New Algorithms For The Optimal Selection Of The Bandpass Sampling Rate In Measurement Instrumention

The modern measurement instruments involved in telecommunication systems are generally based on suitable digital signal processing methods which provide the desired quantities by elaborating the digitized samples. To meet the accuracy and repeatability required by the telecommunication applications and to warrant the alias-free sampling (Nyquist-Shannon theorem), the measurement instruments are usually forced to operate with high sampling frequencies, long observation periods and very fast measurement algorithms. It is worth noting that fixed the observation period, a reduction in the sampling rate directly leads to a reduction in the number of samples to be stored in memory, and consequently in the computational burden and the processing time of the measurement algorithm. If bandpass signals are involved, as it happens in modern telecommunication systems, the bandpass sampling theory could be employed to significantly reduce the sampling rate, without any replica overlapping. This opportunity is very attractive for both instrument designers and users since it allows optimizing the hardware resources through a more efficient employment. The choice of the bandpass sampling rate is a not trivial task, and wrong values may cause aliasing phenomena and affect the accuracy of measurement results. In this paper, two original algorithms, particularly useful to both instrument designers and users, are proposed to automatically select the sampling rate when bandpass signals have to be measured. To assess and validate the efficiency and the suitability of bandpass sampling criteria proposed, preliminary tests were performed on emulated DVB-T signals