Analysis of Data Science and AI-enabled 6G Wireless Communication Networks

Abstract

Current networks (such as 4G and the forthcoming 5G networks) may not be capable of fully congregating quickly emerging traffic strains due to the proliferation of smart fatal, infrastructures and the explosion of diverse applications with varying necessities. As a result, 6G network research has already seen participation from both the private sector and the academic community. Recently, an innovative paradigm has emerged for the intelligent design and optimization of 6G networks based on the combination of artificial intelligence (AI) and data science (DS). Therefore, this article proposes an AI-enabled architecture for 6G networks, which is alienated into four layers: intelligent sensing, data analytics, intelligent control, and smart application, to realize patterns sighting, smart resource management, automatic network adjustment, and intelligent service provisioning. We go over the uses of DS&AI methods in 6G networks, such as AI-enhanced mobile edge computing, intelligent mobility, and smart-spectrum management, and how to implement these methods to maximize the network’s performance. We also emphasize key areas for future study and clarifications for AI-enabled 6G networks, together with computational efficiency, algorithm resilience, hardware development, and energy management.