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Power optimization in cognitive networks with hybrid intelligent algorithms

机译:具有混合智能算法的认知网络中的功率优化

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In this paper, we introduce a hybrid strategy containing pattern search (PS) optimization and genetic algorithm (GA) to resolve the problem of power allocation in cognitive radio networks. Considering the fluctuant interference thresholds in cognitive networks, an approach for solving the problem of coexistence between licensed users and cognitive users is proposed first. Then, based on the analyses of outage probability for cognitive users, a corresponding objective function with regard to the power allocation over Rayleigh fading channels is obtained. Due to the nonlinearity and complexity of this power optimization problem, it is uneasy to figure it out directly by using traditional methods, such as common mathematical deduction or linear programming. Inspired by the concept of intelligent algorithms, we try to employ the scheme of combining PS optimization and GA method, which are both efficient intelligent algorithms to resolve this difficulty. Furthermore, the numerical results are encouraging and show that the proposed approach is worthy of consideration in solving the problem of optimal power allocation in cognitive networks.
机译:在本文中,我们介绍了包含模式搜索(PS)优化和遗传算法(GA)的混合策略,以解决认知无线电网络中的功率分配问题。考虑到认知网络中的波动干扰阈值,提出了一种解决许可用户与认知用户之间的共存问题的方法。然后,基于认知用户的中断概率的分析,获得了对瑞利衰落通道的功率分配的相应目标函数。由于这种功率优化问题的非线性和复杂性,通过使用传统方法,例如常见的数学扣除或线性编程,直接弄清楚它是不安的。灵感来自智能算法的概念,我们尝试采用PS优化和GA方法组合PS优化和GA方法的方案,这些方法都是有效的智能算法来解决这个困难。此外,数值结果是令人鼓舞的,并表明所提出的方法值得考虑解决认知网络中最佳功率分配问题。

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