CNI participates to first responder exercise in Ahr valley
Networked Rescue robots can support first responders by providing high resolution situational insights in case of floodings and other large scale incidents. Therefore the LARUS-PRO UAV was tested jointly with rescue organizations in the Ahr valley (Germany), which was struck by a devastating flooding in 2021. CNI supported the excercise (on October 29, 2022) with its mobile wireless communication lab, which hosted a digital twin representation of the exploration mission. In addition, CNI gathered data of the public mobile radio networks in order to improve its data-driven radio channel prediction method DRaGoN, which is planned to be used for network planning of 5G and future 6G networks.
A press report about the excercise can be found here.
Further information on the research in LARUS and LARUS-PRO can be found in the following publications:
- J. Güldenring, P. Gorczak, F. Eckermann, M. Patchou, J. Tiemann, F. Kurtz, C. Wietfeld, "Reliable Long-Range Multi-Link Communication for Unmanned Search and Rescue Aircraft Systems in Beyond Visual Line of Sight Operation", In Drones, MDPI, vol. 4, no. 2, May 2020.
- J. Tiemann, O. Feldmeier, C. Wietfeld, "Supporting Maritime Search and Rescue Missions through UAS-based Wireless Localization", In IEEE Global Communications Conference Workshops (GLOBECOM Workshops), The 9th International Workshop on Wireless Networking and Control of Unmanned Autonomous Vehicles (Wi-UAV), Abu Dhabi, United Arab Emirates, December 2018. [pdf] [Details]
The newly proposed DRaGoN method developed on the reserach projects DFG SFB 876, Plan& Play as well as 6GEM is described in detail in the following work:
- M. Geis, B. Sliwa, C. Bektas, C. Wietfeld, "TinyDRaGon: Lightweight Radio Channel Estimation for 6G Pervasive Intelligence", In 2022 IEEE Future Networks World Forum (FNWF), Montreal, Canada, October 2022. (Best Paper Award). [pdf] [Details]
- B. Sliwa, M. Geis, C. Bektas, M. Lopéz, P. Mogensen, C. Wietfeld, "DRaGon: Mining latent radio channel information from geographical data leveraging deep learning", In 2022 IEEE Wireless Communications and Networking Conference (WCNC), Austin, Texas, USA, May 2022. [pdf] [Details]