Cellular, Wide-Area, and Non-Terrestrial IoT: A Survey on 5G Advances and the Road Toward 6G

被引:344
作者
Vaezi, Mojtaba [1 ]
Azari, Amin [2 ]
Khosravirad, Saeed R. [3 ]
Shirvanimoghaddam, Mahyar [4 ]
Azari, M. Mahdi [5 ]
Chasaki, Danai [6 ]
Popovski, Petar [7 ]
机构
[1] Villanova Univ, Dept Elect & Comp Engn, Villanova, PA 19085 USA
[2] Ericsson AB, Ericsson Res, S-16480 Stockholm, Sweden
[3] Nokia Bell Labs, Radio Syst Res, Murray Hill, NJ 07974 USA
[4] Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW 2006, Australia
[5] Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust SnT, L-4365 Luxembourg, Luxembourg
[6] Villanova Univ, Dept ECE, Villanova, PA 19085 USA
[7] Aalborg Univ, Dept Elect Syst, DK-9220 Aalborg, Denmark
关键词
5G mobile communication; Industrial Internet of Things; Broadband communication; Wireless sensor networks; Long Term Evolution; Ultra reliable low latency communication; Cellular networks; IoT; IIoT; 5G; 6G; SigFox; LoRa; LTE-M; NB-IoT; security; reliability; survival time; service availability; energy-efficiency; blockchain; SDN; non-terrestrial; satellite; UAV; 3D; NOMA; random access; grant-free access; turbo code; LDPC; polar; deep learning; federated learning; NONORTHOGONAL MULTIPLE-ACCESS; MACHINE-TYPE COMMUNICATIONS; ANALOG FOUNTAIN CODES; PARITY-CHECK CODES; ENERGY-EFFICIENT; RESOURCE-ALLOCATION; ANOMALY DETECTION; POWER ALLOCATION; MASSIVE MIMO; COMMUNICATION DESIGN;
D O I
10.1109/COMST.2022.3151028
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The next wave of wireless technologies is proliferating in connecting things among themselves as well as to humans. In the era of the Internet of Things (IoT), billions of sensors, machines, vehicles, drones, and robots will be connected, making the world around us smarter. The IoT will encompass devices that must wirelessly communicate a diverse set of data gathered from the environment for myriad new applications. The ultimate goal is to extract insights from this data and develop solutions that improve quality of life and generate new revenue. Providing large-scale, long-lasting, reliable, and near real-time connectivity is the major challenge in enabling a smart connected world. This paper provides a comprehensive survey on existing and emerging communication solutions for serving IoT applications in the context of cellular, wide-area, as well as non-terrestrial networks. Specifically, wireless technology enhancements for providing IoT access in the fifth-generation (5G) and beyond cellular networks, and communication networks over the unlicensed spectrum are presented. Aligned with the main key performance indicators of 5G and beyond 5G networks, we investigate solutions and standards that enable energy efficiency, reliability, low latency, and scalability (connection density) of current and future IoT networks. The solutions include grant-free access and channel coding for short-packet communications, non-orthogonal multiple access, and on-device intelligence. Further, a vision of new paradigm shifts in communication networks in the 2030s is provided, and the integration of the associated new technologies like artificial intelligence, non-terrestrial networks, and new spectra is elaborated. In particular, the potential of using emerging deep learning and federated learning techniques for enhancing the efficiency and security of IoT communication are discussed, and their promises and challenges are introduced. Finally, future research directions toward beyond 5G IoT networks are pointed out.
引用
收藏
页码:1117 / 1174
页数:58
相关论文
共 452 条
[1]  
Abbas R., 2017, ARXIV170707401
[2]   Performance Analysis of Short Analog Fountain Codes [J].
Abbas, Rana ;
Shirvanimoghaddam, Mahyar ;
Huang, Tao ;
Li, Yonghui ;
Vucetic, Branka .
2019 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), 2019,
[3]   Novel Design for Short Analog Fountain Codes [J].
Abbas, Rana ;
Shirvanimoghaddam, Mahyar ;
Huang, Tao ;
Li, Yonghui ;
Vucetic, Branka .
IEEE COMMUNICATIONS LETTERS, 2019, 23 (08) :1306-1309
[4]   A Novel Analytical Framework for Massive Grant-Free NOMA [J].
Abbas, Rana ;
Shirvanimoghaddam, Mahyar ;
Li, Yonghui ;
Vucetic, Branka .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2019, 67 (03) :2436-2449
[5]  
Abbasi F., 2020, ARXIV201016144
[6]  
Abdel-Aziz M.K., 2018, IEEE GLOB COMM CONF
[7]  
Abdul-Ghani HA, 2018, INT J ADV COMPUT SC, V9, P355
[8]  
Abu Alsheikh M, 2016, IEEE NETWORK, V30, P22, DOI 10.1109/MNET.2016.7474340
[9]   Mobile Encrypted Traffic Classification Using Deep Learning: Experimental Evaluation, Lessons Learned, and Challenges [J].
Aceto, Giuseppe ;
Ciuonzo, Domenico ;
Montieri, Antonio ;
Pescape, Antonio .
IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2019, 16 (02) :445-458
[10]  
Adame T., 2019, ARXIV191206086