Power spectrum correlation based SNR estimation for cognitive radios

In this paper, we propose a novel method of signal-to-noise ratio (SNR) estimation for cognitive radio (CR) systems at low SNRs. By jointly exploiting the second-order moment of the received signal and the correlation of the received signal power spectrum with the a priori known primary power spectrum, we obtain the estimates of both the signal power and the noise power, and the SNR estimation is thus acquired. Simulation results show that the proposed method outperforms other existing estimators in the low SNR region and the credible range of the estimated SNR extends to around -20 dB. In addition, the proposed method requires no a priori knowledge of the modulation type, making it appealing for wireless systems with adaptive modulation schemes.