Dynamic Handover Optimization Protocol to enhance energy efficiency within the A-LTE 5G network's two-tier architecture
DOI:
https://doi.org/10.59461/ijdiic.v3i3.124Keywords:
A-LTE, 5G, Handover, Mobility Management, Two-tier, Macrocell, FemtocellAbstract
Deploying small macrocell base stations, hence called femtocells, enhances the level of service provided to consumers inside as well as outside. However, the effective management of user mobility poses a significant challenge in their implementation. This paper focuses extensively on this challenge, specifically emphasizing a critical aspect of mobility management: handovers. Regarding macrocell femtocell 5G A-LTE two-tier networks, the decision-making process during handovers holds paramount importance. This research classifies and thoroughly examines decision algorithms concerning handovers, considering factors such as the speed of user equipment, financial considerations, interference, and received signal strength. Nevertheless, a significant number of these described decision algorithms overlook crucial aspects. Firstly, they often fail to account for cell selection when employing a scenario with just one macrocell and numerous femtocells; a hybrid access policy is used. Secondly, a significant number of those methods do not take the retention parameter for the user equipment into account, resulting in an increased occurrence of unnecessary handovers. To address these shortcomings, we propose a sophisticated handover decision algorithm. This novel approach considers various factors, including the individual's speed, received signal strength, time spent there, and the femtocell base station's access policy. Comparing our suggested algorithm to traditional decision algorithms that are only based on simulation, data shows that our proposed approach significantly lowers the frequency of unwanted handovers on received signal strength in the 5G network to improve the Energy Efficiency of the network by over 85%.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Umar Danjuma Maiwada, Kamaluddeen Usman Danyaro, Aliza Bt Sarlan, Aminu Abdulkadir Aliyu
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.