A major challenge in spectrum sensing for cognitive radio (CR) applications is the very high sampling rates involved, which imposes significant demands on the signal acquisition technology. This has given impetus to applying compressive sensing (CS) as a sub-Nyquist sampling paradigm for CR-type wireless signals which exhibit sparsity in certain domains. CS architectures like the random demodulator (RD) and compressive multiplexer (CM) can be used for CR spectral sensing, though both are inherently restricted in terms of the signal classes they can effectively process. To address these limitations, this study presents two unified RD and CM-based CS architectures that seamlessly integrate precolouring and the multitaper spectral estimator into their respective structures to facilitate efficient sensing of both digitally modulated and narrowband signals, along with popular CR-access technologies like orthogonal frequency division multiplexing . A significant feature of these unified CS architectures is they do not require a priori knowledge of either the input signal or modulation scheme, while a tristate spectral classifier is introduced to afford notably enhanced spectrum access opportunities for unlicensed secondary users. A critical performance evaluation corroborates that both unified architectures demonstrate consistently superior CS results and robustness across a broad range of CR-type signals, modulations and access technologies.

中文翻译：

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随机解调器和压缩多路复用器体系结构的统一压缩感测范例

频谱感测面临的主要挑战 认知无线电（CR）应用是涉及的非常高的采样率，这对信号采集技术提出了很高的要求。这推动了应用压缩感测（CS）作为CR型无线信号的子奈奎斯特采样范式，在某些领域表现出稀疏性。CS架构，例如随机解调器 （RD）和 压缩多路复用器（CM）可以用于CR频谱感测，尽管它们在有效处理的信号类别方面都有内在的限制。为了解决这些局限性，本研究提出了两种基于RD和CM的统一CS架构，它们无缝集成了预着色和多锥 频谱估计器进入其各自的结构，以促进对数字调制和窄带信号的有效检测，以及流行的CR接入技术，例如 正交频分复用 。这些统一的CS体系结构的一个重要特征是，它们不需要输入信号或调制方案的先验知识，而引入了三态频谱分类器，为无执照的二级用户提供了显着增强的频谱接入机会。一项关键性能评估证明，这两种统一架构在各种CR类型的信号，调制和访问技术中均能始终如一地展现出出色的CS结果和鲁棒性。