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| 1 | Towards 6G wireless communication networks:vision,enabling technologies,and new paradigm shifts显示文摘The fifth generation(5G)wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized,such as mass connectivity,ultra-reliability,and guaranteed low latency.However,5G will not meet all requirements of the future in 2030 and beyond,and sixth generation(6G)wireless communication networks are expected to provide global coverage,enhanced spectral/energy/cost efficiency,better intelligence level and security,etc.To meet these requirements,6G networks will rely on new enabling technologies,i.e.,air interface and transmission technologies and novel network architecture,such as waveform design,multiple access,channel coding schemes,multi-antenna technologies,network slicing,cell-free architecture,and cloud/fog/edge computing.Our vision on 6G is that it will have four new paradigm shifts.First,to satisfy the requirement of global coverage,6G will not be limited to terrestrial communication networks,which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle(UAV)communication networks,thus achieving a space-airground-sea integrated communication network.Second,all spectra will be fully explored to further increase data rates and connection density,including the sub-6GHz,millimeter wave(mmWave),terahertz(THz),and optical frequency bands.Third,facing the big datasets generated by the use of extremely heterogeneous networks,diverse communication scenarios,large numbers of antennas,wide bandwidths,and new service requirements,6G networks will enable a new range of smart applications with the aid of artificial intelligence(AI)and big data technologies.Fourth,network security will have to be strengthened when developing 6G networks.This article provides a comprehensive survey of recent advances and future trends in these four aspects.Clearly,6G with additional technical requirements beyond those of 5G will enable faster and further communications to the extent that the boundary between physical and cyber worlds disappears. | Xiaohu YOU Cheng-Xiang WANG Jie HUANG Xiqi GAO Zaichen ZHANG Mao WANG Yongming HUANG Chuan ZHANG Yanxiang JIANG Jiaheng WANG Min ZHU Bin SHENG Dongming WANG Zhiwen PAN Pengcheng ZHU Yang YANG Zening LIU Ping ZHANG Xiaofeng TAO Shaoqian LI Zhi CHEN Xinying MA Chih-Lin I Shuangfeng HAN Ke LI Chengkang PAN Zhimin ZHENG Lajos HANZO Xuemin(Sherman)SHEN Yingjie Jay GUO Zhiguo DING Harald HAAS Wen TONG Peiying ZHU Ganghua YANG Jun WANG Erik GLARSSON Hien Quoc NGO Wei HONG Haiming WANG Debin HOU Jixin CHEN Zhe CHEN Zhangcheng HAO Geoffrey Ye LI Rahim TAFAZOLLI Yue GAO HVincent POOR Gerhard P.FETTWEIS Ying-Chang LIANG | 2021 | Science China(Information Sciences)2021，64，1： | 122 |
| 2 | Internet of Vehicles in Big Data Era显示文摘As the rapid development of automotive telematics,modern vehicles are expected to be connected through heterogeneous radio access technologies and are able to exchange massive information with their surrounding environment. By significantly expanding the network scale and conducting both real-time and long-term information processing, the traditional Vehicular AdHoc Networks(VANETs) are evolving to the Internet of Vehicles(Io V), which promises efficient and intelligent prospect for the future transportation system. On the other hand, vehicles are not only consuming but also generating a huge amount and enormous types of data, which is referred to as Big Data. In this article, we first investigate the relationship between Io V and big data in vehicular environment, mainly on how Io V supports the transmission, storage, computing of the big data, and how Io V benefits from big data in terms of Io V characterization,performance evaluation and big data assisted communication protocol design. We then investigate the application of Io V big data in autonomous vehicles. Finally, the emerging issues of the big data enabled Io V are discussed. | Wenchao Xu Haibo Zhou Nan Cheng Feng Lyu Weisen Shi Jiayin Chen Xuemin (Sherman) Shen | 2018 | IEEE/CAA Journal of Automatica Sinica2018，5，1： | 19 |
| 3 | Reconfigurable intelligent surfaces for smart wireless environments:channel estimation,system design and applications in 6G networks显示文摘Reconfigurable intelligent surface(RIS),one of the key enablers for the sixth-generation(6G)mobile communication networks,is considered by designers to smartly reconfigure the wireless propagation environment in a controllable and programmable manner.Specifically,an RIS consists of a large number of low-cost and passive reflective elements(REs)without radio frequency chains.The system gain of RIS wireless systems can be achieved by adjusting the phase shifts and amplitudes of the REs so that the desired signals can be added constructively at the receiver.However,an RIS typically has limited signal processing capability and cannot perform active transmitting/receiving in general,which leads to new challenges in the physical layer design of RIS wireless systems.In this paper,we provide an overview of the RIS-aided wireless systems,including the reflection principle,channel estimation,and system design.In particular,two types of emerging RIS systems are considered:RIS-aided wireless communications(RAWC)and RISbased information transmission(RBIT),where the RIS plays the role of the reflector and the transmitter,respectively.We also envision the potential applications of RIS in 6G networks. | Ying-Chang LIANG Jie CHEN Ruizhe LONG Zhen-Qing HE Xianqi LIN Chenlu HUANG Shilin LIU Xuemin(Sherman)SHEN Marco DI RENZO | 2021 | Science China(Information Sciences)2021，64，10： | 12 |
| 4 | Learning-Based Joint Resource Slicing and Scheduling in Space-Terrestrial Integrated Vehicular Networks显示文摘In this paper,we investigate the resource slicing and scheduling problem in the space-terrestrial integrated vehicular networks to support both delay-sensitive services(DSSs)and delay-tolerant services(DTSs).Resource slicing and scheduling are to allocate spectrum resources to different slices and determine user association and bandwidth allocation for individual vehicles.To accommodate the dynamic network conditions,we first formulate a joint resource slicing and scheduling(JRSS)problem to minimize the long-term system cost,including the DSS requirement violation cost,DTS delay cost,and slice reconfiguration cost.Since resource slicing and scheduling decisions are interdependent with different timescales,we decompose the JRSS problem into a large-timescale resource slicing subproblem and a small-timescale resource scheduling subproblem.We propose a two-layered reinforcement learning(RL)-based JRSS scheme to find the solutions to the subproblems.In the resource slicing layer,spectrum resources are pre-allocated to different slices via a proximal policy optimization-based RL algorithm.In the resource scheduling layer,spectrum resources in each slice are scheduled to individual vehicles based on dynamic network conditions and service requirements via matching-based algorithms.We conduct extensive trace-driven experiments to demonstrate that the proposed scheme can effectively reduce the system cost while satisfying service quality requirements. | Huaqing Wu Jiayin Chen Conghao Zhou Junling Li Xuemin(Sherman)Shen | 2021 | Journal of Communications and Information Networks2021，6，3： | 3 |
| 5 | Global patterns of hepatocellular carcinoma management from diagnosis to death: the BRIDGE Study显示文摘 | Joong‐Won Park Minshan Chen Massimo Colombo Lewis R. Roberts Myron Schwartz Pei‐Jer Chen Masatoshi Kudo Philip Johnson Samuel Wagner Lucinda S. Orsini Morris Sherman | 2015 | Liver Int2015，，9： | 3 |
| 6 | Early Management Experience of Perforation after ERCP显示文摘 | Guohua Li Youxiang Chen Xiaojiang Zhou Nonghua Lv Stuart Sherman | 2012 | Gastroenterology Research and Practice2012，，： | 2 |
| 7 | DEA model with shared resources and efficiency decomposition 显示文摘 | Chen Yao Du Juan Sherman H D | 2010 | European Journal of Operational Research2010，207，1： | 1 |
| 8 | Dependence of cardiac ^11C- meta-hydroxyephedrine retention on norepinephrine transporter density显示文摘 | Raffel DM Chen W Sherman PS | 2006 | J Nucl Med2006，47，9： | 1 |
| 9 | A B-spline approach for empirical mode decompositions显示文摘 | Qiuhui Chen Norden Huang Sherman Riemenschneider Yuesheng Xu | 2006 | Advances in Computational Mathematics (-)2006，，1： | 1 |
| 10 | Cybertwin-Assisted Mode Selection in Ultra-Dense LEO Integrated Satellite-Terrestrial Network显示文摘Ultra-dense low earth orbit(LEO)integrated satellite-terrestrial network(ULISTN)has become an emerging paradigm to support massive access of Internet of things(IoT)in beyond fifth generation mobile networks(B5G).In ULISTN,there are two communication modes:cellular mode and satellite mode,where IoT users assessing terrestrial small base stations(TSBSs)and terrestrial-satellite terminals(TSTs)respectively.However,how to optimize the network performance and guarantee self-interests of the operator and IoT users in ULISTN is a challenging issue.In this paper,we propose a cybertwin-assisted joint mode selection and dynamic pricing(JMSDP)scheme for effective network management in ULISTN,where cybertwin serves as the intelligent agent.In JMSDP,the operator determines optimal access prices of TSBSs and TSTs,while each user selects the access mode according to access prices.Specifically,the operator conducts the Stackelberg game aiming at maximizing average throughput depending on the mode selection results of IoT users.Meanwhile,IoT users as followers adopt the evolutionary game to choose an access mode based on the access prices provided by the operator.Simulation results show that the proposed JMSDP can improve the average throughput and reduce the delay effectively,comparing with random access(RA)and maximum rate access. | Xin Zhang Bo Qian Xiaohan Qin Ting Ma Jiachen Chen Haibo Zhou Xuemin(Sherman)Shen | 2022 | Journal of Communications and Information Networks2022，7，4： | 1 |
| 11 | DEA model with shared resources and efficiency decomposition 显示文摘 | Chen Yao Du Juan Sherman H D | 2010 | European Journal of Operational Research2010，207，1： | 1 |
| 12 | Com- pass-M1 Broadcast Codes in E2, E5b, and E6 Frequen- cy Bands 显示文摘 | GAO Xing-xin CHEN Alan LO Sherman | 2009 | IEEE Journal of Selected Topics in Signal Proceeding2009，3，04： | 1 |
| 13 | Estrogen upregulates endothelial nitric oxide synthase gene expression in fetal pulmonary endothelium显示文摘 | Jun SS Chen Z German Z Yuhanna IS Sherman TS | 1997 | Circ Res1997，81，3： | 1 |
| 14 | A B-spline approach for empirical mode decompositions显示文摘 | Qiuhui Chen Norden Huang Sherman Riemenschneider Yuesheng Xu | 2006 | Advances in Computational Mathematics (-)2006，，1： | 1 |
| 15 | A B-spline approach for empirical mode decompositions 显示文摘 | Chen Q H Huang N E Sherman R | 2006 | Advances in Computational Mathematics2006，24，1： | 1 |
| 16 | DEA model with shared resources and efficiency decomposition 显示文摘 | CHEN YAO DU JUAN SHERMAN DAVID H | 2010 | European Journal of Operational Research2010，，11： | 1 |
| 17 | DEA model with shared resources and efficiency decomposition 显示文摘 | Yao Chen Juan Du David Sherman H | 2010 | European Journal of Operational Research2010，207，： | 1 |
| 18 | A comparison of two fishery-independent survey programs used to define the population structure of American lobster, Humarus americanus, in the Gulf of Maine 显示文摘 | CHEN Y SHERMAN S WILSON C | 2006 | Fishery Bulletin2006，104，： | 1 |
| 19 | Riemenschneider, Construction of multivariate biorthogonal wavelets with arbitrary vanishing moments显示文摘 | Di-Rong Chen Bin Han Sherman D | 2000 | Advances in Computational Mathematics2000，13，2： | 1 |
| 20 | Small cell carcinoma of the cervix: treatment and survival outcomes of 188 patients显示文摘 | Joshua G. Cohen Daniel S. Kapp Jacob Y. Shin Renata Urban Alexander E. Sherman Lee-may Chen Kathryn Osann John K. Chan | 2010 | American Journal of Obstetrics and Gynecology2010，，4： | 1 |
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