A Comparison of Three Classes of Spectrum Sensing Techniques

Abstract

Spectrum sensing is used to identify the (temporarily) unused (licensed) frequency bands and as such plays a key role in dynamic spectrum access. Spectrum sensing is currently being investigated by a number of researchers. In this paper we compare the performance of three classes of algorithms-energy detectors, autocorrelation detectors, and the cyclic autocorrelation detector. The focus of the study is on the trade-offs of the three approaches under fixed false alarm and detection probabilities.