郭强, 张晓萌, 朱若函. 基于粒子群优化的模糊神经网络垂直切换算法[J]. 微电子学与计算机, 2015, 32(8): 12-18,23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.003
引用本文: 郭强, 张晓萌, 朱若函. 基于粒子群优化的模糊神经网络垂直切换算法[J]. 微电子学与计算机, 2015, 32(8): 12-18,23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.003
GUO Qiang, ZHANG Xiao-meng, ZHU Ruo-han. A PSO-fussy Neuron Based Access Selection in Heterogeneous Wireless Networks[J]. Microelectronics & Computer, 2015, 32(8): 12-18,23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.003
Citation: GUO Qiang, ZHANG Xiao-meng, ZHU Ruo-han. A PSO-fussy Neuron Based Access Selection in Heterogeneous Wireless Networks[J]. Microelectronics & Computer, 2015, 32(8): 12-18,23. DOI: 10.19304/j.cnki.issn1000-7180.2015.08.003

基于粒子群优化的模糊神经网络垂直切换算法

A PSO-fussy Neuron Based Access Selection in Heterogeneous Wireless Networks

  • 摘要: 针对异构网络融合场景中各种无线接入技术的选择,提出一种基于粒子群算法优化的模糊神经网络的垂直切换算法(PSO-FNN).该算法由对信号强度的前向差分预测模块、预判决模块、模糊神经网络处理模块和接入判决模块四个模块组成.其中差分预测模块可以预测出下一时刻的接收信号强度,这样可以缩短切换触发时间,提高判决精确性.预判决模块的执行可以减少进入模糊神经网络模块的样本数.模糊神经网络模块考虑了网络接收信号强度、网络负载、网络带宽和用户终端的移动速度四种判决因素,并采用了改进后的搜索能力更好的粒子群算法进行优化.仿真结果表明,该算法选择的网络在业务响应时间和吞吐量等方面具有更好的性能,提高了用户服务质量.

     

    Abstract: In view of a variety of wireless access technology selection in the integrated environments of heterogeneous networks, an improved PSO-FNN-based vertical handoff algorithm is proposed. The algorithm consists of four modules including forward difference prediction of received signal strength, pre-decision, fuzzy neural network processing and the decision of network selection. And it is combined with the forward difference prediction for the signal strength of next time to improve the handoff accuracy. By applying the pre-decision module, the number of samples entering into fuzzy neural network is decreased. Received signal strength, network bandwidth, network load, terminal moving speed are taken into account as the decision factors in the fuzzy neural network processing module. And using the improved PSO which shows better search ability to optimize FNN. The simulations show that the proposed algorithm can select the network which has better performance in terms of service response time and throughout and can improve customer service quality.

     

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