Towards 5G/6G data harmonization through NLP and semantic web technologies
Telecommunication systems utilize several mechanisms to collect data from 5G/6G-enabled IoT. In the 5G/6G community, various AI techniques and tools are applied to 5G/6G data to monitor, predict, and make decisions. Therefore, 5G/6G data must be interoperable for monitoring, prediction, and decision support systems. However, 5G/6G data are typically mapped in local data models for local applications, which poses challenges to using them in different or cross-domain applications due to a lack of interoperability issues. In this paper, we propose an approach to support and enhance the interoperability of 5G/6G data through NLP and Semantic Web technologies to achieve 5G/6G data harmonization.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-03-19
- DOI
- https://doi.org/10.5281/zenodo.15069713
- Primary Topic
- Wireless Signal Modulation Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00