[1] Zhou Y Q, Liu L, Wang L, et al.Service-aware 6G: an intelligent and open network based on the convergence of communication, computing and caching[J]. Digital Communications and Networks, 2020, 6(3): 253-260. DOI:10.1016/j.dcan.2020.05.003. [2] Zhou Y Q, Tian L, Liu L, et al.Fog computing enabled future mobile communication networks: a convergence of communication and computing[J]. IEEE Communications Magazine, 2019, 57(5): 20-27. DOI: 10.1109/MCOM.2019.1800235. [3] Sun J C, Masouros C.Deployment strategies of multiple aerial BSs for user coverage and power efficiency maximization[J]. IEEE Transactions on Communications, 2018, 67(4): 2981-2994. DOI:10.1109/TCOMM.2018.2889460. [4] Khuwaja A A, Zheng G, Chen Y F, et al.Optimum deployment of multiple UAVs for coverage area maximization in the presence of co-channel interference[J]. IEEE Access, 2019, 7: 85203-85212. DOI:10.1109/ACCESS.2019.2924720. [5] Liu Y, Yan J J, Zhao X H.Deep reinforcement learning based latency minimization for mobile edge computing with virtualization in maritime UAV communication network[J]. IEEE Transactions on Vehicular Technology, 2022, 71(4): 4225-4236. DOI:10.1109/TVT.2022.3141799. [6] Letaief K B, Shi Y M, Lu J M, et al.Edge artificial intelligence for 6G: vision, enabling technologies, and applications[J]. IEEE Journal on Selected Areas in Communications, 2021, 40(1): 5-36. DOI:10.1109/JSAC.2021.3126076. [7] Lee G, Saad W, Bennis M.Online optimization for UAV-assisted distributed fog computing in smart factories of industry 4.0[C]//2018 IEEE Global Communications Conference (GLOBECOM). December 9-13, 2018, Abu Dhabi, United Arab Emirates. IEEE, 2019: 1-6. DOI: 10.1109/GLOCOM.2018.8647441. [8] Hsu Y H, Gau R H.Reinforcement learning-based collision avoidance and optimal trajectory planning in UAV communication networks[J]. IEEE Transactions on Mobile Computing, 2022, 21(1): 306-320. DOI: 10.1109/TMC.2020.3003639. [9] Brik B, Ksentini A, Bouaziz M.Federated learning for UAVs-enabled wireless networks: use cases, challenges, and open problems[J]. IEEE Access, 2020, 8: 53841-53849. DOI:10.1109/ACCESS.2020.2981430. [10] Wiering M, van Otterlo M. Reinforcement learning: state-of-the-art[J]. Adaptation, Learning, and Optimization, 2012, 12: 1-653. [11] Mozaffari M, Saad W, Bennis M, et al.A tutorial on UAVs for wireless networks: applications, challenges, and open problems[J]. IEEE Communications Surveys & Tutorials, 2019, 21(3): 2334-2360. DOI: 10.1109/COMST.2019.2902862. [12] Cheng X, Yu B, Yang L Q, et al.Communicating in the real world: 3D MIMO[J]. IEEE Wireless Communications, 2014, 21(4): 136-144. DOI:10.1109/MWC.2014.6882306. [13] Chandhar P, Danev D, Larsson E G.Massive MIMO for communications with drone swarms[J]. IEEE Transactions on Wireless Communications, 2018, 17(3): 1604-1629. DOI:10.1109/TWC.2017.2782690. [14] Zhou Y F, Zhou H L, Zhou F H, et al.Robust chance-constrained trajectory and transmit power optimization for UAV-enabled CR networks[C]//ICC 2020-2020 IEEE International Conference on Communications (ICC). June 7-11, 2020, Dublin, Ireland. IEEE, 2020: 1-7. DOI:10.1109/ICC40277.2020.9148733. [15] Xu Y J, Liu Z J, Huang C W, et al.Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks[J]. IEEE Internet of Things Journal, 2021, 8(23): 17161-17171. DOI:10.1109/JIOT.2021.3078264. [16] Bouadi H, Bouchoucha M, Tadjine M.Modelling and stabilizing control laws design based on backstepping for an UAV type-quadrotor[J]. IFAC Proceedings Volumes, 2007, 40(15): 245-250. DOI:10.3182/20070903-3-FR-2921.00043. [17] Li B, Li Q L, Zeng Y, et al.3D trajectory optimization for energy-efficient UAV communication: a control design perspective[J]. IEEE Transactions on Wireless Communications, 2022, 21(6): 4579-4593. DOI:10.1109/TWC.2021.3131384. [18] Mofid O, Mobayen S.Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties[J]. ISA Transactions, 2018, 72: 1-14. DOI:10.1016/j.isatra.2017.11.010. [19] Ogata K.Modern control engineering[M]. 5th ed. Boston: Prentice Hall, 2010. [20] Shi D J, Dai X H, Zhang X W, et al.A practical performance evaluation method for electric multicopters[J]. IEEE/ASME Transactions on Mechatronics, 2017, 22(3): 1337-1348. DOI:10.1109/TMECH.2017.2675913. [21] Lin X Q, Yajnanarayana V, Muruganathan S D, et al.The sky is not the limit: LTE for unmanned aerial vehicles[J]. IEEE Communications Magazine, 2018, 56(4): 204-210. DOI: 10.1109/MCOM.2018.1700643. [22] Zhao J W, Gao F F, Wu Q H, et al.Beam tracking for UAV mounted SatCom on-the-move with massive antenna array[J]. IEEE Journal on Selected Areas in Communications, 2018, 36(2): 363-375. DOI:10.1109/JSAC.2018.2804239. [23] Sun Y, Xu D F, Ng D W K, et al. Optimal 3D-trajectory design and resource allocation for solar-powered UAV communication systems[J]. IEEE Transactions on Communications, 2019, 67(6): 4281-4298. DOI:10.1109/TCOMM.2019.2900630. [24] Wächter A, Biegler L T.On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming[J]. Mathematical Programming, 2006, 106(1): 25-57. DOI:10.1007/s10107-004-0559-y. [25] Andersson J A E, Gillis J, Horn G, et al. CasADi: a software framework for nonlinear optimization and optimal control[J]. Mathematical Programming Computation, 2019, 11(1): 1-36. DOI:10.1007/s12532-018-0139-4. [26] Zhang S Y, Zhang S Y, Yuan W J, et al.Efficient rate-splitting multiple access for the Internet of Vehicles: federated edge learning and latency minimization[J]. IEEE Journal on Selected Areas in Communications, 2023, 41(5): 1468-1483. DOI:10.1109/JSAC.2023.3240716. |