TY - JOUR
T1 - Budget-Constrained MAB for Trajectory Planning in Aerial-Aided Emergency Networks
AU - Hosny, Ramez
AU - Hashima, Sherief
AU - Hatano, Kohei
AU - Mohamed, Ehab Mahmoud
AU - ElHalawany, Basem M.
N1 - Publisher Copyright:
Copyright © 2023 Ramez Hosny et al.
PY - 2023
Y1 - 2023
N2 - In this paper, we introduce a trajectory planning algorithm (TPA) in aerial/unmanned aerial vehicle- (UAV-) aided communications using a practical budget-constrained multiarmed bandit (BC-MAB) in disaster regions. Hence, we propose two cost-efficient TPAs based on two variants of the upper confidence bound (UCB) algorithms, namely, UCB-BC1 and UCB-BC2, via orthogonal multiple access (OMA) transmission. The former assumes prior information about the minimum expected costs, while the latter estimates the minimum costs from empirical observations. Simulation results confirm that the proposed algorithms outperform other benchmark schemes in terms of the total number of assisted survivors, battery consumption, and convergence speed.
AB - In this paper, we introduce a trajectory planning algorithm (TPA) in aerial/unmanned aerial vehicle- (UAV-) aided communications using a practical budget-constrained multiarmed bandit (BC-MAB) in disaster regions. Hence, we propose two cost-efficient TPAs based on two variants of the upper confidence bound (UCB) algorithms, namely, UCB-BC1 and UCB-BC2, via orthogonal multiple access (OMA) transmission. The former assumes prior information about the minimum expected costs, while the latter estimates the minimum costs from empirical observations. Simulation results confirm that the proposed algorithms outperform other benchmark schemes in terms of the total number of assisted survivors, battery consumption, and convergence speed.
UR - http://www.scopus.com/inward/record.url?scp=85149103207&partnerID=8YFLogxK
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U2 - 10.1155/2023/5209054
DO - 10.1155/2023/5209054
M3 - Article
AN - SCOPUS:85149103207
SN - 1530-8669
VL - 2023
JO - Wireless Communications and Mobile Computing
JF - Wireless Communications and Mobile Computing
M1 - 5209054
ER -