Research On The Key Technologies Of Vertical Handoff In Radio Resource Management Of Heterogeneous Networks

With the rapid development of wireless communication industry, various wirelessaccess technologies emerging, in order to meet the growing needs of data andcommunication services, wireless resources worldwide will gradually shift to the nextgeneration of mobile communication networks. Future wireless communication networkwill be a seamless integration of heterogeneous wireless network based on all IP and whichcan support for multiple wireless access, wherein the vertical handoff technology as thekey technology of heterogeneous networks, has become the key technology and researchfocus in the field. In heterogeneous networks, there is large different between the receivedsignal stress in different access technologies, so the traditional horizontal handoff strategycan’t form the flavor and requirement in vertical handoff. One of the challenges is todesign efficient and reasonable vertical handoff strategy to meet the requirement ofseamless mobile management in different wireless networks.Firstly, based on the depth study of the result of domestic and international networkselection algorithm, this article fully consider the impact of vertical handover decisionattribute factors, and according to the characteristics of different attributes integrated themto the algorithms and programs to improve the efficiency and effectiveness of the verticalhandover. This article will introduce fuzzy neural network to the vertical handover decisionsolutions and algorithms, and problems of fuzzy neural network for the slow convergenceand easy to fall into local minimum solved by solutions proposed ant colony optimizationalgorithm based fuzzy neural network vertical handoff algorithm (ACO-FNN). Thealgorithm put factors as received signal strength, available bandwidth, the mobile terminalspeed into the pre-determination process, which can reduce the number of usersparticipating in handover, in cell selection stage, the initial parameter value is set by colonyoptimization algorithm to improve the fuzzy the accuracy of the neural network learningparameters. Simulation results show that the algorithm effectively reduces the number ofPing-Pong occurs, and reduces the congestion rate.The research work and results of this paper could provide references for the researchon fuzzy neural network based vertical handoff decision algorithms in heterogeneouswireless networks.