Improved Spectrum Sensing Method for Cognitive Radio Based on Time Domain Averaging and Correlation

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 SNR environments. With the assumption that the received signal samples 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.