Spectrum sensing for low SNR environment using maximum minimum eigenvalue (MME) detection
The rapid progression in wireless networking has suggested dynamic spectrum allocation to increase spectrum utilization. Cognitive radio (CR) is a key technology to enable dynamic spectrum access. Spectrum sensing provide spectrum awareness to CR system. Although energy detection (ED) is commonly used for spectrum sensing method, it gives poor performance under low noise environment and also suffers from noise uncertainty. Eigenvalue based detection is used to overcome ED drawbacks in this paper. Simulation results are presented for evaluating detection performance with respect to the received SNR and threshold parameters such as desired probability of false alarm (Pf) number of samples (N) and smoothing factor (L) It is shown in all cases that higher SNR value and threshold parameters setting give better probability of detection. In addition, the effect of different pulse shaping filters on probability of detection are investigated.
2016 International Seminar on Intelligent Technology and Its Applications (ISITIA)