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Energy Efficient Heterogeneous Network Selection Method Based on Fuzzy Neural Network

机译:基于模糊神经网络的高效节能异构网络选择方法

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摘要

Heterogeneous network selection algorithm can be expected to play an increasingly important role in the future wireless communication network. Due to the difference in energy consumption of different networks, selecting appropriate access network according to energy consumption characteristics and applications for Mobile Terminal (MT) can effectively extend battery life. In this paper, a fuzzy neural network based energy efficient network selection method is proposed. To select the optimal network and achieve the best balance between performance and energy consumption, the proposed method takes network bandwidth, signal strength, Quality of Service (QoS) and energy consumption into account. A novel energy efficiency utility function is proposed to calculate the energy utility value of different applications based on real-time and non-real-time service. And the calculated energy utility value together with other QoS parameters is input into Fuzzy Neural Network (FNN) for subsequent processing. Finally, the most appropriate network can be selected by comparing the inference results of fuzzy neural network. Computer simulations show that the proposed algorithms can reduce the energy consumption for MT effectively, and has superior performance in terms of access blocking probability and packet dropping probability.
机译:异构网络选择算法有望在未来的无线通信网络中发挥越来越重要的作用。由于不同网络的能耗差异,根据能耗特征和移动终端(MT)的应用选择合适的接入网络可以有效地延长电池寿命。提出了一种基于模糊神经网络的节能网络选择方法。为了选择最佳网络并在性能和能耗之间达到最佳平衡,该方法考虑了网络带宽,信号强度,服务质量(QoS)和能耗。提出了一种新颖的能效效用函数,用于基于实时和非实时服务来计算不同应用的能效值。并将计算出的能源效用值与其他QoS参数一起输入到模糊神经网络(FNN)中进行后续处理。最后,通过比较模糊神经网络的推理结果,可以选择最合适的网络。计算机仿真表明,所提出的算法可以有效降低MT的能耗,并且在访问阻塞概率和丢包概率方面均具有优越的性能。

著录项

  • 来源
    《Journal of information and computational science》 |2014年第10期|3373-3385|共13页
  • 作者单位

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

    School of Electronic Engineering, Beijing University of Posts and Telecommunications Beijing 100876, China,Beijing Key Laboratory of Work Safety Intelligent Monitoring, Beijing University of Posts and Telecommunications, Beijing 100876, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Future Wireless Communication; FNN; Network Selection; Energy-efficient; Battery Life;

    机译:未来的无线通信;FNN;网络选择;高效节能;电池寿命;

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