A New Method of Spectrum Sensing in Cognitive Radio for Dynamic and Randomly Modelled Primary Users

Abstract

In this study, a new spectrum sensing method for cognitive radio (CR) is proposed for primary user (PU) signals which are modelled as random with unknown power. It is also assumed that, being dynamic, the PU might exhibit multiple status changes in the channel within the sensing period. As a novel approach for detecting dynamic and randomly modelled PUs, we propose a cumulative sum based weighted energy detector (CuS-WED) that only utilizes the samples between the last status change point (LSCP) of the PU and the end of the sensing period contrary to using all the observed data samples in the sensing period. It is shown that the proposed sensing strategy provides noticeable performance improvement in detecting dynamic and randomly modelled PUs. Probability of detection performance of the proposed sensing scheme is investigated for strictly one, at most two, and at most three status changes of the PU. Based on simulation results, it is concluded that the proposed method performs better than the other existing techniques, especially for low probability of false alarm values.