Enhancing Cognitive Radio Spectrum Sensing: A Comparative Analysis of Energy Detection and Matched Filter Detection in Diverse Fading Channels

Spectrum sensing is a vital part of cognitive radio technology. Cognitive Radio (CR) continuously senses the spectrum so as to identify the unoccupied bands and assign them to the CR users. To sense the vacant band, three different spectrum sensing techniques are used, namely energy detection (ED), matched filter detection (MFD), and cyclo-stationary detection. Energy detection is the most widely used technique as it does not require any prior knowledge of the primary signal and, hence has considerably lower complexity than other systems. ED is the optimal technique to detect unknown signal if the noise power is known. In this, the CR user senses the absence or presence of primary user based in the received signal energy. As ED depends only on SNR of the signal received, its performance is subjected to noise power uncertainty. ED can only determine the presence/absence of signal but cannot differentiate among signal types. As a result of which it often causes false detection due to unintended CR signals. To overcome the shortcomings offered by ED, we have extensively studied Matched filter detection in different channel scenarios, and it was found that Matched filter detection performs better.