Robust spectrum sensing algorithms under noise uncertainty

Abstract

In this paper, two spectrum sensing procedures are studied. The first one is based on a modification of the Energy Detector (ED) and the second one is based on a two-sample Goodness-of-Fit (GoF) test. The two procedures require a vector of noise samples, and are robust against noise uncertainty. Exact probability of detection are given for deterministic and Gaussian signal over additive white Gaussian noise (AWGN) and Rayleigh flat fading channel for the modified ED. Simulations show that the two procedures outperform previous schemes.