Enhanced energy detection using matched filter for spectrum sensing in cognitive radio networks

Abstract

Cognitive Radio (CR) deals with the designing of intelligent wireless communication systems through the use of transceivers that are capable of automatically detecting and accessing vacant communication channels in the radio bandwidth while avoiding the ones occupied, with the aim of maximizing the utilization of the Radio Frequency (RF) spectrum and minimizing the interference of users. In primary transmitter detection i.e. non-cooperative spectrum sensing, the licensed primary users (PUs) are detected based on the signal received by the unlicensed secondary users (SUs). This paper provides an insight into one such method, namely, the energy detection technique, which has low computational and implementation complexities, and is extremely generic. However, the detection of weak PU signals across a noisy channel is a challenging endeavor and calls for a more sophisticated approach. A matched filter can be used to obtain additional information regarding the channel activity, help individuate the transmitted pulses from the noise and reduce the effects of unlicensed signal interference. The proposed algorithm attains results from a matched filter and implements it within the energy detector, analyzing the signals over an Additive White Gaussian Noise (AWGN) channel for a range of Signal-to-Noise Ratios (SNRs), which are then evaluated through Receiver Operating Characteristic (ROC) curves with probability of detection (Pd) and probability of false alarm (Pf) as performance metrics.