The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Joint Trajectory and Communication Design for Multi-UAV Enabled Wireless Networks
Open accessAbstract
Due to the high maneuverability, flexible deployment, and low cost, unmanned aerial vehicles (UAVs) have attracted significant interest recently in assisting wireless communication. This paper considers a multi-UAV enabled wireless communication system, where multiple UAV-mounted aerial base stations are employed to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users in the downlink communication by optimizing the multiuser communication scheduling and association jointly with the UAV's trajectory and power control. The formulated problem is a mixed integer nonconvex optimization problem that is challenging to solve. As such, we propose an efficient iterative algorithm for solving it by applying the block coordinate descent and successive convex optimization techniques. Specifically, the user scheduling and association, UAV trajectory, and transmit power are alternately optimized in each iteration. In particular, for the nonconvex UAV trajectory and transmit power optimization problems, two approximate convex optimization problems are solved, respectively. We further show that the proposed algorithm is guaranteed to converge. To speed up the algorithm convergence and achieve good throughput, a low-complexity and systematic initialization scheme is also proposed for the UAV trajectory design based on the simple circular trajectory and the circle packing scheme. Extensive simulation results are provided to demonstrate the significant throughput gains of the proposed design as compared to other benchmark schemes.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
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
Self-citationHandbook of Unmanned Aerial Vehicles
(2015) · doi:10.1007/978-90-481-9707-1 · Cited by 1,103
Cited by
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985
“These papers consider scheduling a drone’s communication with ground mobile devices [159] and optimizing the trajectory of the drone [297, 298].”
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
Self-citationUAV Trajectory Optimization for Data Offloading at the Edge of Multiple Cells
Cheng, F., Zhang, S., Li, Z., Chen, Y., Zhao, N., Yu, F. R., & Leung, V. C. M. (2018) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2018.2811942 · Cited by 350
Airborne Communication Networks: A Survey
Cao, X., Yang, P., Alzenad, M., Xi, X., Wu, D., & Yanikomeroglu, H. (2018) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2018.2864423 · Cited by 331
Metadata
- Authors
- Wu, Q., Zeng, Y., & Zhang, R.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2018-03
- Volume
- 17
- Issue
- 3
- Pages
- 2109-2121
- ISSN
- 1536-1276 (ISSN-L)
- OpenAlex
- W2963061782
- Cited by
- 1,978
- References
- 3
- FWCI
- 189.78
- Type
- journal article
- Language
- en
- Open access
- green
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