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Spectrum sensing for cognitive radio: A signal-processing perspective on signal-statistics exploitation

机译:认知无线电频谱感应:信号统计剥削的信号处理透视

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Future cognitive radios will require use of both established emitter databases and local spectrum sensing to optimize their performance. We view these techniques as ways of estimating an RF environment map (RFEM), which characterizes the position, directivity, power, and modulation type of all relevant RF emitters in a geographical region of interest. Cognitive radios will make their best decisions when they have the best RFEM information available. Good RFEM estimates are facilitated by spectrum-sensing algorithms that exploit the complex statistics of modern communication signals rather than relying on energy detection. We illustrate some of the ways that such statistics can be exploited using collected modern communications signals.
机译:未来的认知收音机需要使用建立的发射器数据库和本地频谱感测以优化其性能。我们将这些技术视为估计RF环境图(RFEM)的方式,其特征在于地理区域中所有相关RF发射器的位置,方向性,功率和调制类型。电子认知收音机将在他们拥有最佳RFEM信息时尽最佳决策。通过频谱感测算法促进了良好的RFEM估计,用于利用现代通信信号的复杂统计而不是依赖于能量检测。我们说明了可以使用收集的现代通信信号利用这种统计数据的一些方法。

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