Decision fusion using fuzzy threshold scheme for target detection in sensor networks

Spectrum sensing is a fundamental surveillance task and is used to detect target signal. Energy detection is a popular spectrum sensing technique. But detection performance of energy detector deteriorates in low signal-to-noise ratio (SNR) conditions and under noise uncertainty. In this paper, we proposed an energy detector with fuzzy threshold scheme for spectrum sensing, in which each sensor node sends local decision to the fusion center depending on the region in which the observed energy lies. Fusion center then makes a final global decision by combining local decisions. Analysis and simulations show that the proposed fuzzy threshold scheme could improve the detect probability effectively under 'OR','AND' and 'K-out-of-N' fusion rules, and overcome the confused region problem. Monte Carlo Simulation results also show that proposed scheme achieves better detection performance and outperforms both conventional energy detector of both single and double threshold, respectively.