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Cognitive radio system with advanced environment awareness engine using integrated propagation models and multiple antennas

机译:具有高级环境意识引擎的认知无线电系统使用集成传播模型和多个天线

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Cognitive radio systems adaptively adjust their radio parameters based on the feedback from the electromagnetic environment. Therefore, it is expected that cognitive radio systems will have better performance if they are integrated with accurate site-specific propagation modeling. Our group has long standing expertise in propagation modeling utilizing geo-spatial tools and indoor building models, and has focus on integrating these models as part of the environment awareness engine in cognitive radios. In this paper, we present the preliminary results for a multi-antenna based spectrum sensing algorithm with adaptive thresholds. The results show that, an almost fixed detection rate of 85% can be achieved for a mobile cognitive radio in an urban environment when the thresholds are set based on the path loss information provided by site-specific propagation modeling. On the other hand, the spectrum sensing algorithm with a fixed threshold shows a great variability in the detection performance, going as low as 65% in regions with heavy fading, which leads to harmful interference.
机译:认知无线电系统基于来自电磁环境的反馈,自适应地调整其无线电参数。因此,如果与准确的站点特定的传播建模集成,则预计认知无线电系统将具有更好的性能。我们的集团在使用地理空间工具和室内建筑模型的传播建模方面拥有长期的专业知识,并专注于将这些模型集成为认知收音机中环境意识引擎的一部分。在本文中,我们提出了一种具有自适应阈值的多天线的频谱感测算法的初步结果。结果表明,当基于由现场特定于传播建模提供的路径损耗信息设置阈值时,可以在城市环境中的移动认知无线电来实现85%的几乎固定检测率。另一方面,具有固定阈值的频谱传感算法显示了检测性能的巨大可变性,在具有沉重衰落的区域中低至65%,这导致有害干扰。

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