Print Email Facebook Twitter Aerial Base Station Placement Leveraging Radio Tomographic Maps Title Aerial Base Station Placement Leveraging Radio Tomographic Maps Author Romero, Daniel (University of Agder) Viet, Pham Q. (University of Agder) Leus, G.J.T. (TU Delft Signal Processing Systems) Date 2022 Abstract Mobile base stations on board unmanned aerial vehicles (UAVs) promise to deliver connectivity to those areas where the terrestrial infrastructure is overloaded, damaged, or absent. A fundamental problem in this context involves determining a minimal set of locations in 3D space where such aerial base stations (ABSs) must be deployed to provide coverage to a set of users. While nearly all existing approaches rely on average characterizations of the propagation medium, this work develops a scheme where the actual channel information is exploited by means of a radio tomographic map. A convex optimization approach is presented to minimize the number of required ABSs while ensuring that the UAVs do not enter no-fly regions. A simulation study reveals that the proposed algorithm markedly outperforms its competitors. Subject Aerial base stationsradio tomographyradio mapsspectrum cartographyplacement To reference this document use: http://resolver.tudelft.nl/uuid:070bf3c9-6848-4062-9004-246f5171f939 DOI https://doi.org/10.1109/ICASSP43922.2022.9746987 Publisher IEEE, Piscataway Embargo date 2022-10-27 ISBN 978-1-6654-0541-6 Source Proceedings of the ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Event ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022-05-23 → 2022-05-27, Singapore, Singapore Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 Daniel Romero, Pham Q. Viet, G.J.T. Leus Files PDF Aerial_Base_Station_Place ... c_Maps.pdf 1.15 MB Close viewer /islandora/object/uuid:070bf3c9-6848-4062-9004-246f5171f939/datastream/OBJ/view