Mobility Management in 5G Heterogeneous Networks: A Scheme for Reducing Handover Failures

Mobile/cellular communication has become very popular in recent decades and has evolved considerably. Cellular communications are shifting towards heterogeneous inter-connectivity. Ultra-dense heterogeneous networks (HetNets) employing small cells (SCs) within a macro cell's coverage area represent a highly promising strategy for boosting both capacity and coverage in 5G cellular networks. An ultra-dense network (UDN) refers to a setup where the number of Radio Access Technologies (RATs) present in a specific geographic location is increased. An ultra-dense network (UDN) is a setup in which the number of Radio Access Technologies (RATs) in a given geographic area is enhanced. As a result, the areas covered by each RAT start to overlap. Small base stations (SBSs) are situated close together in a UDN. Consequently, a single user equipment (UE) might pick up signals from multiple SBS, leading to significant inter-cell interference. This scenario typically arises due to a delayed handover. In environments with densely packed small cells, inter-cell interference is prevalent, causing deterioration in signal quality and subpar service for users. In this respect, we deal with mobility management from the point of view of users' mobility support in multi-RAT and multi-layer environments. We aim to reduce handover failures due to the unavailability of resources at the target base station (BS)/cell/RAT. We implemented a handover strategy that lowers the number of dropped handover calls by using a semi-Markov mobility prediction algorithm for handover control. This allows for the reservation of resources in the destination base station ahead of time, considerably reducing the amount of handover failures. The suggested scheme's findings were validated using a MATLAB simulation of an environment containing tiny cells with various radio access methods. According to the simulation results, predicting the next position of the user equipment resulted in lesser handover call dropping as opposed to new call blocking because they were not expected and thus resources were not prepared for them.