Overview of AI-based Algorithms for Network Slicing Resource Management in B5G and 6G

• Published in: International Wireless Communications and Mobile Computing Conference (Online) pp. 330 - 335
• Main Authors: DEBBABI, Fadoua, JMAL, Rihab, CHAARI, Lamia, AGUIAR, Rui Luis, GNICHI, Rayen, TALEB, Samar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 30.05.2022
• Subjects: 6G mobile communication; Artificial Intelligence; B5G; Network slicing; Quantum computing; Resource management; Standardization; Training; Wireless networks
• ISSN: 2376-6506
• DOI: 10.1109/IWCMC55113.2022.9824988

We are now in the early stage of the Fifth Generation (5G) commercialization, and its improved capabilities and unique features will revolutionize the present wireless network. The 3rd Generation Partnership Project (3GPP) is currently working on the 5G New Radio, also known as the worldwide standardization of 5G, which can operate across a wide variety of frequency bands from minus than 6GHz to mmWave (100GHz). Nonetheless, 5G will not be able to satisfy all requirements for the foreseeable future. Hence, Beyond 5G (B5G) and Sixth Generation (6G) have emerged as concepts representing Next Generation Wireless Networks (NGWNs). B5G and 6G networks will probably integrate Artificial intelligence-based services, tactile services, hybrid access, quantum computing, edge computing, and optical wireless communication. This paper describes potential background concepts relating to Network Slicing and artificial intelligence. We present the literature review by studying the impact of Artificial Intelligence with its promising methods, training models, and architectures to be integrated into B5G Network slicing to perform Resource Management.