Low Complexity Enhanced Hybrid Spectrum Sensing Architectures for Cognitive Radio Equipment
Résumé
Spectrum sensing enables detecting opportunities in licensed bands in order to access unused portions of the licensed spectrum. In this paper we propose two low complexity detectors based on a combination of two well-known and complementary signal detection mechanisms: energy detection and mono-cycle detection, which exploits cyclostationarity property of the signals. In the first algorithm the mono-cycle detector iteratively corrects the thresholds of a double threshold energy detector, that will finally converge to the performance of the mono-cycle detector. The second algorithm uses the mono-cycle detector to directly estimate the noise level N0, which is used to fix the threshold of the radiometer. Simulation results conducted on different environments show promising performances of the proposed detectors especially in low SNR.