AI-Based Approaches for Handover Optimization in 5G New Radio and 6G Wireless Networks
Ahmed F. Ashour, Mostafa M. Fouda
Abstract
In the future, communication networks such as fifth-generation new radio (5G NR) and sixth-generation (6G) will require large data rates and capacities. As a result, mmWave and terahertz (THz) bands are being employed to meet these demands. Unfortunately, these high-frequency bands are susceptible to high path loss, necessitating the deployment of small cells. This, in turn, calls for the installation of a massive number of base stations to cover the whole area. The sheer number of cells and users in such a setup can lead to interruptions in calls when users switch cells, a process known as handover (HO). This has a negative effect on the quality of service (QoS) and the quality of experience (QoE). Therefore, this survey focuses on exploring and comparing artificial intelligence (AI)-based intelligent HO solutions that can optimize HO in 5G NR and 6G networks.