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Application of Compressive Sensing in Cognitive Radio Communications: A Survey

机译：压缩感知在认知无线电通信中的应用：一项调查

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摘要

Compressive sensing (CS) has received much attention in several fields such as digital image processing, wireless channel estimation, radar imaging, and cognitive radio (CR) communications. Out of these areas, this survey paper focuses on the application of CS in CR communications. Due to the under-utilization of the allocated radio spectrum, spectrum occupancy is usually sparse in different domains such as time, frequency, and space. Such a sparse nature of the spectrum occupancy has inspired the application of CS in CR communications. In this regard, several researchers have already applied the CS theory in various settings considering the sparsity in different domains. In this direction, this survey paper provides a detailed review of the state of the art related to the application of CS in CR communications. Starting with the basic principles and the main features of CS, it provides a classification of the main usage areas based on the radio parameter to be acquired by a wideband CR. Subsequently, we review the existing CS-related works applied to different categories such as wideband sensing, signal parameter estimation and radio environment map (REM) construction, highlighting the main benefits and the related issues. Furthermore, we present a generalized framework for constructing the REM in compressive settings. Finally, we conclude this survey paper with some suggested open research challenges and future directions.
机译：压缩感测（CS）在数字图像处理，无线信道估计，雷达成像和认知无线电（CR）通信等多个领域受到了广泛关注。在这些领域之外，本调查论文重点介绍CS在CR通信中的应用。由于分配的无线电频谱的未充分利用，频谱占用通常在诸如时间，频率和空间之类的不同域中稀疏。频谱占用的这种稀疏性质激发了CS在CR通信中的应用。在这方面，考虑到不同领域的稀疏性，一些研究人员已经在各种环境中应用了CS理论。在这个方向上，本调查论文详细介绍了与CS在CR通信中的应用有关的最新技术。从CS的基本原理和主要特征开始，它根据宽带CR要获取的无线电参数对主要使用区域进行分类。随后，我们回顾了现有的CS相关工作，这些工作适用于不同类别，例如宽带传感，信号参数估计和无线电环境图（REM）构造，着重介绍了其主要优点和相关问题。此外，我们提出了在压缩环境中构建REM的通用框架。最后，我们以一些建议的开放研究挑战和未来方向来结束本调查论文。

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