Machine Learning in Beyond 5G/6G Networks-State-of-the-Art and Future Trends

被引：47

作者：

Rekkas, Vasileios P. ^{[1
]}

Sotiroudis, Sotirios ^{[1
]}

Sarigiannidis, Panagiotis ^{[2
]}

Wan, Shaohua ^{[3
]}

Karagiannidis, George K. ^{[4
]}

Goudos, Sotirios K. ^{[1
]}

机构：

[1] Aristotle Univ Thessaloniki, Sch Phys, ELEDIA AUTH, Thessaloniki 54124, Greece

[2] Univ Western Macedonia, Dept Informat & Telecommun Engn, Kozani 50100, Greece

[3] Zhongnan Univ Econ & Law, Sch Informat & Safety Engn, Wuhan 430073, Peoples R China

[4] Aristotle Univ Thessaloniki, Sch Elect & Comp Engn, Thessaloniki 54124, Greece

来源：

ELECTRONICS | 2021年 / 10卷 / 22期

基金：

中国国家自然科学基金;

关键词：

6G; wireless communications; artificial intelligence; machine learning; RESOURCE-ALLOCATION; HANDOVER MANAGEMENT; WIRELESS NETWORKS; POWER ALLOCATION; BEAM SELECTION; DEEP; OPTIMIZATION; CHALLENGES; PREDICTION; COMMUNICATION;

D O I：

10.3390/electronics10222786

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important role in realizing and optimizing 6G network applications. In this paper, we present a brief summary of ML methods, as well as an up-to-date review of ML approaches in 6G wireless communication systems. These methods include supervised, unsupervised and reinforcement techniques. Additionally, we discuss open issues in the field of ML for 6G networks and wireless communications in general, as well as some potential future trends to motivate further research into this area.

引用

下载

页数：28

共 50 条

[1] Unsupervised Machine Learning in 6G Networks - State-of-the-art and Future Trends
Rekkas, Vasileios P.
Sotiroudis, Sotirios
Sarigiannidis, Panagiotis
Karagiannidis, George K.
Goudos, Sotirios K.
2021 10TH INTERNATIONAL CONFERENCE ON MODERN CIRCUITS AND SYSTEMS TECHNOLOGIES (MOCAST), 2021,
[2] Business Opportunities for Beyond 5G and 6G Networks
Nidhi
Mihovska, Albena
Kumar, Ambuj
Prasad, Ramjee
2022 25TH INTERNATIONAL SYMPOSIUM ON WIRELESS PERSONAL MULTIMEDIA COMMUNICATIONS (WPMC), 2022,
[3] Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future
Nawaz, Syed Junaid
Sharma, Shree Krishna
Wyne, Shurjeel
Patwary, Mohammad N.
Asaduzzaman, Md
IEEE ACCESS, 2019, 7 : 46317 - 46350
[4] Machine learning and quantum computing for 5G/6G communication networks - A survey
M S.
International Journal of Intelligent Networks, 2022, 3 : 197 - 203
[5] 5G, 6G, and Beyond: Recent advances and future challenges
Fatima Salahdine
Tao Han
Ning Zhang
Annals of Telecommunications, 2023, 78 : 525 - 549
[6] 5G, 6G, and Beyond: Recent advances and future challenges
Salahdine, Fatima
Han, Tao
Zhang, Ning
ANNALS OF TELECOMMUNICATIONS, 2023, 78 (9-10) : 525 - 549
[7] Artificial intelligence (AI) and machine learning (ML) for beyond 5G/6G communications
Matin, Mohammad Abdul
Goudos, Sotirios K.
Wan, Shaohua
Sarigiannidis, Panagiotis
Tentzeris, Emmanouil M.
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING, 2023, 2023 (01)
[8] Artificial intelligence (AI) and machine learning (ML) for beyond 5G/6G communications
Mohammad Abdul Matin
Sotirios K. Goudos
Shaohua Wan
Panagiotis Sarigiannidis
Emmanouil M. Tentzeris
EURASIP Journal on Wireless Communications and Networking, 2023
[9] USAGE OF NETWORK SIMULATORS IN MACHINE-LEARNING-ASSISTED 5G/6G NETWORKS
Wilhelmi, Francesc
Carrascosa, Marc
Cano, Cristina
Jonsson, Anders
Ram, Vishnu
Bellalta, Boris
IEEE WIRELESS COMMUNICATIONS, 2021, 28 (01) : 160 - 166
[10] Physical layer security for beyond 5G/6G networks: Emerging technologies and future directions
Irram, Fauzia
Ali, Mudassar
Naeem, Muhammad
Mumtaz, Shahid
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2022, 206

← 1 2 3 4 5 →