A survey of 5G network systems: challenges and machine learning approaches

被引:79
作者
Fourati, Hasna [1 ]
Maaloul, Rihab [1 ]
Chaari, Lamia [1 ]
机构
[1] Univ Sfax, Digital Res Ctr SFAX CRNS, Lab Technol & Smart Syst LT2S, Sfax, Tunisia
关键词
5G cellular network; 5G services; 5G key technologies; 5G architectures; 5G challenges; ML solutions; Intelligence; SON; TO-DEVICE COMMUNICATIONS; BIG DATA ANALYTICS; OF-THE-ART; ARTIFICIAL-INTELLIGENCE; RESOURCE-ALLOCATION; CELLULAR NETWORKS; FUNCTION VIRTUALIZATION; WIRELESS COMMUNICATIONS; ENABLING TECHNOLOGIES; ANOMALY DETECTION;
D O I
10.1007/s13042-020-01178-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
5G cellular networks are expected to be the key infrastructure to deliver the emerging services. These services bring new requirements and challenges that obstruct the desired goal of forthcoming networks. Mobile operators are rethinking their network design to provide more flexible, dynamic, cost-effective and intelligent solutions. This paper starts with describing the background of the 5G wireless networks then we give a deep insight into a set of 5G challenges and research opportunities for machine learning (ML) techniques to manage these challenges. The first part of the paper is devoted to overview the fifth-generation of cellular networks, explaining its requirements as well as its key technologies, their challenges and its forthcoming architecture. The second part is devoted to present a basic overview of ML techniques that are nowadays applied to cellular networks. The last part discusses the most important related works which propose ML solutions in order to overcome 5G challenges.
引用
收藏
页码:385 / 431
页数:47
相关论文
共 231 条
  • [1] Network Function Virtualization in 5G
    Abdelwahab, Sherif
    Hamdaoui, Bechir
    Guizani, Mohsen
    Znati, Taieb
    [J]. IEEE COMMUNICATIONS MAGAZINE, 2016, 54 (04) : 84 - 91
  • [2] Next Generation 5G Wireless Networks: A Comprehensive Survey
    Agiwal, Mamta
    Roy, Abhishek
    Saxena, Navrati
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (03): : 1617 - 1655
  • [3] A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives
    Ahmed, Irfan
    Khammari, Hedi
    Shahid, Adnan
    Musa, Ahmed
    Kim, Kwang Soon
    De Poorter, Eli
    Moerman, Ingrid
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2018, 20 (04): : 3060 - 3097
  • [4] Deep Learning for Radio Resource Allocation in Multi-Cell Networks
    Ahmed, K., I
    Tabassum, H.
    Hossain, E.
    [J]. IEEE NETWORK, 2019, 33 (06): : 188 - 195
  • [5] REALIZING THE TACTILE INTERNET: HAPTIC COMMUNICATIONS OVER NEXT GENERATION 5G CELLULAR NETWORKS
    Aijaz, Adnan
    Dohler, Mischa
    Aghvami, A. Hamid
    Friderikos, Vasilis
    Frodigh, Magnus
    [J]. IEEE WIRELESS COMMUNICATIONS, 2017, 24 (02) : 82 - 89
  • [6] Al-Falahy N, 2017, IT PROF, V19, P12, DOI 10.1109/MITP.2017.9
  • [7] Efficient Cell Outage Detection in 5G HetNets Using Hidden Markov Model
    Alias, Multazamah
    Saxena, Navrati
    Roy, Abhishek
    [J]. IEEE COMMUNICATIONS LETTERS, 2016, 20 (03) : 562 - 565
  • [8] A Survey of Self Organisation in Future Cellular Networks
    Aliu, Osianoh Glenn
    Imran, Ali
    Imran, Muhammad Ali
    Evans, Barry
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2013, 15 (01): : 336 - 361
  • [9] Towards the fulfillment of 5G network requirements: technologies and challenges
    Alnoman, Ali
    Anpalagan, Alagan
    [J]. TELECOMMUNICATION SYSTEMS, 2017, 65 (01) : 101 - 116
  • [10] Enhanced Machine Learning Scheme for Energy Efficient Resource Allocation in 5G Heterogeneous Cloud Radio Access Networks
    AlQerm, Ismail
    Shihada, Basem
    [J]. 2017 IEEE 28TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC), 2017,