Yu, Xiangbin, Huang, Xu, Wang, Kezhi, Shu, Feng and Dang, Xiaoyu (2022) Joint Design of Power Allocation, Beamforming and Positioning for Energy-Efficient UAV-Aided Multiuser Millimeter-Wave Systems. IEEE Journal on Selected Areas in Communications, 40 (10). pp. 2930-2945. ISSN 0733-8716
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Abstract
In this paper, the joint design of power allocation (PA), beamforming (BF) and positioning is studied for unmanned-aerial-vehicle (UAV) aided millimeter-Wave (UAV-mmWave) systems, with the objective of maximizing the energy efficiency (EE), under the constraints of maximum transmitting power, minimum data rate from the ground users and positioning range of the UAV. To address the above problem, we first obtain the positioning of the UAV, with the help of approximate beam pattern. Then, near-optimal BF and closed-form PA are derived given the obtained position, with the help of block coordinate descent method. To reduce the complexity, two suboptimal BF schemes with one-loop iteration and closed-form solutions are respectively derived. Furthermore, we propose the simplified algorithms for two special cases, i.e., only line-of-sight (LoS) path and Non-LoS (NLoS) path exist between the users and the UAV. Simulation results verify the effectiveness of the developed joint schemes and show the superior EE performance. Moreover, they can obtain almost the same performance as the existing benchmark schemes but with lower complexity.
| Item Type: | Article |
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| Additional Information: | Funding information: This work was supported in part the National Natural Science Foundation of China under Grant 62071234, Grant 62071229, and Grant 61972093; in part by the Hainan Province Science and Technology Special Fund under Grant DKJ2021022; in part by the Scientific Research Fund Project of Hainan University under Grant KYQD(ZR)-21008; and in part by the National Key Research and Development Program of China under Grant 2018YFB180110. |
| Subjects: | G400 Computer Science |
| Department: | Faculties > Engineering and Environment > Computer and Information Sciences |
| Depositing User: | Elena Carlaw |
| Date Deposited: | 08 Apr 2022 14:56 |
| Last Modified: | 26 Oct 2022 13:19 |
| URI: | https://nrl.northumbria.ac.uk/id/eprint/48852 |
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