.png){kind=icon}
.png){kind=icon}
Return
Optimal Transport of Multimodal Visual-Haptic Metaverse Flows in the Presence of eMBB Traffic
.png){kind=icon}
PRE
AI
J
T
S
DOI：10.1109/tnsm.2026.3714067.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We study resource allocation for multiple metaverse users in 5G networks and beyond. To ensure an immersive experience, one should consider the multimodal nature of the metaverse, where each user generates multiple coupled flows, e.g., visual and haptic, characterized by joint Quality of Experience (QoE) requirements, for instance in terms of subjective Just Noticeable Difference (JND) metric. These flows can be transported via 5G services, such as Ultra Reliable Low Latency Communications (URLLC) for the haptic flow and enhanced Mobile Broadband (eMBB) for the visual one. Furthermore, the metaverse users share the radio resources with classical eMBB users. We formulate an optimization problem to maximize the weighted sum of visual throughput for metaverse users and the throughput of eMBB users relative to their minimum requirements, subject to fairness and feasibility constraints. Our approach accounts for discrete Modulation and Coding Schemes (MCS) and heterogeneous radio conditions. Numerical results show that our proposed scheme effectively balances throughput, fairness, and immersive-experience requirements, avoiding the feasibility violations observed under equal allocation and reducing immersive-constraint violations by approximately 19% with respect to a non-immersive baseline. We eventually make use of real haptic traffic traces to evaluate computation time and performance under varying haptic requirements.
Keywords:
Metaverse
resource allocation
5G/6G
Journal
IF:
5.4
Papers:
509
Citations:
9.2K
Organization
Cited Papers