الفهرس 
Orthogonal Frequency Division MultiplexingOnly 14 pages are availabe for public view
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Abstract
Orthogonal Frequency Division Multiplexing (OFDM) system is one of the modern techniques which utilized in wireless communication such as the next generations of mobile and High Definition Television (HDTV) broadcasting systems. These systems require high data rate transmissions to be compatible with modern user’s demands. So, the utilization of the available spectrum is required to be as efficient as possible. But, due to multipath propagation in mobile radio channel, the problem of ISI takes place. Thus, it is required to overcome ISI which causes signal distortion and in turn degradation of the communication system performance. OFDM multiplexing technique can overcome these aforementioned challenges. However, high data rates transmission not only producing high complexity of the signal processing, but also requires high storage space of the multimedia applications. So, this thesis suggests applying the compressive sensing paradigm based the wireless communication with OFDM modulation scheme to solve these challenges. Compressive sensing (CS) is a novel under-sampling paradigm for simple and fast data acquisition and compression. In traditional compression techniques, the signal is sampled with a sampling rate larger than or equal to the Shannon-Nyquist rate for a proper signal reconstruction. But, CS performs sampling for the sparse signal with a rate lower than the Shannon Nyquist while grantees the proper reconstruction of the compressed sparse signal by exploiting the sparsity property. Although, CS saves communication resources by reducing the required bandwidth and the required storing space, it degrades the signal to noise ratio. Initially, the thesis realizes the OFDM system and checking it with the well-known channel denoising techniques to stand on the best one that suits the realized system. Then, evaluates the OFDM system with respect to different scenarios of channel model. The thesis secondly, investigates various CS reconstruction algorithms to select the most suitable one which achieves the aforementioned challenges. Applying efficient CS on OFDM with best channel model lead to higher data rates, reducing ISI, increasing spectrum efficiency, saving communication resources, reducing computational complexity, and reducing processing time because of using the simple and fast CS acquisition and compression technique . On third, the performance of the proposed system of CS based wireless communication using OFDM as modulation scheme is evaluated for different image and audio samples in terms of peak signal to noise ratio (PSNR) and mean square error (MSE). Finally, the proposed system has been tested for different compression ratios to show how much the proposed system is a reliable one.