The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications
Open accessAbstract
In this paper, the efficient deployment and mobility of multiple unmanned aerial vehicles (UAVs), used as aerial base stations to collect data from ground Internet of Things (IoT) devices, are investigated. In particular, to enable reliable uplink communications for the IoT devices with a minimum total transmit power, a novel framework is proposed for jointly optimizing the 3D placement and the mobility of the UAVs, device-UAV association, and uplink power control. First, given the locations of active IoT devices at each time instant, the optimal UAVs' locations and associations are determined. Next, to dynamically serve the IoT devices in a time-varying network, the optimal mobility patterns of the UAVs are analyzed. To this end, based on the activation process of the IoT devices, the time instances at which the UAVs must update their locations are derived. Moreover, the optimal 3D trajectory of each UAV is obtained in a way that the total energy used for the mobility of the UAVs is minimized while serving the IoT devices. Simulation results show that, using the proposed approach, the total-transmit power of the IoT devices is reduced by 45% compared with a case, in which stationary aerial base stations are deployed. In addition, the proposed approach can yield a maximum of 28% enhanced system reliability compared with the stationary case. The results also reveal an inherent tradeoff between the number of update times, the mobility of the UAVs, and the transmit power of the IoT devices. In essence, a higher number of updates can lead to lower transmit powers for the IoT devices at the cost of an increased mobility for the UAVs.
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
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
The Hungarian method for the assignment problem
Kuhn, H. W. (1955) · Naval Research Logistics Quarterly · doi:10.1002/nav.3800020109 · Cited by 13,120
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
Sequential quadratic programming
Boggs, P. T., & Tolle, J. W. (1995) · Acta Numerica · doi:10.1017/s0962492900002518 · Cited by 1,858
Chen, M., Mozaffari, M., Saad, W., Yin, C., Debbah, M., & Hong, C. S. (2017) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2017.2680898 · Cited by 742
Self-citation
Cited by
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
Energy Efficient Federated Learning Over Wireless Communication Networks
Yang, Z., Chen, M., Saad, W., Hong, C. S., & Shikh-Bahaei, M. (2021) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2020.3037554 · Cited by 1,153
Self-citationOtto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985
“[181] M, P, LR, H, Exp several drones communication constraints (eg, probability of successful transmission depends on distance, limited communication range), energy consumption function (limited energy, energy consumption depends on velocity vector) telecommunications”
BackgroundDistributed Federated Learning for Ultra-Reliable Low-Latency Vehicular Communications
Samarakoon, S., Bennis, M., Saad, W., & Debbah, M. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2019.2956472 · Cited by 459
Self-citationUltra Reliable UAV Communication Using Altitude and Cooperation Diversity
Azari, M. M., Rosas, F., Chen, K.-C., & Pollin, S. (2018) · IEEE Transactions on Communications · doi:10.1109/tcomm.2017.2746105 · Cited by 448
Metadata
- Authors
- Mozaffari, M., Saad, W., Bennis, M., & Debbah, M.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2017-11
- Volume
- 16
- Issue
- 11
- Pages
- 7574-7589
- ISSN
- 1536-1276 (ISSN-L)
- OpenAlex
- W2604830243
- Cited by
- 1,093
- References
- 5
- FWCI
- 106.73
- 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: Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications. https://app.cochat.ai/papers/10.1109/twc.2017.2751045
- The paper
- Mozaffari, M., Saad, W., Bennis, M., & Debbah, M. (2017). Mobile Unmanned Aerial Vehicles (UAVs) for Energy-Efficient Internet of Things Communications. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2017.2751045
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.