Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks

Abstract

Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency. To tackle this problem, we propose an Unmanned Aerial Vehicle (UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell. To fully exploit its potential, we jointly optimize the UAV position, user association, spectrum allocation, and power allocation to maximize the sum-log-rate of all users in two adjacent cells. To tackle the complicated joint opti- mization problem, we first design a genetic-based algorithm to optimize the UAV position. Then, we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method, so as to obtain the optimal user association and spectrum allocation schemes. We further propose an iterative power allocation algorithm based on the sequential convex approximation theory. The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput, and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.

Keywords

Load balance / Unmanned aerial vehicle / User association / Resource management

References

[1] J. Navarro-Ortiz, P. Romero-Diaz, S. Sendra, P. Ameigeiras, J.J. Ramos-Munoz, J.M. Lopez-Soler, A survey on 5G usage scenarios and traffic models, IEEE Commun. Surveys Tuts. 22 (2) (2020) 905-929.

[2] J.G. Andrews, S. Singh, Q. Ye, X. Lin, H.S. Dhillon, An overview of load balancing in HetNets: old myths and open problems, IEEE Wireless Commun. 21 (2) (2014) 18-25.

[3] D. Liu, L. Wang, Y. Chen, M. Elkashlan, K.-K. Wong, R. Schober, L. Hanzo, User association in 5G networks: a survey and an outlook, IEEE Commun. Surveys Tuts. 18 (2) (2016) 1018-1044.

[4] Z.Z.P. Han, Z. Wang, User association for load balance in heterogeneous networks with limited CSI feedback, IEEE Commun. Lett. 24 (5) (2020) 1095-1099.

[5] A. Hava, Y. Ghamri-Doudane, J. Murphy, G. Muntean, A load balancing solution for improving video quality in loaded wireless network conditions, IEEE Trans. Broadcast. 65 (4) (2019) 742-754.

[6] M. O.A.R.Q. Shaddad, N.A. Alsarori, T.M. Shami, Biased user association in 5G heterogeneous networks, in: 2021 International Conference of Technology, Science and Administration (ICTSA), 2021, pp. 1-4.

[7] K.M. Addali, S.Y.B. Melhem, Y. Khamayseh, Z. Zhang, M. Kadoch, Dynamic mobility load balancing for 5G small-cell networks based on utility functions, IEEE Access 7 (2019) 126998-127011.

[8] A. Alizadeh, M. Vu, Load balancing user association in millimeter wave MIMO networks, IEEE Trans. Wireless Commun. 18 (6) (2019) 2932-2945.

[9] D. Zhai, Q. Shi, R. Zhang, X. Tang, H. Cao, Coverage maximization for heterogeneous aerial networks, IEEE Wireless Commun. Lett.doi:10.1109/LWC.2021.3121076.

[10] E.B.T. Van Chien, E.G. Larsson, Joint power allocation and load balancing optimization for energy-efficient cell-free massive MIMO networks, IEEE Trans. Wireless Commun. 19 (10) (2020) 6798-6812.

[11] H.S.S.H. Lee, M. Kim, I. Lee, Belief propagation for energy efficiency maximization in wireless heterogeneous networks, IEEE Trans. Wireless Commun. 20 (1) (2021) 56-68.

[12] H.K.S. Sobhi-Givi, M.G. Shayesteh, N. Rajatheva,Resource allocation and user association for load balancing in NOMA-Based cellular heterogeneous networks, in:2020 Iran Workshop on Communication and Information Theory (IWCIT), 2020,pp.1-6.

[13] Y. C, et al., A spectrum allocation method based on load balancing for heterogeneous networks of smart grid, in: 2020 International Wireless Communications and Mobile Computing (IWCMC), 2020, pp. 111-115.

[14] M. Javad-Kalbasi, S. Valaee,Energy and spectrum efficient user association for backhaul load balancing in small cell networks, in: GLOBECOM 2020-2020 IEEE Global Communications Conference, 2020, pp. 1-6.

[15] D.X.C. Jialing, Y. Mingxi, J. Bingli,Q -learning based selection strategies for load balance and energy balance in heterogeneous networks, in:2020 5th International Conference on Computer and Communication Systems (ICCCS), 2020, pp. 728-732.

[16] W. Teng, M. Sheng, K. Guo, Z. Qiu, Content placement and user association for delay minimization in small cell networks, IEEE Trans. Veh. Technol. 68 (10) (2019) 10201-10215.

[17] W. Khawaja, I. Guvenc, D.W. Matolak, U.-C. Fiebig, N. Schneckenburger, A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles, IEEE Commun. Surveys Tuts. 21 (3) (2019) 2361-2391.

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

[19] Y. Li, L. Cai, UAV-assisted dynamic coverage in a heterogeneous cellular system, IEEE Netw. 31 (4) (2017) 56-61.

[20] C. Lai, C. Chen, L. Wang, On-demand density-aware UAV base station 3D placement for arbitrarily distributed users with guaranteed data rates, IEEE Wireless Commun. Lett. 8 (3) (2019) 913-916.

[21] V. Saxena, J. Jaldén, H. Klessig, Optimal UAV base station trajectories using flow- level models for reinforcement learning, IEEE Trans. Cogn. Commun. Netw. 5 (4) (2019) 1101-1112.

[22] Z. Chen, H. Zhang, UAV-assisted networks through a tunable dependent model, IEEE Commun. Lett. 24 (5) (2020) 1110-1114.

[23] S. Ahmed, M.Z. Chowdhury, Y.M. Jang, Energy-efficient UAV relaying communications to serve ground nodes, IEEE Commun. Lett. 24 (4) (2020) 849-852.

[24] P.K. Sharma, D. Deepthi, D.I. Kim, Outage probability of 3-D mobile UAV relaying for hybrid satellite-terrestrial networks, IEEE Commun. Lett. 24 (2) (2020) 418-422.

[25] W. Chen, S. Zhao, R. Zhang, Y. Chen, L. Yang, UAV-assisted data collection with nonorthogonal multiple access, IEEE Internet Things J 8 (1) (2021) 501-511.

[26] M. Yi, X. Wang, J. Liu, Y. Zhang, B. Bai,Deep reinforcement learning for fresh data collection in UAV-assisted IoT networks, in: IEEE INFOCOM 2020 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), 2020, pp. 716-721.

[27] M. Monemi, H. Tabassum, Performance of UAV-assisted D2D networks in the finite block-length regime, IEEE Trans. Commun. 68 (11) (2020) 7270-7285.

[28] Y. Li, G. Feng, M. Ghasemiahmadi, L. Cai, Power allocation and 3-D placement for floating relay supporting indoor communications, IEEE Trans. Mobile Comput. 18 (3) (2019) 618-631.

[29] D. Zhai, H. Li, X. Tang, R. Zhang, Z. Ding, F.R. Yu, Height optimization and resource allocation for NOMA enhanced UAV-aided relay networks, IEEE Trans. Commun. 69 (2) (2021) 962-975.

[30] Y. Song, S.H. Lim, S.W. Jeon, S. Baek, On cooperative achievable rates of UAV assisted cellular networks, IEEE Trans. Veh. Technol. 69 (9) (2020) 9882-9895.

[31] A. Fotouhi, H. Qiang, M. Ding, M. Hassan, L.G. Giordano, A. Garcia-Rodriguez, J. Yuan, Survey on UAV cellular communications: practical aspects, standardization advancements, regulation, and security challenges, IEEE Commun. Surveys Tuts. 21 (4) (2019) 3417-3442.

[32] P. Yang, X. Xi, K. Guo, T.Q.S. Quek, J. Chen, X. Cao, Proactive uav network slicing for urllc and mobile broadband service multiplexing, IEEE J. Sel. Area. Commun. 39 (10) (2021) 3225-3244.

[33] Y. Chen, W. Feng, G. Zheng, Optimum placement of uav as relays, IEEE Commun. Lett. 22 (2) (2018) 248-251.

[34] K. Wang, R. Zhang, L. Wu, Z. Zhong, L. He, J. Liu, X. Pang, Path loss measurement and modeling for low-altitude UAV access channels, in: 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 2017, pp. 1-5.

[35] Document TR 38.901 V14.0.0: Study on Channel Model for Frequencies from 0.5 to 100 GHz (Release 14), Tech. rep., 3GPP Technical Specification Group Radio Access Network, July 2017.

[36] P. Guo, X. Wang, Y. Han, The enhanced genetic algorithms for the optimization design, in: Proc. Biomedical Engineering and Informatics Conference, vol. 7, 2010, pp. 2990-2994.

[37] C. Jiang, Y. Chen, Y. Gao, K.J. Ray Liu, Indian buffet game with negative network externality and non-bayesian social learning, IEEE Trans. Syst., Man, Cybern. Syst. 45 (4) (2015) 609-623.

[38] H. Tuy, Convex Analysis and Global Optimization, Kluwer Academic, 1998.

[39] Y. Li, M. Sheng, C. Yang, X. Wang, Energy efficiency and spectral efficiency tradeoff in interference-limited wireless networks, IEEE Commun. Lett. 17 (10) (2013) 1924-1927.

[40] Q. Ye, B. Rong, Y. Chen, M. Al-Shalash, C. Caramanis, J.G. Andrews, User association for load balancing in heterogeneous cellular networks, IEEE Trans. Wireless Commun. 12 (6) (2013) 2706-2716.

[41] S. Boyd, L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004.