Analysis of Spectrum Sensing Based on Energy Detection Method in Cognitive Radio Networks

Spectrum sensing is an important aspect that maximizes the opportunistic usage of available spectrum. The cognitive/secondary users have to sense the spectrum repeatedly to prevent interference to licensed users. In this paper, an improved spectrum sensing model is proposed using energy detection technique. Using Central Limit theorem, an appropriate threshold is derived and the test statistics is obtained for Additive White Guassian Noise channel. The relation between detection probability and false alarm probability is derived. Computer Simulations were shown that an improved Pd can be obtained for QPSK and DVB-T signals. It has been observed that the SNR wall can be increased by increasing the number of samples of the primary signal.