The DOI matches its Crossref record.
Efficient 3-D placement of an aerial base station in next generation cellular networks
Abstract
Agility and resilience requirements of future cellular networks may not be fully satisfied by terrestrial base stations in cases of unexpected or temporary events. A promising solution is assisting the cellular network via low-altitude unmanned aerial vehicles equipped with base stations, i.e., drone-cells. Although drone-cells provide a quick deployment opportunity as aerial base stations, efficient placement becomes one of the key issues. In addition to mobility of the drone-cells in the vertical dimension as well as the horizontal dimension, the differences between the air-to-ground and terrestrial channels cause the placement of the drone-cells to diverge from placement of terrestrial base stations. In this paper, we first highlight the properties of the drone-cell placement problem, and formulate it as a 3-D placement problem with the objective of maximizing the revenue of the network. After some mathematical manipulations, we formulate an equivalent quadratically-constrained mixed integer non-linear optimization problem and propose a computationally efficient numerical solution for this problem. We verify our analytical derivations with numerical simulations and enrich them with discussions which could serve as guidelines for researchers, mobile network operators, and policy makers.
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
Cited by
Unmanned Aerial Vehicles (UAVs): A Survey on Civil Applications and Key Research Challenges
Shakhatreh, H., Sawalmeh, A. H., Al-Fuqaha, A., Dou, Z., Almaita, E., Khalil, I., Othman, N. S., Khreishah, A., & Guizani, M. (2019) · IEEE Access · doi:10.1109/access.2019.2909530 · Cited by 2,529
UAV Communications for 5G and Beyond: Recent Advances and Future Trends
Li, B., Fei, Z., & Zhang, Y. (2019) · IEEE Internet of Things Journal · doi:10.1109/jiot.2018.2887086 · Cited by 1,377
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985
“[32] M, E, Exp several drones communication constraints (eg, limited communication range, threshold for the signal-to-noise ratio, given transmission power, altitude-dependent probability of line-of-sight communication) telecommunications”
BackgroundOptimal 3D-Trajectory Design and Resource Allocation for Solar-Powered UAV Communication Systems
Sun, Y., Xu, D., Ng, D. W. K., Dai, L., & Schober, R. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2900630 · Cited by 452
Cellular-Enabled UAV Communication: A Connectivity-Constrained Trajectory Optimization Perspective
Zhang, S., Zeng, Y., & Zhang, R. (2019) · IEEE Transactions on Communications · doi:10.1109/tcomm.2018.2880468 · Cited by 426
Metadata
- Authors
- Bor-Yaliniz, R. I., El-Keyi, A., & Yanikomeroglu, H.
- Venue
- 2016 IEEE International Conference on Communications (ICC)
- Publisher
- IEEE
- Published
- 2016-05
- Pages
- 1-5
- ISSN
- 1550-3607 (ISSN-L)
- OpenAlex
- W2289204537
- Cited by
- 893
- References
- 0
- FWCI
- 211.74
- Type
- conference paper
- Language
- en
- Open access
- closed
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: Efficient 3-D placement of an aerial base station in next generation cellular networks. https://app.cochat.ai/papers/10.1109/icc.2016.7510820
- The paper
- Bor-Yaliniz, R. I., El-Keyi, A., & Yanikomeroglu, H. (2016). Efficient 3-D placement of an aerial base station in next generation cellular networks. 2016 IEEE International Conference on Communications (ICC). https://doi.org/10.1109/icc.2016.7510820
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.