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Application of Analytic Wavelet Transform for Signal Detection in Nyquist Folding Analog-to-Information Receiver

机译:分析小波变换在奈奎斯特折叠模数 - 信息接收器中的信号检测中的应用

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One of the challenges in Cognitive Radio (CR) is efficiently monitoring a wideband radio frequency (RF) spectrum in order to identify unoccupied bands. Compressive Sensing (CS) has recently been proposed to address this problem. Typical CS techniques, however, involve random projections followed by a computationally intensive signal reconstruction process. Since spectral monitoring does require full signal reconstruction - only identification of occupied regions to avoid - we propose a novel spectrum monitoring approach based on the Nyquist Folding Receiver (NYFR) in conjunction with the Analytic Wavelet Transform. The NYFR performs analog compression via a non-uniform sampling process that induces a chirp-like modulation on each received signal. This induced modulation can be measured using time-frequency analysis techniques to determine the original RF band of origin without full signal reconstruction. This paper investigates the feasibility of using the Analytic Wavelet Transform to perform NYFR information recovery in support of CR wideband spectrum sensing.
机译:认知无线电(CR)中的一个挑战是有效地监视宽带射频(RF)频谱以识别未占用的频带。最近提出了压缩感应(CS)来解决这个问题。然而,典型的CS技术涉及随机投影,然后涉及计算密集的信号重建过程。由于光谱监测确实需要完全信号重建 - 仅识别占用区域以避免 - 我们提出了一种基于奈奎斯特折叠接收器(NYFR)的新型频谱监测方法,与分析小波变换结合。 NYFR通过非均匀采样过程执行模拟压缩,该过程在每个接收信号上引起啁啾样调制。可以使用时频分析技术测量该诱导调制,以确定没有完全信号重建的原始原点的原始RF频带。本文研究了使用分析小波变换来执行NYFR信息恢复的可行性,以支持CR宽带频谱感测。

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