底层认知无线电中译码转发协同网络的低干扰中继选择

Chih‐Wen Chang, Po-Hsun Lin, S. Su
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引用次数: 26

摘要

在底层解码转发(DaF)协同认知无线电(CR)网络中,在不违反干扰温度(IT)限制的情况下,采用传统的最大最小选择法来选择最优中继。但是,最大最小选择可能会对主系统(PS)造成一些额外的干扰,从而降低所谓的传输比(TR)。需要注意的是,TR被新定义为二次系统(SS)容量增益与由于SS活动导致的PS容量损失之比。为了提高TR值,我们在博弈论定价函数的激励下,考虑了SS对PS的干扰影响,提出了一种新的低干扰中继选择方法。然而,使用低干扰选择,可能并不总是选择最佳中继。为了澄清这一现象,将静止最优概率定义为所提方案选择最优继电器的概率。此外,还分析了低干扰选择对SS容量的影响。仿真结果表明,该方法不仅分析结果准确,而且在TR值和总容量方面性能优越,可以实现更高的频谱效率。相信本文的研究结果可以为评估频谱效率提供另一种观点,并在未来激发更多有趣和重要的研究课题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A low-interference relay selection for decode-and-forward cooperative network in underlay cognitive radio
In the underlay decode-and-forward (DaF) cooperative cognitive radio (CR) network, an optimal relay can be selected by the conventional max-min selection on the condition of not violating the interference temperature (IT) limit. However, the max-min selection may cause some extra amount of interference to the primary system (PS) such that the so-called transfer ratio (TR) can be lower. Note that TR is newly defined as the ratio of the secondary system's (SS's) capacity gain to the PS's capacity loss due to the activities of SS. In order to improve the TR value, we are motivated by the pricing function in Game theory to propose a novel low-interference relay selection by taking the impacts of the interference from SS to PS into consideration. Using the low-interference selection, however, the optimal relay may not always be picked. To clarify this phenomenon, the still optimal probability is defined as the probability of selecting the optimal relay by the proposed scheme. In addition, the impact of the low-interference selection on the SS's capacity is also analyzed. The simulation results prove not only the exactness of the analytical results but also the superior performance in terms of the TR value and total capacity which also indicates that a higher spectrum efficiency can be achieved. It is believed that the results of this paper can provide an alternative viewpoint of evaluating the spectrum efficiency and inspire more interesting and important research topics in the future.
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