Abstract
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.