On the Reduction of the Noise Uncertainty Effects in Energy Detection for Spectrum Sensing in Cognitive Radios

For its simplicity and ease of implementation, Energy detection (ED) is attractive for spectrum sensing in cognitive radio (CR) systems. In ED, the energy captured is compared against a fixed detection threshold, which is estimated as a function of the noise power. Uncertainties caused by the imperfect knowledge of the noise power, referred to as noise uncertainty, leads to a reduced performance of the ED, particularly at low SNR levels. In this work, we introduce a novel approach that aims to overcome the SNR-wall problem of the ED caused by the noise uncertainty effects. This proposal relies on the cooperation of multiple receivers for adapting, at each sensing period, the detection threshold to the noise power present at the time of spectrum sensing process is occurring. The preliminary evaluation show that when the detection threshold is adapted to the current noise conditions, the ED observes a significant improvement on the probability of detection under the presence of noise uncertainty, compared to the non-adaptive threshold ED. Furthermore, with our proposal, the ED performs better than the well-known Eigenvalue-based Detection (EBD) and the Generalized Likelihood Ratio Test-based Detection (GLRD) for low to moderate sensing time and number of cooperating receivers.