TY - JOUR
T1 - Computer Vision-Aided mmWave UAV Communication Systems
AU - Hua, Zizheng
AU - Lu, Yang
AU - Pan, Gaofeng
AU - Gao, Kun
AU - Costa, Daniel Benevides Da
AU - Chen, Su
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2023/7/15
Y1 - 2023/7/15
N2 - Unmanned aerial vehicle (UAV) communication systems usually operate in harsh scenarios, which require accurate information about the topology and wireless channel to achieve the desired transmission performance. Therefore, when millimeter-wave (mmWave) communication with its intrinsic Line-of-Sight (LoS) condition is adopted, accurate target localization is essential to determine the spatial relationship between the UAV and the grounded receivers (Rxs). In this article, a computer-vision (CV)-aided jointly optimization scheme of flight trajectory and power allocation is designed for mmWave UAV communication systems by utilizing the visual information captured via cameras equipped at the UAV. Compared with traditional schemes, the implementation cost and overhead can be greatly saved as no radio frequency transmissions are required in the proposed localization scheme. In addition, the transmit power at the UAV is jointly optimized with its flight trajectory in two different cases. Finally, simulation results are presented to demonstrate the efficiency of the proposed schemes.
AB - Unmanned aerial vehicle (UAV) communication systems usually operate in harsh scenarios, which require accurate information about the topology and wireless channel to achieve the desired transmission performance. Therefore, when millimeter-wave (mmWave) communication with its intrinsic Line-of-Sight (LoS) condition is adopted, accurate target localization is essential to determine the spatial relationship between the UAV and the grounded receivers (Rxs). In this article, a computer-vision (CV)-aided jointly optimization scheme of flight trajectory and power allocation is designed for mmWave UAV communication systems by utilizing the visual information captured via cameras equipped at the UAV. Compared with traditional schemes, the implementation cost and overhead can be greatly saved as no radio frequency transmissions are required in the proposed localization scheme. In addition, the transmit power at the UAV is jointly optimized with its flight trajectory in two different cases. Finally, simulation results are presented to demonstrate the efficiency of the proposed schemes.
KW - Computer vision
KW - deep learning
KW - energy efficiency
KW - trajectory optimization
KW - unmanned aerial vehicle (UAV) communication
UR - http://www.scopus.com/inward/record.url?scp=85149395233&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2023.3251377
DO - 10.1109/JIOT.2023.3251377
M3 - Article
AN - SCOPUS:85149395233
SN - 2327-4662
VL - 10
SP - 12548
EP - 12561
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 14
ER -