The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Cellular Connectivity for UAVs: Network Modeling, Performance Analysis, and Design Guidelines
Open accessAbstract
The growing use of aerial user equipments (UEs) in various applications requires ubiquitous and reliable connectivity for safe control and data exchange between these devices and ground stations. Key questions that need to be addressed when planning the deployment of aerial UEs are whether the cellular network is a suitable candidate for enabling such connectivity and how the inclusion of aerial UEs might impact the overall network efficiency. This paper provides an in-depth analysis of user and network-level performance of a cellular network that serves both unmanned aerial vehicles (UAVs) and ground users in the downlink. Our results show that the favorable propagation conditions that UAVs enjoy due to their height often backfire on them, as the increased load-dependent co-channel interference received from neighboring ground base stations (BSs) is not compensated by the improved signal strength. When compared with a ground user in an urban area, our analysis shows that a UAV flying at 100 m can experience a throughput decrease of a factor 10 and a coverage drop from 76% to 30%. Motivated by these findings, we develop UAV and network-based solutions to enable an adequate integration of UAVs into cellular networks. In particular, we show that an optimal tilting of the UAV antenna can increase the coverage from 23% to 89% and throughput from 3.5 to 5.8 b/s/Hz, outperforming ground UEs. Furthermore, our findings reveal that depending on the UAV altitude and its antenna configuration, the aerial user performance can scale with respect to the network density better than that of a ground user. Finally, our results show that network densification and the use of microcells limit the UAV performance. Although UAV usage has the potential to increase the area spectral efficiency (ASE) of cellular networks with a moderate number of cells, they might hamper the development of future ultradense networks.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Wireless communications with unmanned aerial vehicles: opportunities and challenges
Zeng, Y., Zhang, R., & Lim, T. J. (2016) · IEEE Communications Magazine · doi:10.1109/mcom.2016.7470933 · Cited by 4,048
A Tutorial on UAVs for Wireless Networks: Applications, Challenges, and Open Problems
Mozaffari, M., Saad, W., Bennis, M., Nam, Y.-H., & Debbah, M. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2902862 · Cited by 299
Cited by
Evolution of Non-Terrestrial Networks From 5G to 6G: A Survey
Azari, M. M., Solanki, S., Chatzinotas, S., Kodheli, O., Sallouha, H., Colpaert, A., Mendoza Montoya, J. F., Pollin, S., Haqiqatnejad, A., Mostaani, A., et al. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3199901 · Cited by 668
Self-citationComprehensive survey of UAVs communication networks
Hentati, A. I., & Fourati, L. C. (2020) · Computer Standards & Interfaces · doi:10.1016/j.csi.2020.103451 · Cited by 184
Metadata
- Authors
- Azari, M. M., Rosas, F., & Pollin, S.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2019-07
- Volume
- 18
- Issue
- 7
- Pages
- 3366-3381
- ISSN
- 1536-1276 (ISSN-L)
- 1558-2248
- OpenAlex
- W2798444003
- Cited by
- 197
- References
- 2
- FWCI
- 18.12
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Cellular Connectivity for UAVs: Network Modeling, Performance Analysis, and Design Guidelines. https://app.cochat.ai/papers/10.1109/twc.2019.2910112
- The paper
- Azari, M. M., Rosas, F., & Pollin, S. (2019). Cellular Connectivity for UAVs: Network Modeling, Performance Analysis, and Design Guidelines. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2019.2910112
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.