Analysis of data science and AI-enabled 6G wireless communication networks

Current networks, such as 4G and the forthcoming 5G networks, may not be capable to fully congregate quickly emerging traffic strains due to the proliferation of smart fatal, infrastructures and 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, a 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: an intelligent-sensing, a data-analytics, intelligent-control and smart-application, with the goal of realizing patterns sighting, smart-resource management, automatic network adjustment, and intelligent-service provisioning. We then 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 go into detail about how to implement these methods to maximize the network's performance. We also emphasize key areas for future study and possible clarifications for AI-enabled 6G networks, together with as computational efficiency, algorithm resilience, hardware-development, and energy-management.