Joint trajectory and CoMP clustering optimization in UAV-assisted cellular systems: a coalition formation game approach

被引:0
作者
Mostafa M. Abdelhakam
Mahmoud M. Elmesalawy
Ibrahim I. Ibrahim
Samir G. Sayed
机构
[1] Helwan University,Department of Electronics and Communications Engineering, Faculty of Engineering
来源
EURASIP Journal on Wireless Communications and Networking | / 2023卷
关键词
Unmanned aerial vehicles (UAVs); Coordinated multi-point (CoMP); Game theory; Coalitional games; Trajectory optimization;
D O I
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中图分类号
学科分类号
摘要
In this paper, the flexibility of unmanned aerial vehicles (UAVs), as well as the benefits of coordinated multi-point (CoMP) transmission, are utilized for mitigating the interference in cellular networks. Specifically, the joint problem of CoMP clusters and UAVs’ trajectories is addressed for downlink transmission in a UAV-assisted cellular system. The problem is presented as a non-convex optimization problem that aims to maximize the sum rate of the ground users by taking into account the clustering, UAV mobility and backhaul capacity constraints. Since the formulated problem is known to be NP-hard, we partition it into two sub-problems. Particularly, by using coalitional game theory, the CoMP clusters are obtained with a given UAVs’ trajectories. Then, UAVs’ trajectories are optimized with given CoMP clusters using successive convex approximation technique. Based on the block coordinate descent method, the two sub-problems are solved alternatively until convergence. Numerical results are conducted and demonstrated the effectiveness of the proposed algorithm.
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共 94 条
[1]  
Abrar M(2021)Energy efficient UAV-enabled mobile edge computing for IoT devices: a review IEEE Access 9 127779-127798
[2]  
Ajmal U(2021)Joint beamforming coordination and user selection for CoMP enabled NR-U networks IEEE Internet Things J. 9 14530-14541
[3]  
Almohaimeed ZM(2018)A cooperation strategy based on bargaining game for fair user-centric clustering in cloud-RAN IEEE Commun. Lett. 22 1454-1457
[4]  
Gui X(2021)Multi-UAV trajectory optimization considering collisions in FSO communication networks IEEE J. Sel. Areas Commun. 39 3378-3394
[5]  
Akram R(2021)Trajectory optimization and resource allocation for OFDMA UAV relay networks IEEE Trans. Wirel. Commun. 20 6634-6647
[6]  
Masroor R(2022)Cooperative UAV enabled relaying systems: joint trajectory and transmit power optimization IEEE Trans. Green Commun. Netw. 6 543-557
[7]  
Chen Q(2021)Joint resource allocation and trajectory optimization with QoS in UAV-based NOMA wireless networks IEEE Trans. Wirel. Commun. 20 6343-6355
[8]  
Yang K(2022)Minimizing mission completion time of UAVs by jointly optimizing the flight and data collection trajectory in UAV-enabled WSNs IEEE Internet Things J. 15 13498-3394
[9]  
Jiang H(2022)Deep reinforcement learning approach for joint trajectory design in multi-UAV IoT networks IEEE Trans. Veh. Technol. 71 3389-15366
[10]  
Qiu M(2022)Joint communication and trajectory optimization for multi-UAV enabled mobile internet of vehicles IEEE Trans. Intell. Transp. Syst. 23 15354-2371