Hybrid Cooperative Spectrum Sensing Algorithm for Cognitive Radio Networks

Abstract

Cognitive radio (CR) promises to tackle the challenge of spectrum scarcity by enabling spectrum sharing between secondary and primary users. In this regard, several spectrum sensing approaches have been proposed to maintain spectrum sharing without interfering the primary user (PU) activities. These approaches have different levels of computational complexity and accuracy. Despite the level of accuracy, none of the spectrum sensing approaches can overcome the hidden node problem. Therefore, this paper aims to tackle this problem by proposing a hybrid cooperative spectrum sensing (HCSS) algorithm. The proposed HCSS deploys the approaches of energy detection (ED) and cyclostationary feature detection (CFD) to detect the PU’s channel occupancy. Furthermore, OR-rule is deployed in order to minimize the interference of secondary users (SUs) on PU. The proposed HCSS is analyzed and compared against the non-cooperative case of ED and CFD and subject to AWGN and Rayleigh fading. The proposed HCSS algorithm is found to outperform ED and CFD in terms of probability of detection at various levels of signal-to-noise ratios (SNR).