The Effect of Variable Factors on the Handover Performance for Ultra Dense Network

TL;DR

This paper investigates how variable factors like TTT, gNB density, and user velocity affect 5G handover performance in ultra-dense networks, using a simulation to optimize handover parameters.

Contribution

It provides a comprehensive analysis of 5G handover management by evaluating the impact of TTT, gNB density, and user velocity through simulation, offering optimization insights.

Findings

Optimal TTT values vary with gNB density and user velocity.

Higher gNB density increases handover frequency and failures.

Adjustable TTT improves handover performance under different conditions.

Abstract

With wireless communication technology development, the 5G New Radio (NR) has been proposed and developed for a decade. This advanced mobile communication technology has more advancements, such as higher system capacity, higher spectrum efficiency, higher data rates, and so on. In 5G, Ultra- Dense Network (UDN) is deployed for increasing the system capacity and frequency reuse to meet high application requirements. The architecture of 5G UDN is to realize the dense and flexible deployment of smaller general Node B (gNB). However, the increased capacity of applying UDN in 5G is anticipated at the cost of increased signal interference, increased handover times, and increased handover failures. The Time to Trigger (TTT) is one of the most important factors in handover frequency which is deserved to be detected. Moreover, the density of the 5G gNBs influences the handover times and performance as well. In this work, we provide a compendium of 5G handover management. A downlink system-level simulator for 5G handover is built and utilized to evaluate the effect of different TTT values and densities of gNBs on the 5G handover. In addition, different velocities of Traffic Users (TUs) have been applied to the simulation system. From the simulation results, the handover performance has been analyzed and optimized by applying adjustable TTT under different densities of gNBs which will help people have a better understanding of the selection and effect of proper TTT, UDN, and different velocities of TUs on 5G handover performance.