Performance Evaluation of Decision Fusion Rules of Wireless Sensor Networks in Generalized Gaussian Noise

Generalized Gaussian Noise에서의 무선센서 네트워크의 Decision Fusion Rule의 성능 분석에 관한 연구

Fusion of decisions from multiple distributed sensor nodes is studied in this work. Based on the canonical parallel fusion model, we derive the optimal likelihood ratio based fusion rule with the assumptions of the generalized Gaussian noise model and the arbitrary fading channel. This optimal fusion rule, however, requires the complete knowledge of the channels and the detection performance of local sensor nodes. To mitigate these requirements and to provide near optimum performance, we derive suboptimum fusion rules by using high and low signal-to-noise ratio (SNR) approximations to the optimal fusion rule. Performance evaluation is conducted through simulations.