AI-Driven Load Balancing in Paravirtualized 5G Networks: Architecture, Implementation, and Future Prospects

Abstract

With the rapid proliferation of services and the challenges faced by existing deployed technologies, a need arose for an advanced solution. This need culminated in the development of 5G technology to address the limitations of previous generations. However, despite being a relatively recent innovation and still in its pre-deployment phase, 5G networks already face significant load management issues at their peripheries due to the increasing number of services and applications. How can the integration of Artificial Intelligence (AI), particularly using supervised methods, optimize workload distribution in 5G networks? This paper presents a comprehensive literature review on 5G and AI, a case study of a paravirtualized 5G network enhanced with AI agents and explores the opportunities arising from the integration of these two technologies in bandwidth management.