近年來，感知無線電被視為可解決頻譜使用效率不高和日漸增加的頻譜需求的方法。在感知無線電中，頻譜感測是一項非常重要的議題。如果觀察的頻譜範圍很廣，即稱為廣域頻譜感測。然而，廣域的頻譜感測有其技術上的困難。隨著壓縮感測技術的發展，我們取樣可以低於耐奎氏速率。

在本篇論文中，我們提出的架構運用MWC (Modulated Wideband Converter) 做低於耐奎氏速率的取樣。取樣之後，再利用壓縮感測的還原技術，找出support，support為有可能被使用的頻帶。之後再用Psudoinverse運算還原訊號。然而我們最主要的目的是做頻譜感測，所以我們並不需要將訊號還原至耐奎氏速率，用低速率的訊號去做頻譜感測，這樣可以降低運算複雜度。此外，因為頻域的原點等於時域序列的總和，所以我們就用總和 (Summation)運算去取代快速傅立葉轉換 (Fast Fourier Transform)處理器。 因此，我們所提出之頻譜感測系統的運算複雜度比原本使用耐奎氏速率取樣的適應性多訊窗頻譜(Adaptive Multi-taper Spectrum Detector)偵測器降低了93.3%。

In recent years, cognitive radio, which has the ability of spectrum sensing and self-adjustment
transmission power and modulation, is regarded as an effective solution to the problem of ineffective
spectrum utilization. Spectrum sensing is one of the most important issue in cognitive
radio, which needs to find out where the spectrum hole is. The cognitive radio has to detect
spectrum holes in a wide frequency range that can be viewed as wideband spectrum sensing.
However, wideband spectrum sensing has its technical challenges. Fortunately, with the development
of compressed sensing, it’s possible to acquire a signal at a sub-Nyquist rate. In
other words, we can use lower rate ADC instead the higher rate one.
In this thesis, the proposed architecture uses modulated wideband converter for sub-Nyquist
rate sampling. It samples with more than one branch by low rate ADCs, and then the compressive
sensing recovery algorithm recovers support which is implied where the probable
active band is. Although the modulated wideband converter needs more hardware components,
its rate is far below the Nyquist rate. It implies that is cheaper than the Nyquist rate
components, and it is easy to implement. However, the reconstructive procedure is computationally
complex in conventional modulated wideband converter, because it interpolates the
reconstructive signal to Nyquist rate. In order to reduce computational complexity, the signal
is not reconstruct completely. Nevertheless, the main purpose of the proposed architecture is
to do spectrum sensing, the low rate signal is included the narrow band information. Since
the original point in frequency domain is the summation of sequence in time domain, the
fast Fourier transform processor is replaced by summation procedure. The spectrum sensing
system can reduce computational loads by 93:3% compared to adaptive multitaper spectral
detector with Nyquist rate sampling.

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