Hybrid Handover Decision Using Neuro-Fuzzy Logic Approach for Heterogeneous Wireless Networks

Abstract

This paper decides about the vertical handover which is a significant process in the fifth generation (5G), using neuro-fuzzy logic that works between artificial neural network and fuzzy logic of heterogeneous wireless networks has 3 categories as Wireless Local Area Network (WLAN), Long Term Evolution-Advanced (LTE-A), and Mobile Worldwide Interoperability for Microwave Access (Mobile WiMAX). In addition, determine parameters affecting the handover decision of wireless communication such as received signal strength (RSS), mobile speed, and bandwidth to enter the handover decision process of neuro-fuzzy and the simulation of a structure uses data measured from parameters. The conditions of handover decision are threshold value and dwell time that prevent connection quality and unnecessary handover from decreasing. The purpose of this paper is to make users satisfied with the quality of service (QoS) and reduce the number of handovers and blocked calls. The research result found that the neuro-fuzzy algorithm has better performance when compared with fuzzy logic and back-propagation neural network methods. Consequently, the neuro-fuzzy illustrates the number of handovers and the number of blocked calls on average decrease by 38% and 26% when compared with the back-propagation neural network and decrease by 59% and 36% when compared with the fuzzy logic method, respectively.