The importance of spectral magnitude in signal through a noisy channels in data transmission

In this paper we present a novel technique that can be applied in data transmission noisy channels. The method is based on the reconstruction of one or two dimensional signal with finite support from only its Fourier transform magnitude computed from the converted original signal. This method is the Saxton and Gershberg iterative algorithm for reconstructing a non minimum phase sequence from magnitude, using this method we have proved that spectral magnitude is less sensitive to additive white Gaussian noise than spectral phase and signal. The algorithm is operated on converted non minimum to minimum phase signal by concentrating the higher energy on the left hand end sequence than the right hand end sequence, thus dealing with magnitude we have achieved a good performance at all SNR levels with limited extra computational complexity.