Hard Decision Fusion based Cooperative Spectrum Sensing in Cognitive Radio System

Abstract

Cooperative spectrum sensing was proposed to combat fading, noise uncertainty, shadowing, and even hidden node problem due to primary users (PUs) activity that is not spatially localized. It improves the probability of detection by collaborating to detect PUs signal in cognitive radio (CR) system as well. This paper studies cooperative spectrum sensing and signal detection in CR system by implementing hard decision combining in data fusion centre. Through computer simulation, we evaluate the performances of cooperative spectrum sensing and signal detection by employing OR and AND rules as decision combining. Energy detector is used to observe the presence of primary user (PU) signal. Those results are compared to non-cooperative signal detection for evaluation. They show that cooperative technique has better performance than non-cooperative. Moreover, signal to noise ratio (SNR) with greater than or equal 10 dB and 15 collaborated users in CR system has optimal value for probability of detection.