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A review of unmanned aerial vehicles deployment optimization in 6G low-altitude communication scenarios
Received date: 2024-09-30
Revised date: 2024-10-14
Accepted date: 2024-11-05
Online published: 2024-11-20
Supported by
National Natural Science Foundation of China(62225103);Beijing Municipal Natural Science Foundation(L212004)
With the rapid evolution of 6G standards， the application of Unmanned Aerial Vehicles （UAVs） in low-altitude communication networks has become a research hotspot. This paper gives a review of UAV deployment optimization in low-altitude communication scenarios， conducting analysis of both static and dynamic deployment strategies for UAVs， as well as related deployment optimization algorithms. The article first explains three basic strategies for UAV deployment： static deployment， single-UAV dynamic deployment， and multi-UAV dynamic deployment， exploring their advantages in different application scenarios. Then， the UAV deployment optimization models are discussed in terms of the channel model， constraints， and objective functions within low-altitude communication networks. Based on this， the paper systematically compares existing UAV deployment optimization algorithms， analyzing the strengths and weaknesses of each algorithm from multiple perspectives. Finally， future research directions of UAV deployment optimization are forecasted， and emerging technologies such as intelligent reflecting surfaces and integrated communication and sensing are analyzed to provide reference and insights for researchers in the field.
Haijun ZHANG , Qingyue XIA , Xu MA , Chao REN , Yang LU . A review of unmanned aerial vehicles deployment optimization in 6G low-altitude communication scenarios[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2025 , 46(11) : 531296 -531296 . DOI: 10.7527/S1000-6893.2024.31296
| [1] | 易芝玲， 王森， 韩双锋， 等. 从5G到6G的思考： 需求、挑战与技术发展趋势［J］. 北京邮电大学学报， 2020， 43（2）： 1-9. |
| YI Z L， WANG S， HAN S F， et al. From 5G to 6G： Requirements， challenges and technical trends［J］. Journal of Beijing University of Posts and Telecommunications， 2020， 43（2）： 1-9 （in Chinese）. | |
| [2] | 陈新颖， 盛敏， 李博， 等. 面向6G的无人机通信综述［J］. 电子与信息学报， 2022， 44（3）： 781-789. |
| CHEN X Y， SHENG M， LI B， et al. Survey on unmanned aerial vehicle communications for 6G［J］. Journal of Electronics & Information Technology， 2022， 44（3）： 781-789 （in Chinese）. | |
| [3] | GUPTA L， JAIN R， VASZKUN G. Survey of important issues in UAV communication networks［J］. IEEE Communications Surveys & Tutorials， 2016， 18（2）： 1123-1152. |
| [4] | VAEZI M， AZARI A， KHOSRAVIRAD S R， et al. Cellular， wide-area， and non-terrestrial IoT： A survey on 5G advances and the road toward 6G［J］. IEEE Communications Surveys & Tutorials， 2022， 24（2）： 1117-1174. |
| [5] | JAVED S， HASSAN A， AHMAD R， et al. State-of-the-art and future research challenges in UAV swarms［J］. IEEE Internet of Things Journal， 2024， 11（11）： 19023-19045. |
| [6] | 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. |
| [7] | CHEN R R， SUN Y J， LIANG L P， et al. Joint power allocation and placement scheme for UAV-assisted IoT with QoS guarantee［J］. IEEE Transactions on Vehicular Technology， 2022， 71（1）： 1066-1071. |
| [8] | NGUYEN H T， TUAN H D， DUONG T Q， et al. Joint D2D assignment， bandwidth and power allocation in cognitive UAV-enabled networks［J］. IEEE Transactions on Cognitive Communications and Networking， 2020， 6（3）： 1084-1095. |
| [9] | ZHONG X J， GUO Y， LI N， et al. Joint optimization of relay deployment， channel allocation， and relay assignment for UAVs-aided D2D networks［J］. IEEE/ACM Transactions on Networking， 2020， 28（2）： 804-817. |
| [10] | PAN H Y， LIU Y H， SUN G， et al. Resource scheduling for UAVs-aided D2D networks： A multi-objective optimization approach［J］. IEEE Transactions on Wireless Communications， 2024， 23（5）： 4691-4708. |
| [11] | YU Z， GONG Y M， GONG S M， et al. Joint task offloading and resource allocation in UAV-enabled mobile edge computing［J］. IEEE Internet of Things Journal， 2020， 7（4）： 3147-3159. |
| [12] | MEI W D， WU Q Q， ZHANG R. Cellular-connected UAV： Uplink association， power control and interference coordination［C］∥2018 IEEE Global Communications Conference （GLOBECOM）. Piscataway： IEEE Press， 2018. |
| [13] | ZHOU L Y， CHEN X H， HONG M Y， et al. Efficient resource allocation for multi-UAV communication against adjacent and co-channel interference［J］. IEEE Transactions on Vehicular Technology， 2021， 70（10）： 10222-10235. |
| [14] | LU J， LI J F， YU F R， et al. UAV-assisted heterogeneous cloud radio access network with comprehensive interference management［J］. IEEE Transactions on Vehicular Technology， 2024， 73（1）： 843-859. |
| [15] | YANG P， XI X， QUEK T Q S， et al. Power control for a URLLC-enabled UAV system incorporated with DNN-based channel estimation［J］. IEEE Wireless Communications Letters， 2021， 10（5）： 1018-1022. |
| [16] | LIN N， LIU Y H， ZHAO L， et al. An adaptive UAV deployment scheme for emergency networking［J］. IEEE Transactions on Wireless Communications， 2022， 21（4）： 2383-2398. |
| [17] | PAN W， LV N， HOU B， et al. Resource allocation and outage probability optimization method for multi-hop UAV relay network for servicing heterogeneous users［J］. IEEE Transactions on Network Science and Engineering， 2024， 11（3）： 2769-2781. |
| [18] | YANG Z Y， BI S Z， ZHANG Y A. Deployment optimization of dual-functional UAVs for integrated localization and communication［J］. IEEE Transactions on Wireless Communications， 2023， 22（12）： 9672-9687. |
| [19] | LIU K， LIU Y M， YI P F， et al. Deployment and robust hybrid beamforming for UAV MmWave communications［J］. IEEE Transactions on Communications， 2023， 71（5）： 3073-3086. |
| [20] | ZHANG X Q， ZHANG H J， SUN K， et al. Human-centric irregular RIS-assisted multi-UAV networks with resource allocation and reflecting design for metaverse［J］. IEEE Journal on Selected Areas in Communications， 2024， 42（3）： 603-615. |
| [21] | YUAN X P， HU Y L， ZHANG J， et al. Joint user scheduling and UAV trajectory design on completion time minimization for UAV-aided data collection［J］. IEEE Transactions on Wireless Communications， 2023， 22（6）： 3884-3898. |
| [22] | WANG Y L， CHEN M， PAN C H， et al. Joint optimization of UAV trajectory and sensor uploading powers for UAV-assisted data collection in wireless sensor networks［J］. IEEE Internet of Things Journal， 2022， 9（13）： 11214-11226. |
| [23] | 付澍， 杨祥月， 张海君， 等. 物联网数据收集中无人机路径智能规划［J］. 通信学报， 2021， 42（2）： 124-133. |
| FU S， YANG X Y， ZHANG H J， et al. UAV path intelligent planning in IoT data collection［J］. Journal on Communications， 2021， 42（2）： 124-133 （in Chinese）. | |
| [24] | ZHU B T， BEDEER E， NGUYEN H H， et al. UAV trajectory planning for AoI-minimal data collection in UAV-aided IoT networks by transformer［J］. IEEE Transactions on Wireless Communications， 2023， 22（2）： 1343-1358. |
| [25] | SHEN L F， WANG N， ZHANG D， et al. Energy-aware dynamic trajectory planning for UAV-enabled data collection in mMTC networks［J］. IEEE Transactions on Green Communications and Networking， 2022， 6（4）： 1957-1971. |
| [26] | CHAI R， GAO Y F， SUN R J， et al. Time-oriented joint clustering and UAV trajectory planning in UAV-assisted WSNs： Leveraging parallel transmission and variable velocity scheme［J］. IEEE Transactions on Intelligent Transportation Systems， 2023， 24（11）： 12092-12106. |
| [27] | LIU K， ZHENG J. UAV trajectory planning with interference awareness for time-constrained data collection［C］∥GLOBECOM 2023-2023 IEEE Global Communications Conference. Piscataway： IEEE Press， 2023. |
| [28] | MA Y， TANG Y Q， MAO Z J， et al. Energy-efficient 3D trajectory optimization for UAV-aided wireless sensor networks［C］∥GLOBECOM 2023-2023 IEEE Global Communications Conference. Piscataway： IEEE Press， 2023. |
| [29] | LIU J， YANG F， WANG X J， et al. Joint optimization of charging station placement and UAV trajectory for fresh data collection［J］. IEEE Internet of Things Journal， 2024， 11（14）： 25057-25073. |
| [30] | LIU B Y， WAN Y Y， ZHOU F H， et al. Resource allocation and trajectory design for MISO UAV-assisted MEC networks?［J］. IEEE Transactions on Vehicular Technology， 2022， 71（5）： 4933-4948. |
| [31] | WANG D， TIAN J， ZHANG H X， et al. Task offloading and trajectory scheduling for UAV-enabled MEC networks： An optimal transport theory perspective［J］. IEEE Wireless Communications Letters， 2022， 11（1）： 150-154. |
| [32] | YE W D， ZHAO L， ZHOU J， et al. Energy-efficient flight scheduling and trajectory optimization in UAV-aided edge computing networks［J］. IEEE Transactions on Network Science and Engineering， 2024， 11（5）： 4591-4602. |
| [33] | LI P M， XIE L F， YAO J P， et al. Cellular-connected UAV with adaptive air-to-ground interference cancellation and trajectory optimization［J］. IEEE Communications Letters， 2022， 26（6）： 1368-1372. |
| [34] | LIU K， ZHENG J. UAV trajectory planning with interference awareness in UAV-enabled time-constrained data collection systems［J］. IEEE Transactions on Vehicular Technology， 2024， 73（2）： 2799-2815. |
| [35] | ZHAO N， YE Z Y， PEI Y Y， et al. Multi-agent deep reinforcement learning for task offloading in UAV-assisted mobile edge computing［J］. IEEE Transactions on Wireless Communications， 2022， 21（9）： 6949-6960. |
| [36] | LI C L， GAN Y Z， ZHANG Y， et al. A cooperative computation offloading strategy with on-demand deployment of multi-UAVs in UAV-aided mobile edge computing［J］. IEEE Transactions on Network and Service Management， 2024， 21（2）： 2095-2110. |
| [37] | LIAO Z F， YUAN C H， ZHENG B， et al. An adaptive deployment scheme of unmanned aerial vehicles in dynamic vehicle networking for complete offloading［J］. IEEE Internet of Things Journal， 2024， 11（13）： 23509-23520. |
| [38] | TARIQ Z U A， BACCOUR E， ERBAD A， et al. RL-based adaptive UAV swarm formation and clustering for secure 6G wireless communications in dynamic dense environments［J］. IEEE Access， 2024， 12： 125609-125628. |
| [39] | DUAN X J， LIU H Y， TANG H， et al. A novel hybrid auction algorithm for multi-UAVs dynamic task assignment［J］. IEEE Access， 2019， 8： 86207-86222. |
| [40] | CHAI S Q， LAU V K N. Multi-UAV trajectory and power optimization for cached UAV wireless networks with energy and content recharging-demand driven deep learning approach［J］. IEEE Journal on Selected Areas in Communications， 2021， 39（10）： 3208-3224. |
| [41] | SONG S， CHOI M， KO D E， et al. Multi-UAV trajectory optimization considering collisions in FSO communication networks［J］. IEEE Journal on Selected Areas in Communications， 2021， 39（11）： 3378-3394. |
| [42] | HU W J， YU Y， LIU S M， et al. Multi-UAV coverage path planning： A distributed online cooperation method［J］. IEEE Transactions on Vehicular Technology， 2023， 72（9）： 11727-11740. |
| [43] | SHAO X X， GONG Y J， ZHAN Z H， et al. Bipartite cooperative coevolution for energy-aware coverage path planning of UAVs［J］. IEEE Transactions on Artificial Intelligence， 2022， 3（1）： 29-42. |
| [44] | YAN C X， FU L G， ZHANG J K， et al. A comprehensive survey on UAV communication channel modeling［J］. IEEE Access， 2019， 7： 107769-107792. |
| [45] | AL-HOURANI A， KANDEEPAN S， LARDNER S. Optimal LAP altitude for maximum coverage［J］. IEEE Wireless Communications Letters， 2014， 3（6）： 569-572. |
| [46] | DING R， GAO F， SHEN X S. 3D UAV trajectory design and frequency band allocation for energy-efficient and fair communication： A deep reinforcement learning approach［J］. IEEE Transactions on Wireless Communications， 2020， 19（12）： 7796-7809. |
| [47] | CAO H J， YU G H， CHEN Z G. Cooperative task offloading and dispatching optimization for large-scale users via UAVs and HAP［C］∥2023 IEEE Wireless Communications and Networking Conference （WCNC）. Piscataway： IEEE Press， 2023. |
| [48] | GONG S M， WANG M， GU B， et al. Bayesian optimization enhanced deep reinforcement learning for trajectory planning and network formation in multi-UAV networks［J］. IEEE Transactions on Vehicular Technology， 2023， 72（8）： 10933-10948. |
| [49] | DAI C， ZHU K， HOSSAIN E. Multi-agent deep reinforcement learning for joint decoupled user association and trajectory design in full-duplex multi-UAV networks［J］. IEEE Transactions on Mobile Computing， 2022， 22（10）： 6056-6070. |
| [50] | TSAI H C， HONG Y P， SHEU J P. Completion time minimization for UAV-enabled surveillance over multiple restricted regions［J］. IEEE Transactions on Mobile Computing， 2023， 22（12）： 6907-6920. |
| [51] | TANG G F， DU P F， LEI H J， et al. Trajectory design and communication resources allocation for wireless powered secure UAV communication systems［J］. IEEE Systems Journal， 2022， 16（4）： 6300-6308. |
| [52] | HU X Y， WONG K K， YANG K， et al. UAV-assisted relaying and edge computing： Scheduling and trajectory optimization［J］. IEEE Transactions on Wireless Communications， 2019， 18（10）： 4738-4752. |
| [53] | QIAN Y W， WANG F F， LI J， et al. User association and path planning for UAV-aided mobile edge computing with energy restriction［J］. IEEE Wireless Communications Letters， 2019， 8（5）： 1312-1315. |
| [54] | DENG X H， LI J， GUAN P Y， et al. Energy-efficient UAV-aided target tracking systems based on edge computing［J］. IEEE Internet of Things Journal， 2022， 9（3）： 2207-2214. |
| [55] | LIU Y， LIU S， LIU X， et al. Sensing fairness-based energy efficiency optimization for UAV enabled integrated sensing and communication［J］. IEEE Wireless Communications Letters， 2023， 12（10）： 1702-1706. |
| [56] | YUAN X P， JIANG H， HU Y L， et al. Joint analog beamforming and trajectory planning for energy-efficient UAV-enabled nonlinear wireless power transfer［J］. IEEE Journal on Selected Areas in Communications， 2022， 40（10）： 2914-2929. |
| [57] | XIA W C， ZHU Y X， DE SIMONE L， et al. Multiagent collaborative learning for UAV enabled wireless networks［J］. IEEE Journal on Selected Areas in Communications， 2022， 40（9）： 2630-2642. |
| [58] | WU T H， LIU J F， LIU J， et al. A novel AI-based framework for AoI-optimal trajectory planning in UAV-assisted wireless sensor networks［J］. IEEE Transactions on Wireless Communications， 2022， 21（4）： 2462-2475. |
| [59] | SUN H G， ZHOU Y， TANG J C， et al. Average AoI-minimal trajectory design for UAV-assisted IoT data collection system： A safe-TD3 approach［J］. IEEE Wireless Communications Letters， 2024， 13（2）： 530-534. |
| [60] | CHEN B Q， LIU D， ZHANG J L， et al. Learning-aided UAV-cooperation reduces the age-of-information in wireless networks［J］. IEEE Communications Letters， 2024， 28（5）： 1053-1057. |
| [61] | YANG G， QIAN Y W， REN K， et al. Covert wireless communications for augmented reality systems with dual cooperative UAVs［J］. IEEE Journal of Selected Topics in Signal Processing， 2023， 17（5）： 1119-1130. |
| [62] | ZHOU L， WU D， WEI X， et al. Seeing isn’t believing： QoE evaluation for privacy-aware users［J］. IEEE Journal on Selected Areas in Communications， 2019， 37（7）： 1656-1665. |
| [63] | DU H Y， NIYATO D， XIE Y A， et al. Performance analysis and optimization for jammer-aided multiantenna UAV covert communication［J］. IEEE Journal on Selected Areas in Communications， 2022， 40（10）： 2962-2979. |
| [64] | LI Z， LIAO X M， SHI J， et al. MD-GAN-based UAV trajectory and power optimization for cognitive covert communications［J］. IEEE Internet of Things Journal， 2022， 9（12）： 10187-10199. |
| [65] | SUN C， XIONG X X， ZHAI Z Y， et al. Max-Min fair 3D trajectory design and transmission scheduling for solar-powered fixed-wing UAV-assisted data collection［J］. IEEE Transactions on Wireless Communications， 2023， 22（12）： 8650-8665. |
| [66] | DIAO X B， ZHENG J C， CAI Y M， et al. Fair data allocation and trajectory optimization for UAV-assisted mobile edge computing［J］. IEEE Communications Letters， 2019， 23（12）： 2357-2361. |
| [67] | REN Y H， ZHANG L. An adaptive evolutionary multi-objective estimation of distribution algorithm and its application to multi-UAV path planning［J］. IEEE Access， 2023， 11： 50038-50051. |
| [68] | LI J H， SUN G， DUAN L J， et al. Multi-objective optimization for UAV swarm-assisted IoT with virtual antenna arrays［J］. IEEE Transactions on Mobile Computing， 2024， 23（5）： 4890-4907. |
| [69] | WAN Y T， ZHONG Y F， MA A L， et al. An accurate UAV 3-D path planning method for disaster emergency response based on an improved multiobjective swarm intelligence algorithm［J］. IEEE Transactions on Cybernetics， 2023， 53（4）： 2658-2671. |
| [70] | SHAMI T M， EL-SALEH A A， ALSWAITTI M， et al. Particle swarm optimization： A comprehensive survey［J］. IEEE Access， 2022， 10： 10031-10061. |
| [71] | FU Y G， DING M Y， ZHOU C P， et al. Route planning for unmanned aerial vehicle （UAV） on the sea using hybrid differential evolution and quantum-behaved particle swarm optimization［J］. IEEE Transactions on Systems， Man， and Cybernetics： Systems， 2013， 43（6）： 1451-1465. |
| [72] | HARIS M， BHATTI D M S， NAM H. A fast-convergent hyperbolic tangent PSO algorithm for UAVs path planning［J］. IEEE Open Journal of Vehicular Technology， 2024， 5： 681-694. |
| [73] | YAN F， CHU J， HU J， et al. Cooperative task allocation with simultaneous arrival and resource constraint for multi-UAV using a genetic algorithm［J］. Expert Systems with Applications， 2024， 245： 123023. |
| [74] | ZHENG J B， DING M H， SUN L， et al. Distributed stochastic algorithm based on enhanced genetic algorithm for path planning of multi-UAV cooperative area search［J］. IEEE Transactions on Intelligent Transportation Systems， 2023， 24（8）： 8290-8303. |
| [75] | WU L J， SUN Q， XU H T， et al. Design of hybrid simulated annealing algorithm for UAV scheduling based on coordinated task scheduling［C］∥2021 40th Chinese Control Conference （CCC）. Piscataway： IEEE Press， 2021. |
| [76] | MA M X， WU J， SHI Y， et al. Chaotic random opposition-based learning and cauchy mutation improved moth-flame optimization algorithm for intelligent route planning of multiple UAVs［J］. IEEE Access， 2022， 10： 49385-49397. |
| [77] | DEWANGAN R K， SHUKLA A， GODFREY W W. Three dimensional path planning using grey wolf optimizer for UAVs［J］. Applied Intelligence， 2019， 49（6）： 2201-2217. |
| [78] | 张国印， 孟想， 李思照. 基于果蝇优化算法的无人机航路规划方法［J］. 无线电通信技术， 2021， 47（3）： 344-352. |
| ZHANG G Y， MENG X， LI S Z. UAV path planning method based on fruit fly optimization algorithm［J］. Radio Communications Technology， 2021， 47（3）： 344-352 （in Chinese）. | |
| [79] | DUAN H B， ZHAO J X， DENG Y M， et al. Dynamic discrete pigeon-inspired optimization for multi-UAV cooperative search-attack mission planning［J］. IEEE Transactions on Aerospace and Electronic Systems， 2021， 57（1）： 706-720. |
| [80] | WU Y， LIANG T J， GOU J Z， et al. Heterogeneous mission planning for multiple UAV formations via metaheuristic algorithms［J］. IEEE Transactions on Aerospace and Electronic Systems， 2023， 59（4）： 3924-3940. |
| [81] | SHI L， XU S K. UAV path planning with QoS constraint in device-to-device 5G networks using particle swarm optimization［J］. IEEE Access， 2020， 8： 137884-137896. |
| [82] | ALFATTANI S， JAAFAR W， YANIKOMEROGLU H， et al. Multi-UAV data collection framework for wireless sensor networks［C］∥2019 IEEE Global Communications Conference （GLOBECOM）. Piscataway： IEEE Press， 2019. |
| [83] | SHEN L F， WANG N， ZHU Z Y， et al. UAV-enabled data collection for mMTC networks： AEM modeling and energy-efficient trajectory design［C］∥ICC 2020-2020 IEEE International Conference on Communications （ICC）. Piscataway： IEEE Press， 2020. |
| [84] | JOSEPH J， RADMANESH M， SADAT M N， et al. UAV path planning for data ferrying with communication constraints［C］∥2020 IEEE 17th Annual Consumer Communications & Networking Conference （CCNC）. Piscataway： IEEE Press， 2020. |
| [85] | ROBERGE V， TARBOUCHI M， LABONTE G. Comparison of parallel genetic algorithm and particle swarm optimization for real-time UAV path planning［J］. IEEE Transactions on Industrial Informatics， 2013， 9（1）： 132-141. |
| [86] | ZENG Y， ZHANG R. Energy-efficient UAV communication with trajectory optimization［J］. IEEE Transactions on Wireless Communications， 2017， 16（6）： 3747-3760. |
| [87] | WU Q Q， ZENG Y， ZHANG R. Joint trajectory and communication design for multi-UAV enabled wireless networks［J］. IEEE Transactions on Wireless Communications， 2018， 17（3）： 2109-2121. |
| [88] | HU Q Y， CAI Y L， LIU A， et al. Low-complexity joint resource allocation and trajectory design for UAV-aided relay networks with the segmented ray-tracing channel model［J］. IEEE Transactions on Wireless Communications， 2020， 19（9）： 6179-6195. |
| [89] | WANG H C， WANG J L， DING G R， et al. Completion time minimization for turning angle-constrained UAV-to-UAV communications［J］. IEEE Transactions on Vehicular Technology， 2020， 69（4）： 4569-4574. |
| [90] | ZHANG C M， LU Y. Study on artificial intelligence： The state of the art and future prospects［J］. Journal of Industrial Information Integration， 2021， 23： 100224. |
| [91] | ARULKUMARAN K， DEISENROTH M P， BRUNDAGE M， et al. Deep reinforcement learning： A brief survey［J］. IEEE Signal Processing Magazine， 2017， 34（6）： 26-38. |
| [92] | LUONG N C， HOANG D T， GONG S M， et al. Applications of deep reinforcement learning in communications and networking： A survey［J］. IEEE Communications Surveys & Tutorials， 2019， 21（4）： 3133-3174. |
| [93] | HE H S， YUAN W K， CHEN S W， et al. Deep reinforcement learning-based distributed 3D UAV trajectory design［J］. IEEE Transactions on Communications， 2024， 72（6）： 3736-3751. |
| [94] | MAO Q， HU F， HAO Q. Deep learning for intelligent wireless networks： A comprehensive survey［J］. IEEE Communications Surveys & Tutorials， 2018， 20（4）： 2595-2621. |
| [95] | HUANG Z H， XU X D. DQN-based relay deployment and trajectory planning in consensus-based multi-UAVs tracking network［C］∥2021 IEEE International Conference on Communications Workshops （ICC Workshops）. Piscataway： IEEE Press， 2021. |
| [96] | DENG D H， WANG C W， WANG W D. Joint air-to-ground scheduling in UAV-aided vehicular communication： a DRL approach with partial observations［J］. IEEE Communications Letters， 2022， 26（7）： 1628-1632. |
| [97] | LIU B H， LIU C X， PENG M G. Dynamic cache placement and trajectory design for UAV-assisted networks： a two-timescale deep reinforcement learning approach［J］. IEEE Transactions on Vehicular Technology， 2024， 73（4）： 5516-5530. |
| [98] | 孙彧， 曹雷， 陈希亮， 等. 多智能体深度强化学习研究综述［J］. 计算机工程与应用， 2020， 56（5）： 13-24. |
| SUN Y， CAO L， CHEN X L， et al. Overview of multi-agent deep reinforcement learning［J］. Computer Engineering and Applications， 2020， 56（5）： 13-24 （in Chinese）. | |
| [99] | XIAO Y， SONG Y Q， LIU J. Collaborative multi-agent deep reinforcement learning for energy-efficient resource allocation in heterogeneous mobile edge computing networks［J］. IEEE Transactions on Wireless Communications， 2024， 23（6）： 6653-6668. |
| [100] | PI Y， ZHANG W， ZHANG Y， et al. Applications of multi-agent deep reinforcement learning communication in network management： A survey［DB/OL］. arXiv preprint： 2407.17030，2024. |
| [101] | OUBBATI O S， LAKAS A， GUIZANI M. Multiagent deep reinforcement learning for wireless-powered UAV networks［J］. IEEE Internet of Things Journal， 2022， 9（17）： 16044-16059. |
| [102] | BAI C C， YAN P， PIAO H Y， et al. Learning-based multi-UAV flocking control with limited visual field and instinctive repulsion［J］. IEEE Transactions on Cybernetics， 2024， 54（1）： 462-475. |
| [103] | DENG L Y， GONG W， LIWANG M H， et al. Towards intelligent mobile crowdsensing with task state information sharing over edge-assisted UAV networks［J］. IEEE Transactions on Vehicular Technology， 2024， 73（8）： 11773-11788. |
| [104] | ZHANG Y， ZHUANG Z R， GAO F F， et al. Multi-agent deep reinforcement learning for secure UAV communications［C］∥2020 IEEE Wireless Communications and Networking Conference （WCNC）. Piscataway： IEEE Press， 2020. |
| [105] | ZHANG Y， MOU Z Y， GAO F F， et al. UAV-enabled secure communications by multi-agent deep reinforcement learning［J］. IEEE Transactions on Vehicular Technology， 2020， 69（10）： 11599-11611. |
| [106] | ZHU B T， BEDEER E， NGUYEN H H， et al. UAV trajectory planning in wireless sensor networks for energy consumption minimization by deep reinforcement learning［J］. IEEE Transactions on Vehicular Technology， 2021， 70（9）： 9540-9554. |
| [107] | BRESSON X， LAURENT T. The transformer network for the traveling salesman problem［DB/OL］. arXiv preprint： 2103.03012， 2021. |
| [108] | LONG H， DUAN H. Cooperative mission planning based on game theory for UAVs and USVs heterogeneous system in dynamic scenario［J］. Aircraft Engineering and Aerospace Technology， 2024， 96（9）： 1128-1138. |
| [109] | CHEN J X， WU Q H， XU Y H， et al. Joint task assignment and spectrum allocation in heterogeneous UAV communication networks： A coalition formation game-theoretic approach［J］. IEEE Transactions on Wireless Communications， 2021， 20（1）： 440-452. |
| [110] | WU H C， LI M， GAO Q Y， et al. Eavesdropping and anti-eavesdropping game in UAV wiretap system： A differential game approach［J］. IEEE Transactions on Wireless Communications， 2022， 21（11）： 9906-9920. |
| [111] | CHEN G， ZHAI X B， LI C D. Joint optimization of trajectory and user association via reinforcement learning for UAV-aided data collection in wireless networks［J］. IEEE Transactions on Wireless Communications， 2023， 22（5）： 3128-3143. |
| [112] | YU Y F， LIU X， LEUNG V C M. Fair downlink communications for RIS-UAV enabled mobile vehicles［J］. IEEE Wireless Communications Letters， 2022， 11（5）： 1042-1046. |
| [113] | YE J， QIAO J P， KAMMOUN A， et al. Nonterrestrial communications assisted by reconfigurable intelligent surfaces［J］. Proceedings of the IEEE， 2022， 110（9）： 1423-1465. |
| [114] | BANSAL A， AGRAWAL N， SINGH K， et al. RIS selection scheme for UAV-based multi-RIS-aided multiuser downlink network with imperfect and outdated CSI［J］. IEEE Transactions on Communications， 2023， 71（8）： 4650-4664. |
| [115] | WU Z Q， LI X H， CAI Y X， et al. Joint trajectory and resource allocation design for RIS-assisted UAV-enabled ISAC systems［J］. IEEE Wireless Communications Letters， 2024， 13（5）： 1384-1388. |
| [116] | ZHANG H J， HUANG M L， ZHOU H， et al. Capacity maximization in RIS-UAV networks： A DDQN-based trajectory and phase shift optimization approach［J］. IEEE Transactions on Wireless Communications， 2023， 22（4）： 2583-2591. |
| [117] | BALASUBRAMANIAM A， GUL M J J， MENON V G， et al. Blockchain for intelligent transport system［J］. IETE Technical Review， 2021， 38（4）： 438-449. |
| [118] | AGGARWAL S， KUMAR N， TANWAR S. Blockchain-envisioned UAV communication using 6G networks： Open issues， use cases， and future directions［J］. IEEE Internet of Things Journal， 2021， 8（7）： 5416-5441. |
| [119] | CHENG X， HUANG Z W， BAI L. Channel nonstationarity and consistency for beyond 5G and 6G： A survey［J］. IEEE Communications Surveys & Tutorials， 2022， 24（3）： 1634-1669. |
| [120] | WU J， YUAN W J， HANZO L. When UAVs meet ISAC： Real-time trajectory design for secure communications［J］. IEEE Transactions on Vehicular Technology， 2023， 72（12）： 16766-16771. |
| [121] | PAN Y， LI R G， DA X Y， et al. Cooperative trajectory planning and resource allocation for UAV-enabled integrated sensing and communication systems［J］. IEEE Transactions on Vehicular Technology， 2024， 73（5）： 6502-6516. |
| [122] | DENG C L， FANG X M， WANG X B. Beamforming design and trajectory optimization for UAV-empowered adaptable integrated sensing and communication［J］. IEEE Transactions on Wireless Communications， 2023， 22（11）： 8512-8526. |
| [123] | KANG H Y， CHANG X L， MI?I? J， et al. Cooperative UAV resource allocation and task offloading in hierarchical aerial computing systems： A MAPPO-based approach［J］. IEEE Internet of Things Journal， 2023， 10（12）： 10497-10509. |
| [124] | ARANI A H， HU P， ZHU Y Y. HAPS-UAV-enabled heterogeneous networks： A deep reinforcement learning approach［DB/OL］. arXiv preprint： 2303.12883， 2023. |
| [125] | JAVED S， ALOUINI M S， DING Z G. An interdisciplinary approach to optimal communication and flight operation of high-altitude long-endurance platforms［J］. IEEE Transactions on Aerospace and Electronic Systems， 2023， 59（6）： 8327-8341. |
| [126] | NGUYEN M D， LE L B， GIRARD A. Integrated computation offloading， UAV trajectory control， edge-cloud and radio resource allocation in SAGIN［J］. IEEE Transactions on Cloud Computing， 2024， 12（1）： 100-115. |
| [127] | YU J D， LIU X L， GAO Y， et al. 3D channel tracking for UAV-satellite communications in space-air-ground integrated networks［J］. IEEE Journal on Selected Areas in Communications， 2020， 38（12）： 2810-2823. |
| [128] | HU Z Z， ZENG F Z， XIAO Z， et al. Joint resources allocation and 3D trajectory optimization for UAV-enabled space-air-ground integrated networks［J］. IEEE Transactions on Vehicular Technology， 2023， 72（11）： 14214-14229. |
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