Large-Signal Robustness of the Chair-Varshney Fusion Rule Under Generalized-Gaussian Noises

摘要

The Chair-Varshney rule (CVR) has been used to provide a large signal-to-noise ratio (SNR) approximation of the optimal fusion rule under Gaussian noise. For more practical use in sensor networks, this paper extends CVR to Generalized-Gaussian noise channels, along with verification of the suboptimality and robustness of CVR under the Generalized-Gaussian channel noise through the use of Monte Carlo simulations.