Misdetection Probability Analyses of OFDM Signals in Energy Detection Cognitive Radio Systems

Abstract

Cognitive radio (CR) networks are an intelligent wireless communication technology that is aware of its surrounding environment. The main process of the cognitive radio is spectrum sensing. Energy detection (ED) method was found to be a promising candidate for spectrum sensing in the CR networks. However, the detection performance of the ED method is susceptible to noise fluctuations at the receiver side, known as noise uncertainty. To obtain better performance when noise uncertainty impacts ED process, it is necessary to incorporate a dynamic signal detection based on sensing threshold adaptation. In this paper, the influence of noise uncertainty and dynamic threshold adaptation for the ED of signals transmitted using orthogonal frequency division modulation (OFDM) is investigated. The major contribution of this work is the analyses of the influence of different parameters including: modulation constellations, noise uncertainty level, dynamic threshold and signal to noise ratio values on a probability of received signal misdetection. Simulation results show that a combination of some of the analysed parameters can significantly improve ED process for OFDM signals.