Details

Autor(en) / Beteiligte

• Xia, Dan
• Shi, Jianhua
• Wan, Ke
• Wan, Jiafu
• Martinez-Garcia, Miguel
• Guan, Xin

Titel

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

Ist Teil von

• IEEE wireless communications, 2023-06, Vol.30 (3), p.171-179

Ort / Verlag

New York: IEEE

Erscheinungsjahr

2023

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• 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.