Graph neural network-based scheduling for multi-UAV-enabled communications in D2D networks

Abstract

In this paper, we jointly design the power control and position dispatch for Multi-Unmanned Aerial Vehicle (UAV)-enabled communication in Device-to-Device (D2D) networks. Our objective is to maximize the total transmission rate of Downlink Users (DUs). Meanwhile, the Quality of Service (QoS) of all D2D users must be satisfied. We comprehensively considered the interference among D2D communications and downlink trans- missions. The original problem is strongly non-convex, which requires high computational complexity for traditional optimization methods. And to make matters worse, the results are not necessarily globally optimal. In this paper, we propose a novel Graph Neural Networks (GNN) based approach that can map the considered system into a specific graph structure and achieve the optimal solution in a low complexity manner. Particularly, we first construct a GNN-based model for the proposed network, in which the transmission links and interference links are formulated as vertexes and edges, respectively. Then, by taking the channel state information and the coordinates of ground users as the inputs, as well as the location of UAVs and the transmission power of all transmitters as outputs, we obtain the mapping from inputs to outputs through training the parameters of GNN. Simulation results verified that the way to maximize the total transmission rate of DUs can be extracted effectively via the training on samples. Moreover, it also shows that the performance of proposed GNN-based method is better than that of traditional means.

Keywords

Unmanned aerial vehicle / D2D communication / Graph neural network / Power control / Position planning

References

[1] Y. Zeng, R. Zhang, T.J. Lim, Wireless communications with unmanned aerial vehicles: opportunities and challenges, IEEE Commun. Mag. 54 (5) (2016) 36-42.

[2] M. Chen, X. Wei, J. Chen, L. Wang, L. Zhou, Integration and provision for city public service in smart city cloud union: architecture and analysis, IEEE Wireless Commun. 27 (2) (2020) 148-154.

[3] B. Liu, Y. Wan, F. Zhou, Q. Wu, R.Q. Hu, Robust trajectory and beamforming design for cognitive miso uav networks, IEEE.Wireless.Commun. Lett. 10 (2) (2021) 396-400.

[4] Q. Wu, F. Shen, Z. Wang, G. Ding, 3d spectrum mapping based on roi-driven uav deployment, IEEE Network 34 (5) (2020) 24-31.

[5] F. Zhou, Y. Wu, R.Q. Hu, Y. Qian, Computation rate maximization in uav-enabled wireless-powered mobile-edge computing systems, IEEE J. Sel. Area. Commun. 36 (9) (2018) 1927-1941.

[6] X. Guan, Y. Huang, C. Dong, Q. Wu, User association and power allocation for uav- assisted networks: a distributed reinforcement learning approach, China Communications 17 (12) (2020) 110-122.

[7] Y. Zeng, R. Zhang, Energy-efficient uav communication with trajectory optimization, IEEE Trans. Wireless Commun. 16 (6) (2017) 3747-3760.

[8] S. U Rahman, G.-H. Kim, Y.-Z. Cho, A. Khan, Positioning of uavs for throughput maximization in software-defined disaster area uav communication networks, J. Commun. Network. 20 (5) (2018) 452-463.

[9] A. Asadi, Q. Wang, V. Mancuso, A survey on device-to-device communication in cellular networks, IEEE.Commun. Surv. Tutorials 16 (4) (2014) 1801-1819.

[10] H. Wang, J. Chen, G. Ding, S. Wang, D2d communications underlaying uav-assisted access networks, IEEE Access 6 (2018) 46244-46255.

[11] J. Ji, K. Zhu, D. Niyato, R. Wang, Joint trajectory design and resource allocation for secure transmission in cache-enabled uav-relaying networks with d2d communications, IEEE Internet Things J. 8 (3) (2021) 1557-1571.

[12] B. Wang, R. Zhang, C. Chen, X. Cheng, L. Yang, H. Li, Y. Jin, Graph-based file dispatching protocol with d2d-enhanced uav-noma communications in large-scale networks, IEEE Internet Things J. 7 (9) (2020) 8615-8630.

[13] J. Miao, Q. Liao, Z. Zhao, Joint rate and coverage design for uav-enabled wireless networks with underlaid d2d communications, in: 2020 IEEE 6th International Conference on Computer and Communications, ICCC, 2020, pp. 815-819.

[14] T. Fang, D. Wu, M. Wang, J. Chen,Multi-stage hierarchical channel allocation in uav-assisted d2d networks: a stackelberg game approach, China Communications 18 (2) (2021) 13-26.

[15] K.K. Nguyen, N.A. Vien, L.D. Nguyen, M.-T. Le, L. Hanzo, T.Q. Duong, Real-time energy harvesting aided scheduling in uav-assisted d2d networks relying on deep reinforcement learning, IEEE Access 9 (2021) 3638-3648.

[16] W. Wu, F. Zhou, R.Q. Hu, B. Wang, Energy-efficient resource allocation for secure noma-enabled mobile edge computing networks, IEEE Trans. Commun. 68 (1) (2020) 493-505.

[17] M. Chen, L. Wang, J. Chen, X. Wei, L. Lei, A computing and content delivery network in the smart city: scenario, framework, and analysis, IEEE Network 33 (2) (2019) 89-95.

[18] Y. Bengio, A. Courville, P. Vincent, Representation learning: a review and new perspectives, IEEE Trans. Pattern Anal. Mach. Intell. 35 (8) (2013) 1798-1828.

[19] Y. Zhou, F. Zhou, Y. Wu, R.Q. Hu, Y. Wang, Subcarrier assignment schemes based on q-learning in wideband cognitive radio networks, IEEE Trans. Veh. Technol. 69 (1) (2020) 1168-1172.

[20] Y. Shen, Y. Shi, J. Zhang, K.B. Letaief, Graph neural networks for scalable radio resource management: architecture design and theoretical analysis, IEEE J. Sel. Area. Commun. 39 (1) (2021) 101-115.

[21] T. Jiang, H.V. Cheng, W. Yu, Learning to reflect and to beamform for intelligent reflecting surface with implicit channel estimation, IEEE J. Sel. Area. Commun. 39 (7) (2021) 1931-1945.

[22] M. Lee, G. Yu, G.Y. Li, Graph embedding-based wireless link scheduling with few training samples, IEEE Trans. Wireless Commun. 20 (4) (2021) 2282-2294.

[23] W. Wang, X. Li, R. Wang, K. Cumanan, W. Feng, Z. Ding, O.A. Dobre, Robust 3d- trajectory and time switching optimization for dual-uav-enabled secure communications, IEEE J. Sel. Area. Commun. 39 (11) (2021) 3334-3347.

[24] Z. Wang, F. Zhou, Y. Wang, Q. Wu, Joint 3d trajectory and resource optimization for a uav relay-assisted cognitive radio network, China Communications 18 (6) (2021) 184-200.

[25] D. Kingma, J. Ba, Adam, A Method for Stochastic Optimization, 2014.