Digital Twin and Artificial Intelligence for Intelligent Planning and Energy-Efficient Deployment of 6G Networks in Smart Factories

被引:6
|
作者
Xia, Dan [1 ]
Shi, Jianhua [2 ]
Wan, Ke [3 ]
Wan, Jiafu [1 ]
Martinez-Garcia, Miguel [4 ]
Guan, Xin [5 ]
机构
[1] South China Univ Technol, Sch Mech & Automot Engn, Guangzhou, Peoples R China
[2] Shanxi Datong Univ, Sch Mech & Elect Engn, Datong, Peoples R China
[3] Hong Kong Polytech Univ, Dept Ind & Syst Engn, Hong Kong, Peoples R China
[4] Loughborough Univ, Human Machine Syst, Loughborough, England
[5] Keio Univ, Sch Sci & Technol, Tokyo, Japan
关键词
6G mobile communication; Network topology; Systems architecture; Bandwidth; Throughput; Energy efficiency; Production facilities; CHALLENGES; REQUIREMENTS;
D O I
10.1109/MWC.017.2200495
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Terahertz and higher frequency band wireless communication technologies represent the most promising spectrums for 6G networks. Compared to 4G/5G networks, 6G networks operate in a higher frequency band with greater propagation and penetration losses, which may bring serious challenges to network planning and green communications. The digital twin (DT) technology is able to model and simulate wireless networks to improve network performance and deployment efficiency. The artificial intelligence (AI) algorithms provide strong self-evolution and self-optimization capabilities, enabling the generation of an intelligent network. To achieve intelligent, energy-efficient, and cost-effective deployment of 6G networks in smart factories, this article proposes a DT-based system architecture and a mobile-enhanced edge computing-cloud collaborative mechanism for handling diverse and complex data. Moreover, a DT and AI-based method is developed to enable intelligent planning and deployment of 6G networks in factories, which improves network performance while reducing operational costs.
引用
收藏
页码:171 / 179
页数:9
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