Sampling schemes and detection algorithms for wideband spectrum sensing

This paper establishes a unified model for sub-Nyquist sampling and discusses different aliasing patterns inherent in sub-Nyquist sampling. Several sub-Nyquist sampling schemes are considered within the unified model. This paper also develops multi-channel detection for wideband spectrum sensing following a Bayesian rule based upon the new performance metrics we defined in earlier work. The paper shows that generalized co-prime sampling exhibits similar sensing performance to that of random sampling for the same performance metrics and detection algorithms, and is much easier to implement. Moreover, integer undersampling, which corresponds to the simplest sub-Nyquist sampling scheme and leads to periodic aliasing, appears to be advantageous over the more sophisticated sub-Nyquist sampling schemes in the regime that better protects the primary system.