Innovative methods for the selection of bandpass sampling rate in cost-effective RF measurement instruments

Abstract

The modern instruments involved in the measurement on the telecommunication systems are generally based on suitable digital signal processing methods which provide the desired quantities by elaborating the acquired samples. To warrant suitable accuracy and repeatability as well as 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. However, 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, a number of tests have been performed on emulated and real DVB-T signals. An analysis of the benefits, in terms of computational burden and memory requirement, provided by the bandpass sampling implementation on RF measurement station has been carried out with reference to both nonparametric and parametric kinds of power spectrum density (PSD) estimators.