Compressive Sensing over OFDM Systems

Abstract

Communications development is the fastest-growing Nowadays, so the need and the constant demand for faster and more reliable communication methods have increased. Here, the compressive sensing appeared to meet this need. Compressive sensing is a new method of sampling that is not rendered to the Shannon-Nyquist law. In this thesis, we studied the effects of orthogonal (Fourier and wavelet) modulation with compressive sensing modeling on the characteristics of the signal that are used for medical and security applications. The compressed image performance has been tested in three ways and transmitted via the FFT-OFDM system and the DWT-OFDM system, under various baseband modulation schemes with the effect of white Gaussian noise. Then we compared the transmission performance via FFT-OFDM versus DWT-OFDM. From the simulation is observed that the wave-based OFDM system is better than the Fourier-based OFDM system Furthermore, the wavelets better than Fourier in the utilization of Bandwidth, Unlike FFT that allocates part of Bandwidth of the cyclic prefix (CP), and thus part of it is wasted.