Multiband spectrum access plays an essential role in cognitive radio systems so as to increase the network’s throughput through wideband spectrum sensing. It includes identifying the number of subbands comprising a wide spectrum by edge detection, and also examining their occupancy through primary user detection techniques. Despite the offered accuracy of the wavelet-based approaches, their complexity becomes a drawback. Remarkably, the features revealing property of cepstral analysis and its implementation simplicity make it a suitable candidate for signal detection. Motivated by these reasons, this paper presents a wideband spectrum sensing approach based on cepstral analysis. First, we propose the differential log spectral density algorithm for the edge detection phase in order to detect the spectral boundaries within the wideband of interest. Also, we present a mathematical framework of the proposed algorithm and an expression for the detection threshold of the proposed detector is derived. The simulation results have showed a superior performance of the edge detection algorithm to different wavelet-based techniques at low-to-medium noise power. Used in conjunction with denoising, the proposed edge detector shows good detection results at low signal-to-noise ratio. For the primary user detection phase, we introduce the improved passband autocepstrum detector to tackle the misdetection problem of noise-like signals and it outperforms different state-of-the-art techniques. Finally, the uncertainty problem of the subbands center frequencies is addressed and the baseband autocepstrum detector is introduced as a potential solution to improve signal detection in frequency selective fading.

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基于倒频谱分析的认知无线电宽带频谱感知方法

多频带频谱访问在认知无线电系统中起着至关重要的作用，以通过宽带频谱感测提高网络的吞吐量。它包括通过边缘检测来识别包含宽频谱的子带的数量，并通过主要用户检测技术检查其占用率。尽管基于小波的方法具有很高的准确性，但是它们的复杂性却成为一个缺点。引人注目的是，倒频谱分析的特征揭示性及其易于实现的特性使其成为信号检测的合适候选者。由于这些原因，本文提出了一种基于倒频谱分析的宽带频谱感知方法。首先，我们为边缘检测阶段提出了差分对数谱密度算法，以检测感兴趣宽带内的谱边界。此外，我们提出了所提出算法的数学框架，并得出了所提出检测器的检测阈值的表达式。仿真结果表明，在中低噪声功率下，边缘检测算法的性能优于其他基于小波的技术。结合去噪使用，提出的边缘检测器在低信噪比下显示出良好的检测结果。在主要用户检测阶段，我们推出了改进的通带自动倒谱检测器，以解决类似噪声信号的误检测问题，并且其性能优于其他最新技术。最后，解决了子带中心频率的不确定性问题，引入了基带自动倒谱检测器作为改善频率选择性衰落信号检测的潜在解决方案。