Block Successive Upper-Bound Minimization for Resource Scheduling in Wireless Metaverse
Khan, Latif U. Ullah, Waseem Muhaidat, Sami Guizani, Mohsen Hamdaoui, Bechir
Khan, Latif U.
Ullah, Waseem
Muhaidat, Sami
Guizani, Mohsen
Hamdaoui, Bechir
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Department
Machine Learning
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Type
Journal article
Date
2025
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Language
English
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Abstract
In recent years, there has been a rising trend towards emerging applications (e.g., brain-computer interaction and haptics-based autonomous cars) with diverse requirements. To effectively enable these applications via autonomous operation and intelligent analytics, one can use a metaverseFor more details on how a metaverse can enable emerging applications and architecture, please refer to khan2024ametaverse. In a metaverse, we have two spaces: (a) a meta space based on a virtual model that performs analysis and resource management and (b) a physical space comprised of real world entities. A metaverse effectively enables emerging applications by performing three main tasks: (a) distributed learning of metaverse models; (b) instantly serving the end-users; and (c) sensing of the physical environment and sharing it with the meta space for synchronized operation. To perform these tasks, efficient wireless resource management is needed. Therefore, a novel resource scheduling framework for the wireless metaverse to enable various applications is proposed. Our aim is to minimize the cost of learning and sensing in metaverse. Subsequently, we formulate a problem. Meanwhile, the reliability as well as latency constraints of the service-requesting devices/users will be fulfilled. We assign multiple resource blocks to learning and sensing devices/units, whereas we use a concept of puncturing for service-requesting devices/users upon arrival. We use a scheme that is based on block successive upper-bound minimization and convex optimization for solving our formulated problem. At the end, we use empirical cumulative distribution function vs. cost and cost vs. metaverse entities for numerical evaluations.
Citation
L. U. Khan, W. Ullah, S. Muhaidat, M. Guizani and B. Hamdaoui, "Block Successive Upper-Bound Minimization for Resource Scheduling in Wireless Metaverse," in IEEE Transactions on Network and Service Management, doi: 10.1109/TNSM.2025.3562516
Source
IEEE Transactions on Network and Service Management
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Keywords
etaverse, convex optimization, digital twins, resource optimization
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Publisher
IEEE