A robust cyclic-feature detection against noise uncertainty - Qiang CHEN; Ming JIN; Jingwen TONG (Dianxin kexue)
The detection performance of cyclic-feature detection is much better than energy detection. However, noise uncertainty will degrade its performance severely. Aiming at this problem, a cyclic-feature detection method resisting to noise uncertainty was proposed. It was proved that the noise cyclic spectrum components at different cycle frequencies were independent and identically distributed in two-dimensional cyclic spectrum. Based on this, the noise distribution at the cycle peak was estimated using all values except the spectrum peak positions of licensed user signal, and decision threshold was obtained without noise power prior knowledge, so as to avoid the influence of noise uncertainties. Simulation results demonstrate that the performance of the proposed method is close to that of cyclic-feature detection method with known noise power.