TY - GEN
T1 - Max-Min Fair 3D Trajectory Planning for Solar-Powered UAV-Assisted Data Collection
AU - Sun, Chao
AU - Xiong, Xinxuan
AU - Ni, Wei
AU - Ohtsuki, Tomoaki
AU - Wang, Xin
N1 - Funding Information:
Work in this paper was supported by the National Natural Science Foundation of China Grant No. 62071126 and the Innovation Program of Shanghai Municipal Science and Technology Commission Grant 2OJC1416400.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - This paper presents a new solar-powered fixed-wing unmanned aerial vehicle (UAV)-assisted data collection technique, where a fixed-wing UAV harvests solar energy to fly and collect data from smart devices (SDs). The minimum of the data upload-ed from any of the SDs is maximized by optimizing the UAV's three-dimensional (3D) trajectory. The key idea is that we develop variable substitution and successive convex approximation (SCA) techniques to convexify the nonconvex data transmission, UAV energy consumption and mobility constraints, as well as the nonconvex energy harvesting constraint. The proposed algorithm guarantees a locally optimal solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Another important aspect is that an effective set of approximation parameters are identified for accurate approximation of the solar energy harvesting at relatively low altitudes, contributing to the design of efficient 3D trajectories balancing energy harvesting and data collection. Numerical results show that the 3D flight increases uploaded data by 59% as compared to the two-dimensional (2D) flight.
AB - This paper presents a new solar-powered fixed-wing unmanned aerial vehicle (UAV)-assisted data collection technique, where a fixed-wing UAV harvests solar energy to fly and collect data from smart devices (SDs). The minimum of the data upload-ed from any of the SDs is maximized by optimizing the UAV's three-dimensional (3D) trajectory. The key idea is that we develop variable substitution and successive convex approximation (SCA) techniques to convexify the nonconvex data transmission, UAV energy consumption and mobility constraints, as well as the nonconvex energy harvesting constraint. The proposed algorithm guarantees a locally optimal solution satisfying the Karush-Kuhn-Tucker (KKT) conditions. Another important aspect is that an effective set of approximation parameters are identified for accurate approximation of the solar energy harvesting at relatively low altitudes, contributing to the design of efficient 3D trajectories balancing energy harvesting and data collection. Numerical results show that the 3D flight increases uploaded data by 59% as compared to the two-dimensional (2D) flight.
KW - 3D trajectory
KW - Unmanned aerial vehicle
KW - data collection
KW - solar energy harvesting
UR - http://www.scopus.com/inward/record.url?scp=85139473712&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139473712&partnerID=8YFLogxK
U2 - 10.1109/ICCC55456.2022.9880619
DO - 10.1109/ICCC55456.2022.9880619
M3 - Conference contribution
AN - SCOPUS:85139473712
T3 - 2022 IEEE/CIC International Conference on Communications in China, ICCC 2022
SP - 610
EP - 615
BT - 2022 IEEE/CIC International Conference on Communications in China, ICCC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE/CIC International Conference on Communications in China, ICCC 2022
Y2 - 11 August 2022 through 13 August 2022
ER -
