Abstract
A fully operative and efficient 5G network cannot be complete without the inclusion of artificial intelligence (AI) routines. Existing 4G networks with all-IP (Internet Protocol) broadband connectivity are based on a reactive conception, leading to a poorly efficiency of the spectrum. AI and its subcategories like machine learning and deep learning have been evolving as a discipline, to the point that nowadays this mechanism allows fifth-generation (5G) wireless networks to be predictive and proactive, which is essential in making the 5G vision conceivable. This paper is motivated by the vision of intelligent base stations making decisions by themselves, mobile devices creating dynamically-adaptable clusters based on learned data rather than pre-established and fixed rules, that will take us to a improve in the efficiency, latency, and reliability of the current and real-time network applications in general. An exploration of the potential of AI-based solution approaches in the context of 5G mobile and wireless communications technology is presented, evaluating the different challenges and open issues for future research.
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