AI-assisted Mobility Management in Urban Environments using O-RAN

Key innovations in the context of 6G networks have given rise to ultra dense networks particularly influential in urban environments. Correspondingly, the network mandates a proactive mobility management system capable of administering optimized handover of the user equipment (UE) considering prevailing conditions of the operating environment. We aim to combine AI-assisted mobility management algorithms with Eclipse MOSAIC for evaluating AI-driven Intent Based Networking (IBN). Taking advantage of the Open RAN Alliance (O-RAN) standards, this article proposes a novel handover mechanism inter-linked with simulated urban environment coupled with a handover algorithm focused on ensuring UE Quality of Service (QoS) constraints. This paper is the first part of a series of papers and therefore includes a preliminary evaluation setup and is planned to be extended in subsequent work.