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Combined antenna selection and beamforming in cross-layer design for cognitive networks

机译:认知网络跨层设计中的组合天线选择和波束成形

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We investigate the performance of an antenna selection algorithm applied with precoding to improve the throughput performance of cognitive multiple-input multiple-output (MIMO) radios. We assume cognitive MIMO radios coexist in the same frequency band with the primary users. In such event, for concurrent spectrum access, cognitive nodes use beamforming techniques to cancel the mutual information between cognitive and primary users. In that, cognitive nodes exploit the degrees of freedom offered by MIMO systems to beamform the transmitted signal in an attempt to cancel interference at primary users. In the cross-layer design, cognitive nodes maximize an objective function for the link layer throughput where precoding is applied at the physical layer on the transmitted spatial multiplexed signals. We present a closed form solution for the overall throughput in-terms of the physical layer parameters. Numerical results are presented to show the efficacy of the proposed scheme for different network settings.
机译:我们研究与预编码一起应用的天线选择算法的性能,以提高认知多输入多输出(MIMO)无线电的吞吐量性能。我们假设认知MIMO无线电与主要用户在同一频带中共存。在这种情况下,对于并发频谱访问,认知节点使用波束成形技术来消除认知用户和主要用户之间的相互信息。在这种情况下,认知节点利用MIMO系统提供的自由度对发射信号进行波束形成,以消除主要用户的干扰。在跨层设计中,认知节点将链路层吞吐量的目标函数最大化,在物理层上对传输的空间复用信号应用预编码。我们为物理层参数的整体吞吐量提出了一个封闭式解决方案。数值结果表明了该方案在不同网络环境下的有效性。

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