# Enabling the Wireless Metaverse via Semantic Multiverse Communication

arXiv: https://arxiv.org/abs/2212.06908 · HTML: https://mlsanity.com/paper/2212.06908/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 21 references that are in the map.
- First posted on arXiv 13 Dec 2022.

## Builds on (most cited first, 10 of 10)

- [Magic3D: High-Resolution Text-to-3D Content Creation](https://mlsanity.com/paper/2211.10440/) (2022)
- [Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications](https://mlsanity.com/paper/2207.09353/) (2022)
- [A Survey of Multi-Agent Deep Reinforcement Learning with Communication](https://mlsanity.com/paper/2203.08975/) (2022)
- [Communication-Efficient and Distributed Learning Over Wireless Networks: Principles and Applications](https://mlsanity.com/paper/2008.02608/) (2020)
- [Semantics-Native Communication with Contextual Reasoning](https://mlsanity.com/paper/2108.05681/) (2021)
- [Towards a Decentralized Metaverse: Synchronized Orchestration of Digital Twins and Sub-Metaverses](https://mlsanity.com/paper/2211.14686/) (2022)
- [Towards Semantic Communication Protocols: A Probabilistic Logic Perspective](https://mlsanity.com/paper/2207.03920/) (2022)
- [A Unified View on Semantic Information and Communication: A Probabilistic Logic Approach](https://mlsanity.com/paper/2201.05936/) (2022)
- [Minimizing Latency to Support VR Social Interactions over Wireless Cellular Systems via Bandwidth Allocation](https://mlsanity.com/paper/1802.03450/) (2018)
- [URLLC-eMBB Slicing to Support VR Multimodal Perceptions over Wireless Cellular Systems](https://mlsanity.com/paper/1805.00142/) (2018)

## Built on by (most cited first, 6 of 6)

- [Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey](https://mlsanity.com/paper/2405.20024/) (2024)
- [Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities](https://mlsanity.com/paper/2307.06687/) (2023)
- [Semantic Information Marketing in The Metaverse: A Learning-Based Contract Theory Framework](https://mlsanity.com/paper/2302.11457/) (2023)
- [Energy-Efficient Downlink Semantic Generative Communication with Text-to-Image Generators](https://mlsanity.com/paper/2306.05041/) (2023)
- [Enhancing Semantic Communication with Deep Generative Models -- An ICASSP Special Session Overview](https://mlsanity.com/paper/2309.02478/) (2023)
- [Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions](https://mlsanity.com/paper/2604.25018/) (2026)

## Abstract (arXiv)

Metaverse over wireless networks is an emerging use case of the sixth generation (6G) wireless systems, posing unprecedented challenges in terms of its multi-modal data transmissions with stringent latency and reliability requirements. Towards enabling this wireless metaverse, in this article we propose a novel semantic communication (SC) framework by decomposing the metaverse into human/machine agent-specific semantic multiverses (SMs). An SM stored at each agent comprises a semantic encoder and a generator, leveraging recent advances in generative artificial intelligence (AI). To improve communication efficiency, the encoder learns the semantic representations (SRs) of multi-modal data, while the generator learns how to manipulate them for locally rendering scenes and interactions in the metaverse. Since these learned SMs are biased towards local environments, their success hinges on synchronizing heterogeneous SMs in the background while communicating SRs in the foreground, turning the wireless metaverse problem into the problem of semantic multiverse communication (SMC). Based on this SMC architecture, we propose several promising algorithmic and analytic tools for modeling and designing SMC, ranging from distributed learning and multi-agent reinforcement learning (MARL) to signaling games and symbolic AI.