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.
|Title of host publication||Proceedings of the ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|
|Place of Publication||Piscataway|
|Number of pages||5|
|Publication status||Published - 2022|
|Event||ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Singapore, Singapore|
Duration: 23 May 2022 → 27 May 2022
|Conference||ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)|
|Period||23/05/22 → 27/05/22|
Bibliographical noteGreen 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.
- Aerial base stations
- radio tomography
- radio maps
- spectrum cartography