通信工程系

付澍

姓名:付    

职称/职务:教授、博/硕士生导师

邮箱:shufu@cqu.edu.cn

工作单位:重庆大学微电子与通信工程学院

个人简介:

付澍,博士,教授,博/硕导,中国民革党员。重庆大学“空天地网络智联与信息融合”重庆市重点实验室主要成员、重庆大学嘉陵江实验室首批兼职教授。2023年、2024年连续进入Elsevier /斯坦福全球前2%顶尖科学家年度影响力榜单。担任SCI期刊《Drones》(五年影响因子4.8)青年编委、中国科技期刊卓越行动计划中文领军期刊《通信学报》(EI期刊)青年编委等学术职务。在中科院一区SCI期刊《Chinese Journal of Aeronautics》、《Tsinghua Science and Technology》等发起低空网络主题的多个特刊。举办/协办IEEE ICCC 2023Co-Session Chair)、EAI GameNet 2022General Co-Chair)等多个学术会议。兼任信息物理社会可信服务计算教育部重点实验室“工业互联网研究所”副所长、IEEE PES电力系统通信与网络安全无线通信技术委员会理事、中国电子学会物联网青年专技组委员、重庆市产学研合作促进会理事等多个社会职务。

团队近年来围绕巨维高动态低空网络智能空口与应急通信方向展开研究。发表论文70余篇、授权国家发明专利9项、国防专利2项。近五年在中科院一、二区SCI期刊发表/录用论文30余篇。论文谷歌引用3000余次,单篇最高1300余次,高被引论文1篇,论文H指数为18

在低空及新一代通信网络方向主持了国家自然科学基金面上项目、青年项目、重庆市自然科学基金重点项目等纵向项目,以及航天504所、中电科54所、中国星网、小米公司等横向项目,累计主持经费近500万元。参与了包含国家自然科学基金区域重点项目、重庆市科技局重大专项的研究。候选人牵头的成果“融合5G NR的低轨卫星互联网星地直连与无人机应急辅助”获得2023年度川渝产学研协同创新成果奖二等奖(排名第一)。系列成果与中国星网(重庆)、航天504所、中电科54所合作开发了星间测控数传、多层异构星座空口波束捷变、星地智能接入等多套原型机与半实物仿真验证平台,且与中电科54所合作的项目获得成果应用转化证明。

所指导的研究生多次获得校优秀硕士学位论文、国家奖学金等荣誉,且多人在通信领域SCI顶刊发表论文。毕业研究生部分赴加拿大、英国等继续攻博,部分进入中电科54所、中国星网(重庆)、中国长安(重庆)、云南省移动总公司等单位。团队优秀的研究生可推荐至海外知名高校和团队继续攻博,或推荐至国内知名科研院所与企业工作。

获奖:

[1]  2023年度川渝产学研协同创新成果奖二等奖,融合5G NR的低轨卫星互联网星地直连与无人机应急辅助,2024CG081/7。

       在研项目:

[1] 国家自然科学基金委员会,面上项目,高时效无人机应急数据收集理论与机制研究,20231月至202612月,在研,主持;

[2]  国家级纵向项目,低轨巨星座空口自主迭代演进资源调度关键技术研究,20256月至20266月,在研,主持;

[3]  国家自然科学基金委员会,区域重点项目,山地大城市环境的电磁传输特性与网络优化理论与方法研究,20221月至202512月,在研,参与;

[4]  小米公司,揭榜挂帅项目,GEO卫星网络最优频点预测及快速搜网,20256月至20266月,在研,主持。

部分结题项目:

[1]   国家自然科学基金委员会,青年科学基金项目,超密集网络中基于服务器虚拟机的多点协作技术研究,20181月至202012月,结题,主持; 

[2]  国家级纵向项目,融合5G的捷变波束低轨卫星随机接入控制和资源调度方案研究,20235月至20245月,结题,主持;

[3]  重庆市科技局,重庆市自然科学基金创新发展联合基金重点项目,基于5G波束管理的多星多波束协同理论与机制研究,202311月至202410月,结题,主持;

[4]  重庆市科学技术局,重庆市技术创新与应用发展专项5G重大主题专项,5G应用驱动的边缘计算网络技术研发及应用,20199月至20218月,结题,参与。

研究方向:

16G多层异构网络跨时空资源协同与多址传输

聚焦空天地一体化网络中的轻量化智能协同与高效传输技术,构建支持地面连续覆盖的轻量化智能网络架构,突破动态环境下的资源分配瓶颈,实现通信-感知-计算一体化服务能力提升。主要研究内容涵盖:高动态网络拓扑的时空演化建模与自适应重构机制,空天地全域场景下存储-计算-通信资源的动态协同优化与智能调度,智能反射表面(RIS)赋能的混合多址传输及波束成形技术,多层异构网络中的分布式波束协同与干扰管理。

2)无人机辅助的智能隐蔽通信

聚焦无人机隐蔽通信场景的可解释轻量化智能架构设计,提出无人机辅助隐蔽通信的广义内涵(视距可见性、传输隐蔽性、反侦察性)。利用无人机移动性构建可重组隐蔽通信网络,旨在突破融合雷达和检测方的反无人机系统威胁下无人机的联合背包与旅行商问题挑战,以提升隐蔽通信系统的抗截获能力、侦察下生存能力和应急响应效率。主要研究内容涵盖:基于多维信息的应急用户数据新鲜度指标建模与动态分簇;侦察风险感知下,无人机隐蔽通信的轨迹规划、三维悬停、资源分配、及限制区用户调度的联合优化;无人机隐蔽中继与智能干扰博弈。

3)卫星互联网的智能演进与优化

本研究聚焦卫星互联网的高动态特性与巨维复杂性,重点突破星间-星地动态业务与拓扑变化的特征提取难题,设计轻量化智能体部署与分布式协同实现卫星网络的智能优化与自主演进。主要研究内容涵盖:面向星间-星地通信的轻量化智能体部署与分布式协同架构设计;基于智能博弈理论的星地多用户公平接入机制;融合矩阵理论的可重构星地波束智能捷变技术;数据-信道双驱动的星地直连与中继智能决策方法;异构时间窗约束下的星间智能交换与动态路由算法。

代表性论著/专利:

[1]

Shu Fu, Xue Feng, Ajmery Sultana, and Lian Zhao, "Joint power allocation and 3D deployment for UAV-BSs: a game theory based deep reinforcement learning approach," IEEE Transactions on Wireless Communications, vol. 23, no. 1, pp. 736-748, 2024. (SCI, 5-Year IF = 8.6)  

[1]

Shu Fu, Jie Gao, and Lian Zhao, “Collaborative multi-resource allocation in terrestrial-satellite network towards 6G,” IEEE Transactions on Wireless Communications, vol. 20, no. 11, pp. 7057-7071, 2021. (SCI, 5-Year IF = 8.6)  

[3]

Shu Fu, Wei Wei, Liuguo Yin, and Lian Zhao, “Joint optimization of 3-D placement and transmission power for a relay based covert communication system,” IEEE Transactions on Communications, Minor Revision. (SCI, 5-Year IF = 6.3)

[4]

Shu Fu, Fang Fang, Lian Zhao, Zhiguo Ding, and Xin Jian, “Joint transmission scheduling and power allocation in non-orthogonal multiple access,” IEEE Transactions on Communications, vol. 67, no. 11, pp. 8137-8150, 2019. (SCI, 5-Year IF = 6.3)

[5]

Fang Fang, Bibo Wu, Shu Fu*, Zhiguo Ding, and Xianbin Wang, “Energy-efficient design of STAR-RIS aided MIMO-NOMA networks,” IEEE Transactions on Communications, vol. 71, no. 1, pp. 498-511, 2023. (SCI, 5-Year IF = 6.3)

[6]

Shu Fu, Xiaohui Guo, Fang Fang, Zhiguo Ding, Ning Zhang, and Ning Wang, “Towards energy-efficient data collection by unmanned aerial vehicle base station with NOMA for emergency communications in IoT,” IEEE Transactions on Vehicular Technology, vol. 72, no. 1, pp. 1211-1223, 2023. (SCI, 5-Year IF = 6.5)

[7]

Shu Fu, Yujie Tang, Ning Zhang, Lian Zhao, Shaohua Wu, and Xin Jian, “Joint unmanned aerial vehicle (UAV) deployment and power control for internet of things networks,” IEEE Transactions on Vehicular Technology, vol. 69, no. 4, pp. 4367-4378, 2020. (SCI, 5-Year IF = 6.5)

[8]

Shu Fu, Jie Gao, and Lian Zhao, “Integrated Resource Management for Terrestrial-Satellite Systems,” IEEE Transactions on Vehicular Technology, vol. 69, no. 3, pp. 3256-3266, 2020. (SCI, 5-Year IF = 6.5)

[9]

Bibo Wu, Fang Fang, and Shu Fu*, “Improving the system performance in terrestrial-satellite relay networks by configuring aerial relay” IEEE Transactions on Vehicular Technology, vol. 70, no. 20, pp. 13139-13148, 2021. (SCI, 5-Year IF = 6.5)

[10]

Shu Fu, Meng Zhang, Min Liu, Chen Chen, and Richard Yu, “Towards energy-efficient UAV-assisted wireless networks using an artificial intelligence approach,” IEEE Wireless Communications, vol. 29, no. 5, pp. 77-83, 2022. (SCI, 5-Year IF = 11.1)

[11]

Shu Fu, Lian Zhao, Xin Jian, and Shaohua Wu, “Data attachment: A novel type of wireless transmission,” IEEE Wireless Communications, vol. 26, no. 6, pp. 126-131, 2019. (SCI, 5-Year IF = 11.1)

[12]

Shu Fu, Yun Wang, Xue Feng, Boya Di, and Chunguo Li, “Reconfigurable intelligent surface assisted non-orthogonal multiple access network based on machine learning approaches,” IEEE Network, vol. 38, no. 2, pp. 272-279, 2024. (SCI, 5-Year IF = 8.5)

[13]

Shu Fu, Liuguo Yin, Chunxiao Jiang, and Abbas Jamalipour, “An energy efficient intelligent framework of UAV enhanced vehicular networks,” IEEE Vehicular Technology Magazine, vol. 17, no. 2, pp. 94-102, 2022. (SCI, 5-Year IF = 9.8)

[14]

Shu Fu, Yi Su, Zhi Zhang, and Liuguo Yin, “A deep reinforcement learning framework and its implementation for unmanned aerial vehicle-aided covert communication,” Chinese Journal of Aeronautics, vol. 38, no. 2, pp. 103257, 2025. (SCI, 5-Year IF = 4.6)

[15]

Wei Wei, Shu Fu*, Yujie Tang, Yuan Wu, Haijun Zhang, “Joint optimization of UAV aided covert edge computing via a deep reinforcement learning framework,” Chinese Journal of Aeronautics, on line, pp. 1-15, 2025. (SCI, 5-Year IF = 4.6)  

[16]

Shu Fu, Yujie Tang, Yuan Wu, Ning Zhang, Huaxi Gu, Chen Chen, and Min Liu, “Energy-efficient UAV enabled data collection via wireless charging: a reinforcement learning approach,” IEEE Internet of Things Journal, vol. 8, no. 12, pp. 10209-10219, 2021. (SCI, 5-Year IF = 9)

[17]

Shu Fu, Qilin Fan, Yujie Tang, Haijun Zhang, Xin Jian, and Xiaoping Zeng, “Cooperative computing in integrated blockchain based internet of things,” IEEE Internet of Things Journal, vol. 7, no. 3, pp. 1603-1612, 2020. (SCI, 5-Year IF = 9)

[18]

Shu Fu, Wei Wei, Xue Feng and Liuguo Yin, “Average sum rate optimization in RIS-assisted NOMA satellite network: A deep reinforcement learning approach,”  IEEE Wireless Communications Letters, on line, pp. 1-5, 2025. (SCI, 5-Year IF = 4.9)

[19]

Wen Zeng, Shu Fu*, and Boya Di, “Optimal covert age of information for a RIS-assisted covert communication system,” IEEE Wireless Communications Letters, on line, pp. 1-5, 2025. (SCI, 5-Year IF = 4.9)

[20]

Xue Feng, Shu Fu*, Fang Fang, and Richard Yu, “Optimizing age of information in RIS-assisted NOMA networks: A deep reinforcement learning approach,” IEEE Wireless Communications Letters, vol. 11, no. 10, pp. 2100-2104, 2022. (SCI, 5-Year IF = 4.9)

[21]

付澍;郭小辉;杨祥月,一种无人机在数据收集过程中的路径规划方法,专利号:ZL202110148205.4,授权日期:2023081日。(国家发明专利)

[22]

付澍;马莉娜;简鑫,一种基于二元逻辑关系的无线数据发送方法,专利号:ZL201811197664.6,授权日期:20220211日。(国家发明专利)

[23]

付澍;伍碧波;陈晨;蔡岳平;简鑫;刘敏,一种空天地卫星通信系统的总吞吐量及能耗优化方法,专利号:ZL202110025379.1,授权日期:202118。(国家发明专利)

[24]

付澍;杨祥月;简鑫;蔡岳平;蒋卫恒;梁靓,一种SDN化的5G网络系统及其协作控制方法,专利号:ZL201711041233.6,授权日期:20201013。(国家发明专利)