Open Access Open Access  Restricted Access Subscription Access

Semantic-Empowered Digital Twins for 6G: A Scoping Review of Architectures, Enabling Technologies, and Future Directions

EKOLAMA, Solomon Malcolm, Onu, Kingsley Eyiogwu

Abstract


Digital twins (DTs) optimise resource allocation and intelligent network management but face severe synchronisation lag and intense spectral bottlenecks in ultra-dense 6G networks. Transitioning from passive, data-heavy digital mirrors to cognitive, semantic-empowered digital twins (SE-DTs) is essential to overcome conventional Shannon-centric transmission limitations and enable truly autonomous edge orchestration. This scoping review comprehensively maps recent architectural frameworks and enabling technologies designed to mitigate synchronisation latency, focusing explicitly on task-oriented communication protocols within industrial IoT and broader 6G wireless environments. Guided by the PRISMA-ScR methodological framework, a systematic search of IEEE Xplore, Scopus, and Web of Science databases from 2020 to 2026 was conducted. A rigorous multi-stage screening process was applied to filter relevant literature. The selection process yielded exactly 149 peer-reviewed articles focusing specifically on the structural intersection of semantic communication, deep generative models, and physical-layer digital twin networks. Synthesised data reveals three dominant technological trends: first, the deployment of distributed, edge-computed large language models for low-latency cognitive reasoning; second, the integration of reconfigurable intelligent surfaces (RIS) to protect fragile semantic features from deep channel fading; and third, the adoption of predictive semantic quantisation through non-linear deep joint source-channel coding, which significantly reduces raw bandwidth consumption during state updates. Despite these critical architectural advancements, our qualitative analysis reveals that current SE-DT frameworks suffer from major operational vulnerabilities, entirely lacking standardised cross-layer security protocols, robust knowledge graph synchronisation schemes, and universally accepted semantic-fidelity metrics. Developing lightweight, real-time cryptographic authentication mechanisms and decentralised trust architectures to defend against emerging semantic-layer vulnerabilities, such as ontology poisoning and malicious data manipulation, marks an urgent direction for future 6G edge research. Ultimately, resolving these foundational gaps is vital to ensure secure, resilient, and fully autonomous network orchestration across complex, multi-vendor industrial deployments.


Full Text:

PDF

References


Wu, Y., Zhang, K., & Zhang, Y. (2021). Digital twin networks: A survey. IEEE Internet of Things Journal, 8(18), 13789–13804. DOI: 10.1109/JIOT.2021.3079510.

Khan, L. U., Han, Z., Saad, W., Hossain, E., Guizani, M., & Hong, C. S. (2022). Digital twin of wireless systems: Overview, taxonomy, challenges, and opportunities. IEEE Communications Surveys & Tutorials, 24(4), 2230–2254. DOI: 10.1109/COMST.2022.3198273.

Kuruvatti, N. P., Habibi, M. A., Partani, S., Han, B., Fellan, A., & Schotten, H. D. (2022). Empowering 6G communication systems with digital twin technology: A comprehensive survey. IEEE Access, 10, 112158–112186. DOI: 10.1109/ACCESS.2022.3215493.

Masaracchia, A., Sharma, V., Canberk, B., Dobre, O. A., & Duong, T. Q. (2022). Digital twin for 6G: Taxonomy, research challenges, and the road ahead. IEEE Open Journal of the Communications Society, 3, 2137–2150. doi:10.1109/OJCOMS.2022.3219015.

Minerva, R., Lee, G. M., & Crespi, N. (2020). Digital twin in the IoT context: A survey on technical features, scenarios, and architectural models. Proceedings of the IEEE, 108(10), 1785–1824. DOI: 10.1109/JPROC.2020.2998530.

Alkhateeb, A., Jiang, S., & Charan, G. (2023). Real-time digital twins: Vision and research directions for 6G and beyond. IEEE Communications Magazine, 61(11), 128–134. DOI: 10.1109/MCOM.001.2200866.

Shafiq, M., Liu, Y., & Zhang, P. (2025). From data mirror to smart copilot: A survey on Zhu, F., Chen, J., Wen, J., Yang, Y., Yi, C., Tie, Y., Zhang, P., Cai, J., Niyato, D., & Guizani, M. (2026). From data mirror to smart copilot: A survey on NextG semantic communication for propelling digital twin world into cognitive stage. IEEE Communications Surveys & Tutorials, 28, 4915–4947. https://doi.org/10.1109/COMST.2026.3665395.

Kurka, D. B., & Gündüz, D. (2020). DeepJSCC-f: Deep joint source-channel coding of images with feedback. IEEE Journal on Selected Areas in Information Theory, 1(1), 178-193. DOI: 10.1109/JSAIT.2020.2987203.

Gündüz, D., Qin, Z., Aguerri, I. E., Dhillon, H. S., Yang, Z., Yener, A., Wong, K. K., & Chae, C.-B. (2023). Beyond transmitting bits: Context, semantics, and task-oriented communications. IEEE Journal on Selected Areas in Communications, 41(1), 5–41. doi:10.1109/JSAC.2022.3223408.

Strinati, E. C., & Barbarossa, S. (2021). 6G networks: Beyond Shannon towards semantic and goal-oriented communications. Computer Networks, 190, 107930. DOI: 10.1016/j.comnet.2021.107930.


Refbacks

  • There are currently no refbacks.