Wide Band Spectrum Sensing of RF Signal with subNyquist Sampling for Cognitive Radio

摘要

For Cognitive Radio (CR) networks and systems, the necessary intelligence about the RF environment being a critical issue, spectrum sensing is an essential component. The need for very high sampling rate by the classical approach of Nyquist sampling rates is a crucial factor in the wideband spectrum sensing. In this paper we consider the problem of locating multiple, active sub-bands in a wide range of frequencies. A solution to the above problem is provided by means of a novel sensing scheme, based on subNyquist sampling called 'Multicoset Sampling'. The correlation matrix of a finite number of noisy samples is computed and processed through an estimator to detect the presence of occupied and vacant channels. The performance of this technique is evaluated by computing the probability of detecting the occupied channel as a function of number of samples, and the SNR parameters. Simulation results show a reliable detection at low SNR and limited number of samples.