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Experience-based radio access technology selection in wireless environment

机译:无线环境中基于经验的无线接入技术选择

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摘要

Wireless heterogeneous environments are common reality today and will be even more in the future. This paper is focused on providing wireless access selection method for the future mobile terminals that will use naturally inspired algorithms for best network selection. The novel algorithm uses mobile terminal measurements from different radio access technologies within a given time window. The network selection is based on specified criteria, which number can be increased as needed. Each criterion is modeled with membership function associated with Fuzzy Logic controllers, which are optimized by using Particle Swarm Optimization. Each criterion is weighted, with aim to assign the influence on the decision for radio access network. Hence, our proposed algorithm implements past knowledge of the service performances of available wireless networks used by the mobile, to make a decision for network selection on given time intervals. Main contribution in the algorithm for wireless access network selection is in the usage of nature inspired algorithms, such as Particle Swarm Optimization — PSO, for optimization of Fuzzy Logic controllers, as well as usage of Genetic Algorithm for optimization of decision making based on multi-criteria inputs. The simulation analysis have shown that the proposed algorithm gives better probability of satisfied users compared to other existing wireless network selection algorithms.
机译:无线异构环境在当今已经很普遍,并且在将来会越来越多。本文的重点是为未来的移动终端提供无线接入选择方法,该方法将使用自然启发的算法进行最佳网络选择。该新颖算法在给定的时间窗口内使用来自不同无线电接入技术的移动终端测量。网络选择基于指定的标准,可以根据需要增加数量。每个标准都使用与模糊逻辑控制器关联的隶属函数进行建模,这些函数通过使用粒子群优化进行优化。每个标准都经过加权,目的是分配对无线电接入网络决策的影响。因此,我们提出的算法实现了移动台使用的可用无线网络的服务性能的以往知识,从而可以在给定的时间间隔内做出网络选择的决策。无线接入网选择算法的主要贡献在于使用了自然启发算法,例如用于模糊逻辑控制器优化的粒子群优化算法(PSO),以及用于基于多目标决策的遗传算法优化方法。标准输入。仿真分析表明,与现有的其他无线网络选择算法相比,该算法具有更好的满意用户概率。

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