Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/160310
Title: | When UAV meets IRS: expanding air-ground networks via passive reflection | Authors: | Pang, Xiaowei Sheng, Min Zhao, Nan Tang, Jie Niyato, Dusit Wong, Kai-Kit |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2021 | Source: | Pang, X., Sheng, M., Zhao, N., Tang, J., Niyato, D. & Wong, K. (2021). When UAV meets IRS: expanding air-ground networks via passive reflection. IEEE Wireless Communications, 28(5), 164-170. https://dx.doi.org/10.1109/MWC.010.2000528 | Journal: | IEEE Wireless Communications | Abstract: | Thanks to their flexibility and mobility, unmanned aerial vehicles (UAVs) have been widely applied in wireless networks. However, UAV communications may suffer from blockage and eavesdropping in practical scenarios due to the complex environment. Taking the recent advances in intelligent reflecting surface (IRS) to reconfigure the propagation environments, in this article, we employ IRS to enhance the performance of UAV-aided air-ground networks. First, we overview the combination of UAV and IRS, by introducing the diverse applications of IRS and the appealing advantages of UAV, and highlighting the benefits of combining them. Then, we investigate two case studies where the UAV trajectory, the transmit beamforming and the IRS passive beamforming are jointly optimized. In the first case study, by equipping the IRS on a UAV, the average achievable rate of the relaying network is maximized. In the second one, the IRS is deployed to assist the UAV-ground communication while combating the adversarial eavesdropper. Simulation results are provided to demonstrate the performance enhancement resulting from combining UAV and IRS in air-ground networks. Finally, we shed light on some challenging issues to be resolved for practical implementations in this direction. | URI: | https://hdl.handle.net/10356/160310 | ISSN: | 1536-1284 | DOI: | 10.1109/MWC.010.2000528 | Schools: | School of Computer Science and Engineering | Rights: | © 2021 IEEE. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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