Improved Energy Detection With Laplacian Noise in Cognitive Radio
Yinghui Ye, Yongzhao Li, Guangyue Lu, Fuhui Zhou · IEEE Systems Journal · 2017
Contaminated by Laplacian noise, the performance of energy detection (ED) degrades. To address this problem, an improved energy detection (i-ED) is proposed. Instead of the square of the received signal amplitude in the ED, an arbitrary exponent varying from 0 to 2 is adopted in the proposed algorithm. By deriving the expressions of the false alarm probability and detection probability, we propose an approach to determine the optimal exponent for a given cognitive radio system scenario. Both theoretical analysis and simulation results demonstrate that, by selecting the optimal exponent, the proposed i-ED outperforms ED and the absolute-value cumulating detection in terms of detection performance and robustness to the noise uncertainty.