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A relative rate utility based distributed power allocation algorithm for Cognitive Radio Networks

机译:一种关于认知无线电网络的相对速率效用基于分布式功率分配算法

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In an underlay Cognitive Radio Network, multiple secondary users coexist geographically and spectrally with multiple primary users under a constraint on the maximum received interference power at the primary receivers. Given such a setting, one may ask “how to achieve maximum utility benefit at the secondary users given the imposed interference temperature constraint”? In an attempt at answering this question, we introduce a measure of the marginal secondary utility per unit primary interference (termed as relative rate utility) and propose a distributed algorithm that tries to maximize this measure. We present selected computer based MonteCarlo simulation results, demonstrating the effectiveness of the introduced measure, and the improved performance of the proposed algorithm.
机译:在底层认知无线电网络中,多个辅助用户在地理上和光谱上共存,在主接收器处的最大接收的干扰功率上的约束下使用多个主用户。鉴于这样的设置,可以询问“如何在给予强加的干扰温度约束的二级用户处实现最大实用权限”?在回答这个问题时,我们介绍了每单位初级干扰(称为相对率实用程序)的边际次级实用程序的衡量标准,并提出了一种试图最大化该措施的分布式算法。我们呈现基于计算机的Montecarlo仿真结果,展示了引入的衡量标准的有效性,以及所提出的算法的性能。

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