Cooperative Cognitive Radio Networks: New Approach for Detection Accuracy Analysis Under Impaired Channels

Abstract

The quality of the reporting channel and the relaying mechanism play a significant role in cooperative spectrum sensing (CSS). However, these factors are frequently overlooked when it comes to discussing the performance of CSS in cognitive radio (CR) networks. In this work we investigate the performance of a relay-based CSS approach proposed for CR applications. Specifically, we analyze the detection accuracy of a CR network considering channel impairments, amplify-and-forward relying protocol, and a selection combining scheme. First, a closed form expression for the average false alarm probability is derived. Then, the probability density function (PDF) of the end-to-end signal-to-noise ratio (SNR) is obtained and a closed-form expression for the average detection probability at high SNR applications is derived. The sensing and the reporting channels are assumed to be subjected to independent and identically distributed Rayleigh fading. The PDF approach is used in our analysis. This approach is not easily tractable as it involves higher orders of Bessel functions. However, an approximated polynomial representation of a first-order modified Bessel function of the second kind makes this task possible. The results obtained validate the derived closed form expressions and show the importance of considering reporting channel statistics and relaying mechanism for accurate performance analysis of the CSS in CR networks.