An Adaptive Algorithm for Energy Detection in Cognitive Radio Networks

Spectrum sensing plays a major role in cognitive radio (CR) networks to enhance the throughput of secondary users (SUs) at the same time protecting primary users (PUs) from harmful interference. Among all the available spectrum sensing techniques, energy detection is simple, because of its incoherent nature. However, performance of conventional energy detection deteriorates in low signal to noise ratio (SNR) regions. Performance of the detector also declines because of the inappropriate decision threshold. In this paper, an adaptive threshold based energy detection scheme is proposed in order to make the best trade off between probability of miss detection and false alarm. Numerical results shows that proposed scheme gives better performance than the conventional one.