Surface Acoustic Wave (SAW) technology rapidly expands in modern sensing applications. Temperature, pressure and gases can be measured by SAW structure, configurable to be interrogated wirelessly. Presently, SAW sensor signal conditioning is mainly oriented to read the input-to-output phase difference by using analog circuits. Digital solutions are few (or not) explored, and its feasibility to process SAW signals in real conditions is unknown. This article studies two digital methods based on cross-correlation function and Fourier transform. Here is explained how good (or accurate) these methods read the phase difference when one of its input signals has considerable noise and attenuation, situation very common in SAW technology. This study has never been performed up to now and particular attention is given here to prove its feasibility. Our outcomes indicated that cross-correlation has better results than Fourier transform. In attenuation, cross-correlation reads the phase difference properly, but it is recommendable to apply smooth filtering when noise is significant. This function was developed by LabVIEW platform, whose noise and attenuation were included.