Vertical Handover Decision Based on RBF Approach for Ubiquitous Wireless Networks

S. Kunarak
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引用次数: 2

Abstract

Next generation wireless networks are integrated the multiple wireless access technologies in order to provide the users with the best connection. The vertical handover decision algorithm is an important role to guarantee the seamless mobility in single mobile terminal. In this paper, we apply the radial basis function neural network (RBFNN) for the decision making process in vertical handover based on received signal strength, mobile speed and monetary cost metrics. The simulation results indicate that the proposed approach outperforms in reducing the unnecessary handover and connection dropping but increasing the grade of service with comparing the other two methods as threshold and back propagation neural network.
基于RBF方法的无所不在无线网络垂直切换决策
下一代无线网络集成了多种无线接入技术,为用户提供最佳连接。垂直切换决策算法是保证单个移动终端无缝移动的重要手段。本文将径向基函数神经网络(RBFNN)应用于基于接收信号强度、移动速度和货币成本指标的垂直切换决策过程。仿真结果表明,与阈值和反向传播神经网络两种方法相比,该方法在减少不必要的切换和断开连接以及提高服务等级方面具有明显的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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