Joint Channel Access and Power Control Optimization in Large-Scale UAV Networks: A Hierarchical Mean Field Game Approach

Chen, Runfeng; Chen, Jin; Wang, Haichao; Tong, Xiaobing; Xu, Yifan; Qi, Nan; Xu, Yuhua

doi:10.1109/tvt.2022.3210287

Cited by 5 publications

(2 citation statements)

References 43 publications

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“…The parameters of environment are set as follows: the power spectral density of background noise is -149/dBm/Hz, normalization factor of Rayleigh distribution is 20 and normalization factor of Rice distribution is 1. For comparison, we introduce a hierarchical mean field game approach (HMFGA) [11] as a baseline. Figure 4.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…A resource allocation algorithm is studied based on smoothing and alternating optimization [10]. While the channel access game is combined with the multiple mean fields game and a hierarchical mean field game approach is formulated to jointly optimize spectrum resource [11]. A deep learning algorithm is discussed to formulate the topology of UAVs and transmit power for multiple channels [12].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Knowledge graph completion assisted graph neural network for spectrum resource optimization of UAV swarm

Wang,

Liao,

et al. 2024

J. Phys.: Conf. Ser.

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Unmanned aerial vehicles (UAVs) are playing an increasing critical role in industrial, agricultural and military Scenario. However, the energy consuming cannot be ignored, which constrains the flying time and quality of service (QoS), especially in large UAV swarm. In this paper, a knowledge graph completion assisted graph neural network (KGC-GNN) is proposed for UAV swarm aiming at optimizing the spectrum resource to improve the energy efficiency (EE). The proposed network consists of two parts: a graph attention network based on relational coding (GATRC) encoder and a task-oriented decoder based on InteractE model named CP-IE. The further simulation demonstrates that our approach can attain near-optimal spectrum resource optimization scheme with higher energy efficiency and achieve rapid convergence with the channel distribution information (CDI), UAV and environment parameters.

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Section: Simulation Resultsmentioning

confidence: 99%