and Certified LEO Satellite-Enabled Smart Management System", 2024 International Conference on ICT for Smart Society (ICISS), pp.1-7, 2024.
5.
Sijie Ji, Lixiang Lian, Yuanqing Zheng, Chenshu Wu, "MuSAC: Mutualistic Sensing and Communication for Mobile Crowdsensing", 2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS), pp.243-254, 2024.
6.
Yitong Wang, Chang Liu, Jun Zhao, "Offloading and Quality Control for AI Generated Content Services in 6G Mobile Edge Computing Networks", 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), pp.1-7, 2024.
7.
Liangxin Qian, Jun Zhao, "User Association and Resource Allocation in Large Language Model Based Mobile Edge Computing System over 6G Wireless Communications", 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), pp.1-7, 2024.
8.
Akshita Gupta, Drishti Diwani, Vivek Ashok Bohara, Anand Srivastava, "QoS Aware Task Offloading for Digital-Twin Enabled Connected Vehicular Network", 2024 IEEE Wireless Communications and Networking Conference (WCNC), pp.1-6, 2024.
9.
Yang Lil, Xinyu Zhou, Jun Zhao, "Resource Allocation for Semantic Communication Under Physical-layer Security", GLOBECOM 2023 - 2023 IEEE Global Communications Conference, pp.2063-2068, 2023.
10.
Tianming Lan, Jun Zhao, "Optimization in Mobile Augmented Reality Systems for the Metaverse Over Wireless Communications", GLOBECOM 2023 - 2023 IEEE Global Communications Conference, pp.5439-5444, 2023.

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