Sensing Disruption with Estimation Uncertainty

In this paper, the sensing disruption for a power limited adversary with estimation uncertainty is formulated and analyzed. The estimation uncertainty of the adversary is modeled in terms of its probability of false alarm in vacant bands and the probability of detection in busy bands. The strategy for the adversary is obtained by maximizing the sum of the conditional probabilities of false detection within the spectral range of interest, conditioned on the adversary's estimated spectrum usage status. The proposed algorithm is shown to be significantly more robust than conventional algorithms. It is shown in simulation results that, as the adversary's power budget increases, the proposed algorithm asymptotically approaches the performance upper bound when the adversary has perfect information on the spectrum usage status.