Power Efficiency Maximization in Cognitive Radio Networks

D. J. Kadhim, Shimin Gong, Wenfang Xia, Wei Liu, W. Cheng
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引用次数: 15

Abstract

Cognitive radio technology is used to improve spectrum efficiency by having the cognitive radios act as secondary users to access primary frequency bands when they are not currently being used. In general conditions, cognitive secondary users are mobile nodes powered by battery and consuming power is one of the most important problem that facing cognitive networks; therefore, the power consumption is considered as a main constraint. In this paper, we study the performance of cognitive radio networks considering the sensing parameters as well as power constraint. The power constraint is integrated into the objective function named power efficiency which is a combination of the main system parameters of the cognitive network. We prove the existence of optimal combination of parameters such that the power efficiency is maximized. Then we reformulate the objective function to incorporate the throughput. According to different constraints or degree of significance, we may put proper weight to each term so that we could obtain more preferable combination of parameters. Computer simulations have given the optimal solution curve for different weights. We can draw the conclusion that if we put more emphasis on power efficiency, the transmit power is a more critical parameter, however if throughput is more important, the effect of sensing time is significant.
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认知无线网络的功率效率最大化
认知无线电技术通过让认知无线电在当前未被使用的主要频段充当辅助用户来访问主要频段,从而提高频谱效率。一般情况下,认知二次用户是由电池供电的移动节点,耗电是认知网络面临的最重要问题之一;因此,功耗被认为是一个主要的制约因素。本文研究了考虑感知参数和功率约束的认知无线网络的性能。功率约束被整合到功率效率目标函数中,该目标函数是认知网络主要系统参数的组合。证明了使功率效率最大化的最优参数组合的存在性。在此基础上,我们对目标函数进行了重新表述,以纳入吞吐量。根据不同的约束条件或重要程度,我们可以对每一项赋予适当的权重,从而得到更优的参数组合。计算机仿真给出了不同权重下的最优解曲线。我们可以得出结论,如果我们更重视功率效率,发射功率是一个更关键的参数,而如果更重要的吞吐量,传感时间的影响是显著的。
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