Terrestrial and Non-Terrestrial Networks for Integrated Sensing and Communication
Integrated Sensing And Communication (ISAC) emerges as a crucial aspect of 6G networks. Beyond merely transporting information, communication networks, especially for higher frequency wireless transmissions, can also work as sophisticated sensor arrays. In this scenario, the integration of Terrestrial Networks and Non-Terrestrial Networks (TN-NTNs) appears as a fundamental base for ISAC mainly due to the extensive network dimensions and the use of different mmWave, sub-THz, THz, and optical channels. This paper shows how the TN-NTN Management and Orchestration architectures, leveraging different elements for data collection and Artificial Intelligence-based analysis, can be a reference for sensing operations. In particular, we refer to the vision of the Italian ITA-NTN project, which proposes some guidelines for the management and control of the whole TN-NTN infrastructure considering the main recommendations for cross-domains coming from organizations as 3GPP and ETSI.
Authors
- Luigi Alfredo Grieco (ORCID: https://orcid.org/0000-0002-3443-6924)
- Arcangela Rago (ORCID: https://orcid.org/0000-0002-0812-269X)
- Francesco Malandrino (ORCID: https://orcid.org/0000-0003-0458-2004)
- Alessio Fascista (ORCID: https://orcid.org/0000-0001-6645-6391)
- F. Matera (ORCID: https://orcid.org/0009-0004-6833-0951)
- Giuseppe Virone (ORCID: https://orcid.org/0000-0001-5683-9436)
- Ernestina Cianca (ORCID: https://orcid.org/0000-0002-0337-8354)
- Giuseppe Piro (ORCID: https://orcid.org/0000-0003-3783-5565)
- M. Ruggieri (ORCID: https://orcid.org/0000-0002-9212-3272)
- M. Settembre
- Simone Morosi (ORCID: https://orcid.org/0000-0002-0145-8406)
Institutions
- University of Rome Tor Vergata (IT)
- Fondazione "Ugo Bordoni" (IT)
- University of Florence (IT)
- Polytechnic University of Bari (IT)
Publication Details
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/isse63315.2024.10741118
- Citations
- 4
- Primary Topic
- Energy Efficient Wireless Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 1.40