Performance Evaluation of Matched Filter Detection Using QAM Technique in CR Networks in Different Channel Conditions

Cognitive radio networks have advanced beyond 5G due to the constant need for faster data speeds and greater connection in contemporary wireless communication systems. As we navigate the uncharted territories of these advanced networks, efficient spectrum sensing becomes paramount to ensuring the optimum utilization of the limited and crowded radio frequency spectrum. For cognitive radio to employ spectrum resources effectively, spectrum sensing techniques are used. MATLAB has been utilized to evaluate the performance of matched filter detection. In this paper we have compared results simulated in Rician and Log - Normal (LN) Fading channel Distribution with AWGN channel for different QAM modulation orders, such as 64, and 256 QAM. ROC curve is used for monitoring probability of detection which is obtained for a variety of signal-to-noise ratio ranges and under different probability of false alarms (Pf) conditions. Based on the results, it is observed that the probability of detection for higher order QAM is higher for a larger number of sample values than for a lower-order modulation of QAM but it increases the latency which makes it impractical in real scenarios. For 1000 sample size and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P_{\mathrm{f}}$</tex> of 0.1, the corresponding <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$P_{\mathrm{d}}$</tex> is determined to be 0.5 for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{6 4 - M}$</tex> and for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{2 5 6}-\mathrm{M}, P_{\mathrm{d}}$</tex> is found to be 0.9.