Examinando por Autor "Ladino Vega, Ivan Dario"
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Ítem Modulación OFDM Utilizando WaveletsVillalobos Bernal, Sebastian Eduardo; Aldana Herrera, Fabian Andres; Ladino Vega, Ivan Dario; Gomez Paredes, Juan CarlosOFDM modulation consists of sending symbols on carriers that are othogonal.Fourier analysis refers a set of sinusoidal waves as an orthonormal basis, therefore the complex exponentials are used in OFDM modulation as the set of carries through the use of FFT; however, it is only necessary for carriers to constitute an orthogonal basis for a signal space in order to be used as carriers. Multiresolution analysis shows that wavelet functions also compound an orthonormal basis and as a consequence, can be used as carriers in an OFDM system. Wavelets have advantages over sinusoidal waves. An ODFM system sends sinusoidal waves during a finite interval of time, a process which requires windowing causing the spectrum associated to every carrier is of a decaying sinusoidal form corresponding to a sinc function, which owns lobes that stretch along all frequencies, making filtering produce a partial loss of spectral information; in contrast, wavelets' spectrum has a faster, smoother, exponential-like decay; thus filtering does not cause a significant loss of information. The wavelet spectrum form confers OFDM systems more robustness against inter-symbol interference and noise, as well as the possibility to reduce bandwidth through filtering more than it could be possible for a sinc spectrum form. The aim of this work, is to implement an OFDM system which uses wavelets as the carriers through the Discrete Wavelet Transform, and analyse its performance in terms of the Bit Error Rate (BER) for different values of signal-to-noise ratio in a Additive White Gaussian Noise (AWGN) wireless transmission environment; also, to simulate the BER response for different bandwidth in order to reduce it, so that the BER performance of the wavelet system equals the FFT system and thus, determining the improvement in spectral efficiency which is the ultimate feature to improve.