# Machine Learning-Based Solutions for Handover Decisions in Non-Terrestrial Networks
## 1 Introduction
### Non-Terrestrial Networks Overview  
This section is very important because it gives a deep understanding of the topic studied, which is how to include satellite communication in new radio 5G communication (NR 5G). Since the goal of the 3 GPP in Rel-17 was to specify the improvements found for NR NTN, a focus was placed on LEO and GEO as well as implied compatibility to accommodate high-altitude platform stations and air-to-ground scenarios. In addition to enhancing current data collection features, 3 GPP Release 18 will look at how AI approaches might increase air interface capabilities. Moreover, 3 GPP Release 18 will improve NR data collecting in the context of the self-organizing network (SON) by automating RAN planning, configuration, management, optimization, and healing, SON reduces the need for human involvement [12]. Minimization of drive testing (MDT) gives operators the ability to set up typical UEs to gather and submit measurement data, reducing the need for traditional drive testing. The work on Release-18 will take care of SON features left over from Release 17 and data gathering for random access channel (RACH) optimization. Therefore, the process in this research includes problem analysis, which means identifying some main challenges in non-terrestrial networks and deep comprehension of mobility management. A non-terrestrial network is a network or network segment that uses radio frequency (RF) resources mounted on satellites and includes satellite communications networks, high altitude platform systems (HAPS), and air-to-ground networks as described in Figure 1. Typically, a non-terrestrial network includes the following components: A GEO satellite is supplied by one or more sat-gateways that are installed throughout the satellite targeted coverage; one or more sat-gateways that connect the non-terrestrial network to a public data network (e.g., regional or even continental coverage) [11]. We assume that each UE in a cell only has access to one satellite gateway. A non-GEO satellite is subsequently connected to one or more satellite gateways at once. The system makes sure that there is enough time between each serving satellite to complete mobility anchoring and handover while maintaining service and feeder connection continuity. Both transparent and regenerative (with onboard processing) payloads are possible for satellite implementation. The satellite often produces many beams over a service region that is bounded by its field of view [13]. The beam imprints are typically elliptical. In NTN, we have three different sorts of links: a feeder connection, also known as a radio link, connects a satellite to a ground station, while a service link connects user equipment to the satellite. Inter-satellitelinks (ISL), which are additional links if there is a constellation of satellites, are optional. Regenerative payloads on the satellites are necessary for this. ISL may function in optical or RF frequency bands.  
While a constellation of LEO and MEO satellites is utilized to provide services in both the Northern and Southern hemispheres, GEO satellites and UAS are employed to provide continental or regional service. In certain instances, the constellation may even offer coverage of the entire world, including the polar regions. In contrast to the GEO system, the LEO satellite system has many advantages such as efficient bandwidth usage, low propagation delay, and low power consumption at user terminals and satellites. However, in contrast to the GEO satellite system, the coverage area of LEO satellites is not constant. This is because satellites move asynchronously to the earth, handing them off between ground stations as they pass through different regions of the earth. Therefore, mobility management for LEO satellite systems is more difficult than for GEO systems. In some LEO satellite systems, the satellites communicate with each other using inter-satellite links (ISL).