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6G Mobile Networks: Emerging Technologies and Applications Ying-Chang Liang, Dusit Niyato, Erik G Larsson and Petar Popovski

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6G Mobile Networks: Emerging Technologies and Applications Ying-Chang Liang, Dusit Niyato, Erik G Larsson and Petar Popovski 6G mobile networks: Emerging technologies and applications Ying-Chang Liang, Dusit Niyato, Erik G Larsson and Petar Popovski The self-archived postprint version of this journal article is available at Linköping University Institutional Repository (DiVA): http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-170982 N.B.: When citing this work, cite the original publication. Liang, Y., Niyato, D., Larsson, E. G, Popovski, P., (2020), 6G mobile networks: Emerging technologies and applications, China Communications, 17(9), 90-91. https://doi.org/10.23919/JCC.2020.9205979 Original publication available at: https://doi.org/10.23919/JCC.2020.9205979 Copyright: Institute of Electrical and Electronics Engineers http://www.ieee.org/index.html YOU X H, et al. Sci China Inf Sci 1 SCIENCE CHINA Information Sciences . REVIEW . Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts Xiaohu YOU1,2*, Cheng-Xiang WANG1,2*, Jie HUANG1,2, Xiqi GAO1,2, Zaichen ZHANG1,2, Mao WANG1,2, Yongming HUANG1,2, Chuan ZHANG1,2, Yanxiang JIANG1,2, Jiaheng WANG1,2, Min ZHU1,2, Bin SHENG1,2, Dongming WANG1,2, Zhiwen PAN1,2, Pengcheng ZHU1,2, Yang YANG3,4, Zening LIU3, Ping ZHANG5, Xiaofeng TAO6, Shaoqian LI7, Zhi CHEN7, Xinying MA7, Chih-Lin I8, Shuangfeng HAN8, Ke LI8, Chengkang PAN8, Zhimin ZHENG8, Lajos HANZO9, Xuemin (Sherman) SHEN10, Yingjie Jay GUO11, Zhiguo DING12, Harald HAAS13, Wen TONG14, Peiying ZHU14, Ganghua YANG15, Jun WANG16, Erik G. LARSSON17, Hien Quoc NGO18, Wei HONG19,2, Haiming WANG19,2, Debin HOU19,2, Jixin CHEN19,2, Zhe CHEN19,2, Zhangcheng HAO19,2, Geoffrey Ye LI20, Rahim TAFAZOLLI21, Yue GAO21, H. Vincent POOR22, Gerhard P. FETTWEIS23 & Ying-Chang LIANG24 1National Mobile Communications Research Laboratory, School of Information Science and Engineering, Southeast University, Nanjing 210096, China; 2Purple Mountain Laboratories, Nanjing 211111, China; 3Shanghai Institute of Fog Computing Technology (SHIFT), ShanghaiTech University, Shanghai 201210, China; 4Research Center for Network Communication, Peng Cheng Laboratory, Shenzhen 518000, China; 5State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China; 6National Engineering Laboratory for Mobile Network Technologies, Beijing University of Posts and Telecommunications, Beijing 100876, China; 7National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China; 8China Mobile Research Institute, Beijing 100053, China; 9School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, U.K.; 10Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada; 11Global Big Data Technologies Centre (GBDTC), University of Technology Sydney, Ultimo, Sydney, NSW 2007, Australia; 12School of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, U.K.; 13School of Engineering, Institute for Digital Communications, Li-Fi Research and Development Centre, The University of Edinburgh, Edinburgh EH9 3JL, U.K.; 14Huawei Technologies Canada Co., Ltd, Ottawa K2K 3J1, Canada; 15Huawei Technologies, Shanghai 201206, China; 16Huawei Technologies, Hangzhou 310007, China; 17Department of Electrical Engineering (ISY), Link¨opingUniversity, Link¨oping 581 83, Sweden; 18Institute of Electronics, Communications & Information Technology (ECIT), Queen's University Belfast, Belfast BT3 9DT, U.K.; 19State Key Laboratory of Millimeter Waves, School of Information Science and Engineering, Southeast University, Nanjing 210096, China; 20School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta GA 30332, USA; 215G Innovation Centre, University of Surrey, Guildford GU2 7XH, U.K.; 22Princeton University, Princeton NJ 08544, USA; 23Vodafone Chair Mobile Communications Systems, Technische Universit¨atDresden, Dresden 01069, Germany; 24Center for Intelligent Networking and Communications (CINC), University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China Abstract 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 tech- nologies, network slicing, cell-free architecture, cloud/fog/edge computing, etc. 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-air- ground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6 GHz, 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. Keywords 6G, vision, network architecture, air interface and transmission technologies, space-air-ground- sea integrated network, full-spectrum, artificial intelligence, network security. Citation YOU X H, WANG C X, HUANG J, et al. Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts. Sci China Inf Sci, for review Table 1 A List of Abbreviations. 2D two-dimensional MBD mobile big data 3D three-dimensional MCS modulation coding scheme 3GPP 3rd generation partnership project MEC mobile edge computing 4G fourth generation MIMO multiple-input multiple-output 5G fifth generation ML machine learning 5G- 5G alliance for connected industries MLSE maximum likelihood sequence estima- ACIA and automation tion 5G 5G infrastructure public private part- MMSE minimum mean squared error PPP nership 6G sixth generation mMTC massive machine type communica- tions ACK acknowledgment mmWave millimeter wave A-CPI application-controller plane interface MPC multipath component A/D analog-to-digital MR maximum ratio AI artificial intelligence MRC maximum ratio combining AMF access and mobility management func- MRT maximum ratio transmission tion ANN artificial neural network MS mobile station AP access point MTC machine type communication AR augmented reality MUST multi-user superposition transmission ASK amplitude shift keying MZM Mach-Zehnder modulator AUSF authentication server function NAS non-access stratum * Corresponding author (email: [email protected], [email protected]) YOU X H, et al. Sci China Inf Sci 3 BB baseband NEF network exposure function BCH Bose-Chaudhuri-Hocquenghem NFV network functions virtualization BCJR Bahl, Cocke, Jelinek, and Raviv NFVI NFV infrastructure BER bit error rate NFV NFV management and orchestration M&O BPF bandpass filter NGMN next-generation mobile network B-RAN blockchain radio access network NG- next-generation radio access network RAN BS base stations NLOS non-line-of-sight BSS business support system NOMA non-orthogonal multiple access CC central controller NP non-deterministic polynomial CF cell-free NR new radio CGM continuous glucose monitoring NRF network function repository function CIR channel impulse response NR-V new radio vehicle CNN convolutional neural network NWDA network data analytics CoMP coordinated multi-point OAM orbital angular momentum COTS commercial off-the-shelf OFDM orthogonal frequency-division multi- plexing CPM continuous phase modulation OMA orthogonal multiple access CPU central processing units ONF open networking foundation CR cognitive radio O-RAN open radio access network CRC cyclic redundancy check OSS operations support system CSA cognitive service architecture OTFS orthogonal time frequency space CSI channel state information OWC optical wireless communication CT computed tomography P2P peer-to-peer C-V2X cellular vehicle to everything PAPR peak to average power ratio D/A digital-to-analog PCC parallel concatenated codes DAS distributed antenna system PCF policy control function D-CPI data-controller plane interface PDA placement delivery array DEN2 deep edge node and network PDF probability density function DetNet deterministic networking PDP power delay profile DL deep learning PLS physical layer security DN data network PSD power spectral
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