TY - JOUR
T1 - Optimal trajectory and downlink power control for multi-type UAV aerial base stations
AU - LI, Lixin
AU - SUN, Yan
AU - CHENG, Qianqian
AU - WANG, Dawei
AU - LIN, Wensheng
AU - CHEN, Wei
N1 - Publisher Copyright:
© 2021 Chinese Society of Aeronautics and Astronautics
PY - 2021/9
Y1 - 2021/9
N2 - Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.
AB - Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.
KW - Mean-Field-Type Game (MFTG)
KW - Power control
KW - Q-learning
KW - Trajectory
KW - Unmanned Aerial Vehicle (UAV)
UR - http://www.scopus.com/inward/record.url?scp=85106312432&partnerID=8YFLogxK
U2 - 10.1016/j.cja.2020.12.019
DO - 10.1016/j.cja.2020.12.019
M3 - 文章
AN - SCOPUS:85106312432
SN - 1000-9361
VL - 34
SP - 11
EP - 23
JO - Chinese Journal of Aeronautics
JF - Chinese Journal of Aeronautics
IS - 9
ER -