Asymptotic Analysis of Cooperative Spectrum Sensing under Noise Uncertainty

Abstract

In Cognitive Radio (CR), secondary radios are allowed to use the spectrum allocated to primary radios (PR) only if the spectrum is sensed to be unused by the PR users. Cooperative spectrum sensing is a sensing methodology in which secondary users send their detection results to a central fusion node for global decision. It has been shown that for single node detection, SNR wall provides a hard threshold on the sensed SNR for robust signal detection. In this paper, asymptotic performance of cooperative spectrum sensing with Hard Decision Combining (HDC) will be studied under noise uncertainty. It is first shown that under noise uncertainty, SNR wall is yet a substantial constraint on the performance of the cooperative spectrum sensing when applying HDC. We then show that k-out-of-n fusion rule with finite k (e.g., OR rule) does not result in robust detection of the PR signal, even for SNR values greater than SNR wall. Finally, it is shown that for SNR values greater than the SNR wall, the PR signal can be robustly detected by the k-out-of-n fusion rule with finite n − k (e.g., AND rule).