Time domain averaging and correlation-based improved spectrum sensing method for cognitive radio

摘要

Based on the combination of time domain averaging and correlation, we propose an effective time domain averaging and correlation-based spectrum sensing (TDA-C-SS) method used in very low signal-to-noise ratio (SNR) environments. With the assumption that the received signals from the primary users are deterministic, the proposed TDA-C-SS method processes the received samples by a time averaging operation to improve the SNR. Correlation operation is then performed with a correlation matrix to determine the existence of the primary signal in the received samples. The TDA-C-SS method does not need any prior information on the received samples and the associated noise power to achieve improved sensing performance. Simulation results are presented to show the effectiveness of the proposed TDA-C-SS method.