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An interference avoidance method using two dimensional genetic algorithm for multicarrier communication systems

机译:利用二维遗传算法的多载波通信系统干扰避免方法

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摘要

In this article, we suggest a two-dimensional genetic algorithm (GA) method that applies a cognitive radio (CR) decision engine which determines the optimal transmission parameters for multicarrier communication systems. Because a CR is capable of sensing the previous environmental communication information, CR decision engine plays the role of optimizing the individual transmission parameters. In order to obtain the allowable transmission power of multicarrier based CR system demands interference analysis a priori, for the sake of efficient optimization, a two-dimensional GA structureis proposed in this paper which enhances the computational complexity. Combined with the fitness objective evaluation standard, we focus on two multi-objective optimization methods: The conventional GA applied with the multi-objective fitness approach and the non-dominated sorting GA with Pareto-optimal sorting fronts. After comparing the convergence performance of these algorithms, the transmission power of each subcarrier is proposed as non-interference emission with its optimal values in multicarrier based CR system.
机译:在本文中,我们建议一种二维遗传算法(GA)方法,该方法应用认知无线电(CR)决策引擎,该引擎确定多载波通信系统的最佳传输参数。因为CR能够感知先前的环境通信信息,所以CR决策引擎扮演着优化各个传输参数的角色。为了获得基于多载波的CR系统的允许发射功率,需要先验地进行干扰分析,为进行有效的优化,提出了一种二维GA结构,提高了计算的复杂度。结合适合度客观评价标准,我们着眼于两种多目标优化方法:采用多目标适应度方法的常规GA和具有帕累托最优排序前沿的非主导排序GA。在比较了这些算法的收敛性能之后,在基于多载波的CR系统中,提出了每个子载波的发射功率作为其无干扰值的无干扰发射。

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