An optimal location strategy for multiple drone base stations in massive MIMO

ICT Express - Tập 8 - Trang 230-234 - 2022
Manuel Eugenio Morocho-Cayamcela1, Wansu Lim2, Martin Maier3
1Yachay Tech University, School of Mathematical and Computational Sciences, Deep Learning for Autonomous Driving, Robotics, and Computer Vision Research Group (DeepARC), Hacienda San José, San Miguel de Urcuquí, Ecuador
2Department of Aeronautics, Mechanical and Electronic Convergence Engineering, Kumoh National Institute of Technology, Gumi, Gyeongsangbuk-do 39177, South Korea
3Optical Zeitgeist Laboratory, INRS, Montreal QC, H5A 1K6, Canada

Tài liệu tham khảo

Fotouhi, 2019, Survey on uav cellular communications: Practical aspects, standardization advancements, regulation, and security challenges, IEEE Commun. Surv. Tutor., 21, 3417, 10.1109/COMST.2019.2906228 Aggarwal, 2020, 270 Hanly, 1995, An algorithm for combined cell-site selection and power control to maximize cellular spread spectrum capacity, IEEE J. Sel. Areas Commun., 13, 1332, 10.1109/49.414650 Lin, 2015, Optimizing user association and spectrum allocation in hetnets: A utility perspective, IEEE J. Sel. Areas Commun., 33, 1025, 10.1109/JSAC.2015.2417011 J. Chen, D. Raye, W. Khawaja, P. Sinha, I. Guvenc, Impact of 3d uwb antenna radiation pattern on air-to-ground drone connectivity, in: 2018 IEEE 88th Vehicular Technology Conference, VTC-Fall, 2018, pp. 1–5. Matolak, 2017, Air–ground channel characterization for unmanned aircraft systems—part i: Methods, measurements, and models for over-water settings, IEEE Trans. Veh. Technol., 66, 26, 10.1109/TVT.2016.2530306 H.C. Nguyen, R. Amorim, J. Wigard, I.Z. Kovacs, P. Mogensen, Using lte networks for uav command and control link: A rural-area coverage analysis, in: 2017 IEEE 86th Vehicular Technology Conference, VTC-Fall, 2017, pp. 1–6. Cicek, 2019, The location–allocation problem of drone base stations, Comput. Oper. Res., 111, 155, 10.1016/j.cor.2019.06.010 Liang, 2016, A cluster-based energy-efficient resource management scheme for ultra-dense networks, IEEE Access, 4, 6823, 10.1109/ACCESS.2016.2614517 J. Sun, C. Masouros, Drone positioning for user coverage maximization, in: 2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, 2018, pp. 318–322. Wang, 2020, An integrated affinity propagation and machine learning approach for interference management in drone base stations, IEEE Trans. Cogn. Commun. Netw., 6, 83, 10.1109/TCCN.2019.2946864 El Hammouti, 2019, Learn-as-you-fly: A distributed algorithm for joint 3d placement and user association in multi-uavs networks, IEEE Trans. Wireless Commun., 18, 5831, 10.1109/TWC.2019.2939315 Wang, 2018, Energy efficient placement of a drone base station for minimum required transmit power, IEEE Wirel. Commun. Lett., 1 Marzetta, 2016 Morocho-Cayamcela, 2019, Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions, IEEE Access, 7, 137184, 10.1109/ACCESS.2019.2942390 Björnson, 2019, 1 Björnson, 2019, Massive MIMO is a reality—What is next?, Digit. Signal Process., 94, 3, 10.1016/j.dsp.2019.06.007 Morocho-Cayamcela, 2020, Breaking wireless propagation environmental uncertainty with deep learning, IEEE Transactions on Wireless Communications, 19, 5075, 10.1109/TWC.2020.2986202 Morocho-Cayamcela, 2020, Machine learning to improve multi-hop searching and extended wireless reachability in v2x, IEEE Communications Letters, 24, 1477, 10.1109/LCOMM.2020.2982887