The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications
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| Titel: | The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications |
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| Autoren: | Gonzalez-Prelcic, Nuria, Keskin, Musa Furkan, 1988, Kaltiokallio, Ossi, Valkama, M., Dardari, Davide, Shen, Xiao, Shen, Yuan, Bayraktar, Murat, Wymeersch, Henk, 1976 |
| Quelle: | A holistic flagship towards the 6G network platform and system, to inspire digital transformation, for the world to act together in meeting needs in society and ecosystems with novel 6G services Hårdvarumedveten integrerad lokalisering och avkänning för kommunikationssystem Proceedings of the IEEE. 112(7):676-723 |
| Schlagwörter: | radio simultaneous localization and mapping (SLAM), Distributed joint sensing and communication (S&C), 6G mobile communication, integrated sensing and communications (ISACs), Signal processing algorithms, reconfigurable intelligent surface (RIS)-aided localization, radio positioning, Simultaneous localization and mapping, monostatic sensing, Industries, Wireless networks, near-field ISAC, Surveys, sensing-aided communication, Sensors |
| Beschreibung: | Future wireless networks will integrate sensing, learning, and communication to provide new services beyond communication and to become more resilient. Sensors at the network infrastructure, sensors on the user equipment (UE), and the sensing capability of the communication signal itself provide a new source of data that connects the physical and radio frequency (RF) environments. A wireless network that harnesses all these sensing data can not only enable additional sensing services but also become more resilient to channel-dependent effects such as blockage and better support adaptation in dynamic environments as networks reconfigure. In this article, we provide a vision for integrated sensing and communication (ISAC) networks and an overview of how signal processing, optimization, and machine learning (ML) techniques can be leveraged to make them a reality in the context of 6G. We also include some examples of the performance of several of these strategies when evaluated using a simulation framework based on a combination of ray-tracing measurements and mathematical models that mix the digital and physical worlds. |
| Zugangs-URL: | https://research.chalmers.se/publication/541349 |
| Datenbank: | SwePub |
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Nájsť tento článok vo Web of Science | Abstract: | Future wireless networks will integrate sensing, learning, and communication to provide new services beyond communication and to become more resilient. Sensors at the network infrastructure, sensors on the user equipment (UE), and the sensing capability of the communication signal itself provide a new source of data that connects the physical and radio frequency (RF) environments. A wireless network that harnesses all these sensing data can not only enable additional sensing services but also become more resilient to channel-dependent effects such as blockage and better support adaptation in dynamic environments as networks reconfigure. In this article, we provide a vision for integrated sensing and communication (ISAC) networks and an overview of how signal processing, optimization, and machine learning (ML) techniques can be leveraged to make them a reality in the context of 6G. We also include some examples of the performance of several of these strategies when evaluated using a simulation framework based on a combination of ray-tracing measurements and mathematical models that mix the digital and physical worlds. |
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| ISSN: | 15582256 00189219 |
| DOI: | 10.1109/JPROC.2024.3397609 |