王亮科研成果

综合介绍 General Introduction 研究方向：5G/6G通信、物理层安全、移动边缘计算、无人机通信、可重构智能超表面、机器学习。Google Scholar：主页 个人相册 内容来自集群智慧云企服 发明专利4999元代写全部资料全国受理

教育教学

个人经历 personal experience 工作经历 教育经历 英国克兰菲尔德大学，20211125-20230514，博士后 学校名称 起始时间 结束时间 学历 学位 英国萨里大学 硕士研究生毕业 理学硕士 英国诺森比亚大学 博士研究生毕业 哲学博士 内容来自集群智慧云企服 发明专利4999元代写全部资料全国受理

荣誉获奖

学科信息 Subject information 内容来自集群智慧云企服 请访问正版网址 www.jiqunzhihui.net

科学研究

科研成果 Scientific research results 论文成果 专利成果 软件著作权 专著成果 其他成果 [1] Multi-agent deep reinforcement learning-based trajectory planning for multi-UAV assisted mobile edge computing.IEEE Transactions on Cognitive Communications and Networking, [2] Deep reinforcement learning based dynamic trajectory control for UAV-assisted mobile edge computing.IEEE Transactions on Mobile Computing, [3] Joint trajectory and passive beamforming design for intelligent reflecting surface-aided UAV communications: A deep reinforcement learning approach.IEEE Transactions on Mobile Computing, [4] RL-based user association and resource allocation for multi-UAV enabled MEC.2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC), [5] Deep Q-network based dynamic trajectory design for UAV-aided emergency communications.Journal of Communications and Information Networks, [6] Deep Reinforcement Learning-Based Resource Management for Flexible Mobile Edge Computing: Architectures, Applications, and Research Issues.IEEE Vehicular Technology Magazine, [7] Graph layer security: Encrypting information via common networked physics.Sensors, [8] Secret key rate upper-bound for reconfigurable intelligent surface-combined system under spoofing.2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall), [9] Securing IoT Communication using Physical Sensor Data--Graph Layer Security with Federated Multi-Agent Deep Reinforcement Learning.IEEE--2023 8th International Conference on Signal and Image Processing, [10] Deep reinforcement learning-based long-range autonomous valet parking for smart cities.Sustainable Cities and Society, [11] Long-term CSI-based design for RIS-aided multiuser MISO systems exploiting deep reinforcement learning.IEEE Communications Letters,

内容来自集群智慧云企服 软件产品登记测试全国受理

学术成果

社会兼职 Social Appointments 2021 IEEE  Wireless Communications Letters 模范审稿人IEEE TCCN，TMC，ToC， IoTJ，CL，WCL，ICC等权威期刊及会议审稿人 内容来自集群智慧云企服 www.jiqunzhihui.net

综合介绍