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Circular sparse rulers based on co-prime sampling for compressive power spectrum estimation

机译：基于共质数采样的圆形稀疏标尺用于压缩功率谱估计

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One of the main challenges in cognitive radio systems is the development of fast algorithms for spectrum sensing of wideband signals. To alleviate sampling requirements, several strategies have been proposed, relying on the fact that only covariance information is of interest. Under this premise, this paper solves the design of low rate covariance samplers by developing a multicoset sampling strategy based on co-prime samplers, achieving higher compression ratios than previous solutions. The designed sampling patterns constitute a family of circular sparse rulers, which can be implemented with only two analog-to-digital converters working in parallel, and operating at sampling frequencies significantly lower than the Nyquist rate.
机译：认知无线电系统的主要挑战之一是开发用于宽带信号频谱感测的快速算法。为了减轻采样要求，已经提出了几种策略，这取决于仅关注协方差信息的事实。在此前提下，本文通过开发基于互质采样器的多陪集采样策略，解决了低速率协方差采样器的设计问题，实现了比以前的解决方案更高的压缩率。设计的采样模式构成了一系列的圆形稀疏标尺，只有两个并行工作的模数转换器才能实现，并且它们的采样频率远低于奈奎斯特速率。

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